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m-a-p/FineFineWeb-sample

m-a-p

--- license: apache-2.0 task_categories: - text-classification - text2text-generation - text-generation language: - en size_categories: - n>1T --- # FineFineWeb: A Comprehensive Study on Fine-Grained Domain Web Corpus arXiv: Coming Soon Project Page: Coming Soon Blog: Coming Soon ## Data Statistics | Domain (#tokens/#samples) | Iteration 1 Tokens | Iteration 2 Tokens | Iteration 3 Tokens | Total Tokens | Iteration 1 Count | Iteration 2 Count | Iteration 3 Count | Total Count | | --- | --- | --- | --- | --- | --- | --- | --- | --- | | aerospace | 5.77B | 261.63M | 309.33M | 6.34B | 9100000 | 688505 | 611034 | 10399539 | | agronomy | 13.08B | 947.41M | 229.04M | 14.26B | 15752828 | 2711790 | 649404 | 19114022 | | artistic | 178.25B | 5.79B | 3.75B | 187.80B | 314279703 | 16113512 | 9957104 | 340350319 | | astronomy | 5.20B | 134.39M | 54.66M | 5.38B | 7596521 | 357647 | 145832 | 8100000 | | atmospheric_science | 2.80B | 102.04M | 259.25M | 3.16B | 5709537 | 267789 | 525969 | 6503295 | | automotive | 36.72B | 436.34M | 911.65M | 38.07B | 60239679 | 1166729 | 1535882 | 62942290 | | beauty | 19.10B | 671.88M | 1.01B | 20.78B | 34787376 | 1808382 | 2201810 | 38797568 | | biology | 85.84B | 371.29M | 776.99M | 86.99B | 81413569 | 995384 | 1350348 | 83759301 | | celebrity | 9.63B | 706.41M | 4.22B | 14.56B | 19831188 | 1803788 | 7949240 | 29584216 | | chemistry | 27.80B | 588.92M | 131.46M | 28.52B | 31188189 | 1499085 | 328038 | 33015312 | | christianity | 47.72B | 403.68M | 732.55M | 48.86B | 55013147 | 1349874 | 2021458 | 58384479 | | civil_engineering | 8.85B | 1.27B | 402.91M | 10.52B | 13591632 | 2683940 | 940742 | 17216314 | | communication_engineering | 9.21B | 3.60B | 327.66M | 13.14B | 13001767 | 5959526 | 746495 | 19707788 | | computer_science_and_technology | 194.46B | 3.95B | 4.76B | 203.16B | 278420434 | 10263521 | 8654255 | 297338210 | | design | 96.58B | 3.80B | 450.00M | 100.82B | 190275603 | 16653588 | 2090515 | 209019706 | | drama_and_film | 19.12B | 10.86B | 206.27M | 30.19B | 33117478 | 18443259 | 564251 | 52124988 | | economics | 205.01B | 1.23B | 2.63B | 208.87B | 263965085 | 3874091 | 5505880 | 273345056 | | electronic_science | 30.19B | 7.76B | 482.62M | 38.43B | 42745767 | 12572747 | 1115605 | 56434119 | | entertainment | 152.92B | 1.67B | 5.06B | 159.65B | 256935144 | 5801081 | 9648023 | 272384248 | | environmental_science | 56.98B | 1.48B | 920.77M | 59.37B | 84500393 | 3557056 | 1966731 | 90024180 | | fashion | 18.72B | 977.27M | 264.01M | 19.96B | 53465628 | 3926500 | 1346988 | 58739116 | | finance | 146.39B | 327.45M | 1.13B | 147.85B | 187797764 | 1295893 | 3058801 | 192152458 | | food | 56.10B | 136.32M | 978.91M | 57.22B | 96485838 | 613875 | 3051981 | 100151694 | | gamble | 30.12B | 696.52M | 158.48M | 30.98B | 24909037 | 770540 | 164168 | 25843745 | | game | 43.47B | 2.36B | 2.68B | 48.51B | 65680699 | 4670033 | 3720700 | 74071432 | | geography | 110.18B | 1.16B | 192.67M | 111.53B | 161677214 | 3835932 | 559447 | 166072593 | | health | 191.20B | 427.93M | 18.43B | 210.06B | 215747152 | 1291215 | 23975955 | 241014322 | | history | 45.27B | 1.56B | 1.69B | 48.52B | 55710432 | 4167508 | 3463033 | 63340973 | | hobby | 150.23B | 42.78B | 44.05B | 237.06B | 276636362 | 81360893 | 71407735 | 429404990 | | hydraulic_engineering | 57.36M | 75.40M | 3.65M | 136.41M | 135079 | 163299 | 13453 | 311831 | | instrument_science | 5.35B | 2.02B | 165.43M | 7.54B | 8307736 | 2904274 | 462256 | 11674266 | | journalism_and_media_communication | 440.98B | 21.00B | 1.55B | 463.53B | 645801807 | 50657668 | 4909008 | 701368483 | | landscape_architecture | 3.07B | 557.66M | 64.76M | 3.70B | 5613141 | 1138409 | 166526 | 6918076 | | law | 128.58B | 455.19M | 2.38B | 131.42B | 166473205 | 1660944 | 6145032 | 174279181 | | library | 57.16B | 5.01B | 36.56M | 62.21B | 86592305 | 10440991 | 153014 | 97186310 | | literature | 71.07B | 7.01B | 67.53B | 145.61B | 71191075 | 13247806 | 54760578 | 139199459 | | materials_science | 17.79B | 1.11B | 303.66M | 19.20B | 22136519 | 1663376 | 708384 | 24508279 | | mathematics | 5.87B | 50.33M | 261.65M | 6.18B | 10131933 | 179592 | 653050 | 10964575 | | mechanical_engineering | 86.13B | 1.24B | 129.96M | 87.49B | 111778813 | 3201605 | 428714 | 115409132 | | medical | 140.03B | 813.46M | 4.97B | 145.81B | 149594634 | 2266477 | 8527901 | 160389012 | | mining_engineering | 7.26B | 206.05M | 529.02M | 8.00B | 5540631 | 236145 | 468458 | 6245234 | | movie | 13.09B | 639.20M | 124.67M | 13.86B | 22938808 | 1577576 | 511882 | 25028266 | | music_and_dance | 15.42B | 10.38B | 618.46M | 26.42B | 29566554 | 20233446 | 1998272 | 51798272 | | news | 328.47B | 12.37B | 11.34B | 352.18B | 508567768 | 33206709 | 23482422 | 565256899 | | nuclear_science | 559.05M | 79.89M | 78.79M | 717.72M | 784847 | 170282 | 133598 | 1088727 | | ocean_science | 2.36B | 537.82M | 229.43M | 3.13B | 3700000 | 853052 | 425792 | 4978844 | | optical_engineering | 2.33B | 253.06M | 263.99M | 2.85B | 3510836 | 535026 | 400371 | 4446233 | | painting | 374.41M | 429.63M | 96.57M | 900.61M | 875783 | 824217 | 336203 | 2036203 | | pet | 12.12B | 154.14M | 307.28M | 12.58B | 19624688 | 457635 | 778970 | 20861293 | | petroleum_and_natural_gas_engineering | 950.08M | 515.05M | 121.56M | 1.59B | 1669447 | 899860 | 237843 | 2807150 | | philosophy | 47.99B | 121.26M | 335.77M | 48.44B | 50396964 | 505275 | 1030405 | 51932644 | | photo | 6.56B | 1.74B | 41.44M | 8.34B | 16194329 | 3901598 | 179607 | 20275534 | | physics | 21.56B | 372.21M | 191.17M | 22.12B | 24640373 | 843508 | 473758 | 25957639 | | politics | 79.52B | 253.26M | 930.96M | 80.70B | 97403603 | 1026315 | 2504127 | 100934045 | | psychology | 51.53B | 688.50M | 2.56B | 54.78B | 58829917 | 1881452 | 4066667 | 64778036 | | public_administration | 100.13B | 5.54B | 716.81M | 106.39B | 160247751 | 10657768 | 1785347 | 172690866 | | relationship | 21.87B | 3.69B | 129.60M | 25.69B | 28153321 | 6794774 | 321268 | 35269363 | | sociology | 76.34B | 3.59B | 8.88B | 88.82B | 106447186 | 7836896 | 13040695 | 127324777 | | sports | 118.64B | 379.18M | 1.79B | 120.80B | 173243631 | 1286718 | 4212540 | 178742889 | | statistics | 19.59B | 1.15B | 1.75B | 22.49B | 29958726 | 2746797 | 3390606 | 36096129 | | systems_science | 24.58B | 11.30B | 163.99M | 36.05B | 32879249 | 15120751 | 470001 | 48470001 | | textile_science | 2.59B | 2.89B | 94.56M | 5.57B | 8018141 | 8022001 | 456668 | 16496810 | | topicality | 34.87M | 5.22M | 0 | 40.09M | 137789 | 13506 | 0 | 151295 | | transportation_engineering | 12.80B | 6.61B | 972.50M | 20.38B | 23595624 | 11005933 | 2027812 | 36629369 | | travel | 78.87B | 584.78M | 957.26M | 80.41B | 127250195 | 1851342 | 2430704 | 131532241 | | urban_planning | 12.13B | 2.93B | 53.24M | 15.12B | 20040937 | 6176104 | 201963 | 26419004 | | weapons_science | 80.62M | 3.32B | 140.89M | 3.54B | 215544 | 5695154 | 369541 | 6280239 | | Grand Total | 4010.76B | 206.51B | 208.02B | 4425.30B | 5781764055 | 442387964 | 311920860 | 6536072879 | ## Data Construction Workflow  The data construction workflow can be summarized as follows: 1. **Deduplicate**: The FineWeb dataset is deduplicated using exact deduplication and MinHash techniques to remove redundant data. 2. **URL Labeling**: Root URLs from FineWeb are counted, and the top 1 million URLs are labeled using **GPT-4**. This step generates **DoI (Domain-of-Interest) Coarse-Grained URLs** and **DoNI (Domain-of-Non-Interest) Coarse-Grained URLs** as seed data sources. 3. **Coarse Recall**: a. Based on the labeled root URLs, data is sampled for each domain. b. The sampled data is labeled using **Qwen2-7B-Instruct**, producing 500K **DoI Positive Data** and 500K **DoI Negative Data** (note that for N>1 iterations, each 500K samples are composed of 250K sampled original seed data and 250K refined data after Fine Recall). c. A binary **FastText** model is trained per domain using the labeled data. d. The FastText model performs **coarse recall** on FineWeb, generating **Coarse DoI Data**. 4. **Fine Recall**: a. The **Coarse DoI Data** is labeled using **Qwen2-72B-Instruct** to produce **100K DoI Positive Data** and **50K DoI Negative Data**, with the latter further augmented with 50K negative samples from earlier FastText training. b. A **BERT** model is trained using this labeled data. c. The BERT model performs **fine recall** on the Coarse DoI Data, producing a refined dataset, which is the DoI subset of **FineFineWeb**. 5. **Coarse-Fine Recall Iteration**: The workflow of coarse and fine recall iterates for **3 rounds** with the following adjustments: a. FastText is re-trained using updated seed data, which combines BERT-recalled samples, BERT-dropped samples, and previously labeled seed data. b. The BERT model keeps frozen during subsequent iterations. c. Steps for training FastText, coarse recall, and fine recall are repeated without re-labeling data with Qwen2-Instruct models. ## Domain-Domain Similarity Analysis 1. Perform proportional weighted sampling of the domain subsets based on the sample size of each domain, with a total of 1 billion tokens sampled from the domain subsets. 2. Use the BGE-M3 model to compute the embeddings of the samples in each domain subset, referred to as domain embeddings. 3. Use the BGE-M3 model to compute the embeddings of the samples in each benchmark, referred to as benchmark embeddings (bench embeddings). 4. Calculate the MMD distance and the Wasserstein distance between the domain embeddings and the benchmark embeddings.  The results above reveal the following observations: 1. The two code-related benchmarks, MBPP and HumanEval, exhibit relatively large distances from nearly all domains, indicating that the proportion of code data in the training set is relatively small. Notably, their distance to the mathematics domain is comparatively smaller, suggesting a certain degree of overlap between mathematics data and code data. 2. Benchmarks such as Hellaswag, ARC, MMLU, and BoolQ have distances that are close to almost all domains, except for the gamble domain. This indicates that the samples in these benchmarks involve synergetic effects across multiple domains of knowledge, with a wide distribution. 3. GSM8K and TriviaQA show significant discrepancies with a small number of domains, suggesting that the distribution differences between domains are more pronounced for samples involving grade-school mathematics and fact-based question answering. Some domains contain a substantial amount of this type of data, while others do not. 4. The gamble domain exhibits substantial differences from other domains and has large distances from all benchmarks, indicating that pretraining data related to gambling provides limited benefits for these benchmarks. ## Domain-Domain Duplication Let \\(D_1, D_2, \dots, D_N\\) represent \\(N\\) distinct domains, where we select top-20 URLs for each domain \\(D_i\\), denoted as \\(\{U_{i1}, U_{i2}, \dots, U_{i20}\}\\),. The total set of URLs across all domains is represented as \\(\mathcal{U}\\), and the total number of URLs is \\(M = |\mathcal{U}|\\). For each URL \\(U_k \in \mathcal{U}\\), the term frequency (TF) is defined as the proportion of \\(U_k\\) in the total set of URLs: \\(\text{TF}(U_k) = \frac{\text{count}(U_k)}{M}\\) where \\(\text{count}(U_k)\\) is the number of times \\(U_k\\) appears in \\(\mathcal{U}\\). Additionally, the document frequency \\(K_k\\) of \\(U_k\\) is the number of domains in which \\(U_k\\) appears. Based on this, the inverse document frequency (IDF) is calculated as: \\(\text{IDF}(U_k) = \log(\frac{N}{K_k})\\) The TF-IDF value for each URL \\(U_{ij}\\) in a specific domain \\(D_i\\) is then computed as: \\(\text{TF-IDF}(U_{ij}) = \text{TF}(U_{ij}) \times \text{IDF}(U_{ij})\\)  Using the TF-IDF values of all URLs within a domain, the domain-domain duplicate rate can be analyzed by comparing the **distribution** of TF-IDF values across domains. If a domain has many URLs with **high TF-IDF values**, it indicates that the domain’s URLs are relatively **unique** and significant within the entire set of URLs. Conversely, if a domain has many URLs with **low TF-IDF values**, it suggests that the domain's URLs are more **common** across other domains. Analyzing these values helps assess how similar or redundant a domain's content is in relation to others based on its URL composition. As shown in the figure, most domains have low duplication rates, except for topicality, pet, and atmospheric science. ## **Domain-Benchmark BPC-Acc Correlation** Experimental method: Using 28 models (see the paper), we first calculate BPC for all domains to obtain a model ranking \\(R_D\\). Similarly, we compute scores across all benchmarks to obtain a model ranking \\(R_M\\). We then calculate the Spearman correlation between \\(R_D\\) and \\(R_M\\).  - For benchmarks like ARC, MMLU, GSM8K, HumanEval, and MBPP, STEM-related domains show higher correlation rankings, particularly mathematics, physics, and systems science. - For TriviaQA, which emphasizes factual knowledge over reasoning, domains rich in world knowledge such as literature, history, and library science demonstrate higher correlation rankings. ## Bibtex ```bibtex @misc{ title={FineFineWeb: A Comprehensive Study on Fine-grained Domain Web Corpus}, url={[https://huggingface.co/datasets/m-a-p/FineFineWeb](https://huggingface.co/datasets/m-a-p/FineFineWeb)}, author = {M-A-P, Ge Zhang*, Xinrun Du*, Zhimiao Yu*, Zili Wang*, Zekun Wang, Shuyue Guo, Tianyu Zheng, Kang Zhu, Jerry Liu, Shawn Yue, Binbin Liu, Zhongyuan Peng, Yifan Yao, Jack Yang, Ziming Li, Bingni Zhang, Minghao Liu, Tianyu Liu, Yang Gao, Wenhu Chen, Xiaohuan Zhou, Qian Liu, Taifeng Wang+, Wenhao Huang+}, publisher={huggingface}, verision={v0.1.0}, month={December}, year={2024} } ```

lighteval/mmlu

lighteval

--- annotations_creators: - no-annotation language_creators: - expert-generated language: - en license: - mit multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - question-answering task_ids: - multiple-choice-qa paperswithcode_id: mmlu pretty_name: Measuring Massive Multitask Language Understanding language_bcp47: - en-US dataset_info: - config_name: abstract_algebra features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 19328 num_examples: 100 - name: validation num_bytes: 2024 num_examples: 11 - name: dev num_bytes: 830 num_examples: 5 download_size: 166184960 dataset_size: 160623559 - config_name: anatomy features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 33121 num_examples: 135 - name: validation num_bytes: 3140 num_examples: 14 - name: dev num_bytes: 967 num_examples: 5 download_size: 166184960 dataset_size: 160638605 - config_name: astronomy features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 46771 num_examples: 152 - name: validation num_bytes: 5027 num_examples: 16 - name: dev num_bytes: 2076 num_examples: 5 download_size: 166184960 dataset_size: 160655251 - config_name: business_ethics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 33252 num_examples: 100 - name: validation num_bytes: 3038 num_examples: 11 - name: dev num_bytes: 2190 num_examples: 5 download_size: 166184960 dataset_size: 160639857 - config_name: clinical_knowledge features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 62754 num_examples: 265 - name: validation num_bytes: 6664 num_examples: 29 - name: dev num_bytes: 1210 num_examples: 5 download_size: 166184960 dataset_size: 160672005 - config_name: college_biology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 48797 num_examples: 144 - name: validation num_bytes: 4819 num_examples: 16 - name: dev num_bytes: 1532 num_examples: 5 download_size: 166184960 dataset_size: 160656525 - config_name: college_chemistry features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 24708 num_examples: 100 - name: validation num_bytes: 2328 num_examples: 8 - name: dev num_bytes: 1331 num_examples: 5 download_size: 166184960 dataset_size: 160629744 - config_name: college_computer_science features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 42641 num_examples: 100 - name: validation num_bytes: 4663 num_examples: 11 - name: dev num_bytes: 2765 num_examples: 5 download_size: 166184960 dataset_size: 160651446 - config_name: college_mathematics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 24711 num_examples: 100 - name: validation num_bytes: 2668 num_examples: 11 - name: dev num_bytes: 1493 num_examples: 5 download_size: 166184960 dataset_size: 160630249 - config_name: college_medicine features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 82397 num_examples: 173 - name: validation num_bytes: 7909 num_examples: 22 - name: dev num_bytes: 1670 num_examples: 5 download_size: 166184960 dataset_size: 160693353 - config_name: college_physics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 30181 num_examples: 102 - name: validation num_bytes: 3490 num_examples: 11 - name: dev num_bytes: 1412 num_examples: 5 download_size: 166184960 dataset_size: 160636460 - config_name: computer_security features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 27124 num_examples: 100 - name: validation num_bytes: 4549 num_examples: 11 - name: dev num_bytes: 1101 num_examples: 5 download_size: 166184960 dataset_size: 160634151 - config_name: conceptual_physics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 40709 num_examples: 235 - name: validation num_bytes: 4474 num_examples: 26 - name: dev num_bytes: 934 num_examples: 5 download_size: 166184960 dataset_size: 160647494 - config_name: econometrics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 46547 num_examples: 114 - name: validation num_bytes: 4967 num_examples: 12 - name: dev num_bytes: 1644 num_examples: 5 download_size: 166184960 dataset_size: 160654535 - config_name: electrical_engineering features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 25142 num_examples: 145 - name: validation num_bytes: 2903 num_examples: 16 - name: dev num_bytes: 972 num_examples: 5 download_size: 166184960 dataset_size: 160630394 - config_name: elementary_mathematics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 70108 num_examples: 378 - name: validation num_bytes: 8988 num_examples: 41 - name: dev num_bytes: 1440 num_examples: 5 download_size: 166184960 dataset_size: 160681913 - config_name: formal_logic features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 49785 num_examples: 126 - name: validation num_bytes: 6252 num_examples: 14 - name: dev num_bytes: 1757 num_examples: 5 download_size: 166184960 dataset_size: 160659171 - config_name: global_facts features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 18403 num_examples: 100 - name: validation num_bytes: 1865 num_examples: 10 - name: dev num_bytes: 1229 num_examples: 5 download_size: 166184960 dataset_size: 160622874 - config_name: high_school_biology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 109732 num_examples: 310 - name: validation num_bytes: 11022 num_examples: 32 - name: dev num_bytes: 1673 num_examples: 5 download_size: 166184960 dataset_size: 160723804 - config_name: high_school_chemistry features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 58464 num_examples: 203 - name: validation num_bytes: 7092 num_examples: 22 - name: dev num_bytes: 1220 num_examples: 5 download_size: 166184960 dataset_size: 160668153 - config_name: high_school_computer_science features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 44476 num_examples: 100 - name: validation num_bytes: 3343 num_examples: 9 - name: dev num_bytes: 2918 num_examples: 5 download_size: 166184960 dataset_size: 160652114 - config_name: high_school_european_history features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 270300 num_examples: 165 - name: validation num_bytes: 29632 num_examples: 18 - name: dev num_bytes: 11564 num_examples: 5 download_size: 166184960 dataset_size: 160912873 - config_name: high_school_geography features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 42034 num_examples: 198 - name: validation num_bytes: 4332 num_examples: 22 - name: dev num_bytes: 1403 num_examples: 5 download_size: 166184960 dataset_size: 160649146 - config_name: high_school_government_and_politics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 66074 num_examples: 193 - name: validation num_bytes: 7063 num_examples: 21 - name: dev num_bytes: 1779 num_examples: 5 download_size: 166184960 dataset_size: 160676293 - config_name: high_school_macroeconomics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 117687 num_examples: 390 - name: validation num_bytes: 13020 num_examples: 43 - name: dev num_bytes: 1328 num_examples: 5 download_size: 166184960 dataset_size: 160733412 - config_name: high_school_mathematics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 54854 num_examples: 270 - name: validation num_bytes: 5765 num_examples: 29 - name: dev num_bytes: 1297 num_examples: 5 download_size: 166184960 dataset_size: 160663293 - config_name: high_school_microeconomics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 75703 num_examples: 238 - name: validation num_bytes: 7553 num_examples: 26 - name: dev num_bytes: 1298 num_examples: 5 download_size: 166184960 dataset_size: 160685931 - config_name: high_school_physics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 59538 num_examples: 151 - name: validation num_bytes: 6771 num_examples: 17 - name: dev num_bytes: 1489 num_examples: 5 download_size: 166184960 dataset_size: 160669175 - config_name: high_school_psychology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 159407 num_examples: 545 - name: validation num_bytes: 17269 num_examples: 60 - name: dev num_bytes: 1905 num_examples: 5 download_size: 166184960 dataset_size: 160779958 - config_name: high_school_statistics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 110702 num_examples: 216 - name: validation num_bytes: 9997 num_examples: 23 - name: dev num_bytes: 2528 num_examples: 5 download_size: 166184960 dataset_size: 160724604 - config_name: high_school_us_history features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 296734 num_examples: 204 - name: validation num_bytes: 31706 num_examples: 22 - name: dev num_bytes: 8864 num_examples: 5 download_size: 166184960 dataset_size: 160938681 - config_name: high_school_world_history features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 378617 num_examples: 237 - name: validation num_bytes: 45501 num_examples: 26 - name: dev num_bytes: 4882 num_examples: 5 download_size: 166184960 dataset_size: 161030377 - config_name: human_aging features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 46098 num_examples: 223 - name: validation num_bytes: 4707 num_examples: 23 - name: dev num_bytes: 1008 num_examples: 5 download_size: 166184960 dataset_size: 160653190 - config_name: human_sexuality features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 32110 num_examples: 131 - name: validation num_bytes: 2421 num_examples: 12 - name: dev num_bytes: 1077 num_examples: 5 download_size: 166184960 dataset_size: 160636985 - config_name: international_law features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 53531 num_examples: 121 - name: validation num_bytes: 6473 num_examples: 13 - name: dev num_bytes: 2418 num_examples: 5 download_size: 166184960 dataset_size: 160663799 - config_name: jurisprudence features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 33986 num_examples: 108 - name: validation num_bytes: 3729 num_examples: 11 - name: dev num_bytes: 1303 num_examples: 5 download_size: 166184960 dataset_size: 160640395 - config_name: logical_fallacies features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 50117 num_examples: 163 - name: validation num_bytes: 5103 num_examples: 18 - name: dev num_bytes: 1573 num_examples: 5 download_size: 166184960 dataset_size: 160658170 - config_name: machine_learning features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 33880 num_examples: 112 - name: validation num_bytes: 3232 num_examples: 11 - name: dev num_bytes: 2323 num_examples: 5 download_size: 166184960 dataset_size: 160640812 - config_name: management features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 20002 num_examples: 103 - name: validation num_bytes: 1820 num_examples: 11 - name: dev num_bytes: 898 num_examples: 5 download_size: 166184960 dataset_size: 160624097 - config_name: marketing features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 63025 num_examples: 234 - name: validation num_bytes: 7394 num_examples: 25 - name: dev num_bytes: 1481 num_examples: 5 download_size: 166184960 dataset_size: 160673277 - config_name: medical_genetics features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 20864 num_examples: 100 - name: validation num_bytes: 3005 num_examples: 11 - name: dev num_bytes: 1089 num_examples: 5 download_size: 166184960 dataset_size: 160626335 - config_name: miscellaneous features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 147704 num_examples: 783 - name: validation num_bytes: 14330 num_examples: 86 - name: dev num_bytes: 699 num_examples: 5 download_size: 166184960 dataset_size: 160764110 - config_name: moral_disputes features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 107818 num_examples: 346 - name: validation num_bytes: 12420 num_examples: 38 - name: dev num_bytes: 1755 num_examples: 5 download_size: 166184960 dataset_size: 160723370 - config_name: moral_scenarios features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 374026 num_examples: 895 - name: validation num_bytes: 42338 num_examples: 100 - name: dev num_bytes: 2058 num_examples: 5 download_size: 166184960 dataset_size: 161019799 - config_name: nutrition features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 92410 num_examples: 306 - name: validation num_bytes: 8436 num_examples: 33 - name: dev num_bytes: 2085 num_examples: 5 download_size: 166184960 dataset_size: 160704308 - config_name: philosophy features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 80073 num_examples: 311 - name: validation num_bytes: 9184 num_examples: 34 - name: dev num_bytes: 988 num_examples: 5 download_size: 166184960 dataset_size: 160691622 - config_name: prehistory features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 89594 num_examples: 324 - name: validation num_bytes: 10285 num_examples: 35 - name: dev num_bytes: 1878 num_examples: 5 download_size: 166184960 dataset_size: 160703134 - config_name: professional_accounting features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 124550 num_examples: 282 - name: validation num_bytes: 14372 num_examples: 31 - name: dev num_bytes: 2148 num_examples: 5 download_size: 166184960 dataset_size: 160742447 - config_name: professional_law features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 1891762 num_examples: 1534 - name: validation num_bytes: 203519 num_examples: 170 - name: dev num_bytes: 6610 num_examples: 5 download_size: 166184960 dataset_size: 162703268 - config_name: professional_medicine features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 217561 num_examples: 272 - name: validation num_bytes: 23847 num_examples: 31 - name: dev num_bytes: 3807 num_examples: 5 download_size: 166184960 dataset_size: 160846592 - config_name: professional_psychology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 225899 num_examples: 612 - name: validation num_bytes: 29101 num_examples: 69 - name: dev num_bytes: 2267 num_examples: 5 download_size: 166184960 dataset_size: 160858644 - config_name: public_relations features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 28760 num_examples: 110 - name: validation num_bytes: 4566 num_examples: 12 - name: dev num_bytes: 1496 num_examples: 5 download_size: 166184960 dataset_size: 160636199 - config_name: security_studies features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 204844 num_examples: 245 - name: validation num_bytes: 22637 num_examples: 27 - name: dev num_bytes: 5335 num_examples: 5 download_size: 166184960 dataset_size: 160834193 - config_name: sociology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 66243 num_examples: 201 - name: validation num_bytes: 7184 num_examples: 22 - name: dev num_bytes: 1613 num_examples: 5 download_size: 166184960 dataset_size: 160676417 - config_name: us_foreign_policy features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 28443 num_examples: 100 - name: validation num_bytes: 3264 num_examples: 11 - name: dev num_bytes: 1611 num_examples: 5 download_size: 166184960 dataset_size: 160634695 - config_name: virology features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 38759 num_examples: 166 - name: validation num_bytes: 5463 num_examples: 18 - name: dev num_bytes: 1096 num_examples: 5 download_size: 166184960 dataset_size: 160646695 - config_name: world_religions features: - name: question dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: auxiliary_train num_bytes: 160601377 num_examples: 99842 - name: test num_bytes: 25274 num_examples: 171 - name: validation num_bytes: 2765 num_examples: 19 - name: dev num_bytes: 670 num_examples: 5 download_size: 166184960 dataset_size: 160630086 --- # Dataset Card for MMLU ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository**: https://github.com/hendrycks/test - **Paper**: https://arxiv.org/abs/2009.03300 ### Dataset Summary [Measuring Massive Multitask Language Understanding](https://arxiv.org/pdf/2009.03300) by [Dan Hendrycks](https://people.eecs.berkeley.edu/~hendrycks/), [Collin Burns](http://collinpburns.com), [Steven Basart](https://stevenbas.art), Andy Zou, Mantas Mazeika, [Dawn Song](https://people.eecs.berkeley.edu/~dawnsong/), and [Jacob Steinhardt](https://www.stat.berkeley.edu/~jsteinhardt/) (ICLR 2021). This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge. The test spans subjects in the humanities, social sciences, hard sciences, and other areas that are important for some people to learn. This covers 57 tasks including elementary mathematics, US history, computer science, law, and more. To attain high accuracy on this test, models must possess extensive world knowledge and problem solving ability. A complete list of tasks: ['abstract_algebra', 'anatomy', 'astronomy', 'business_ethics', 'clinical_knowledge', 'college_biology', 'college_chemistry', 'college_computer_science', 'college_mathematics', 'college_medicine', 'college_physics', 'computer_security', 'conceptual_physics', 'econometrics', 'electrical_engineering', 'elementary_mathematics', 'formal_logic', 'global_facts', 'high_school_biology', 'high_school_chemistry', 'high_school_computer_science', 'high_school_european_history', 'high_school_geography', 'high_school_government_and_politics', 'high_school_macroeconomics', 'high_school_mathematics', 'high_school_microeconomics', 'high_school_physics', 'high_school_psychology', 'high_school_statistics', 'high_school_us_history', 'high_school_world_history', 'human_aging', 'human_sexuality', 'international_law', 'jurisprudence', 'logical_fallacies', 'machine_learning', 'management', 'marketing', 'medical_genetics', 'miscellaneous', 'moral_disputes', 'moral_scenarios', 'nutrition', 'philosophy', 'prehistory', 'professional_accounting', 'professional_law', 'professional_medicine', 'professional_psychology', 'public_relations', 'security_studies', 'sociology', 'us_foreign_policy', 'virology', 'world_religions'] ### Supported Tasks and Leaderboards | Model | Authors | Humanities | Social Science | STEM | Other | Average | |------------------------------------|----------|:-------:|:-------:|:-------:|:-------:|:-------:| | [UnifiedQA](https://arxiv.org/abs/2005.00700) | Khashabi et al., 2020 | 45.6 | 56.6 | 40.2 | 54.6 | 48.9 | [GPT-3](https://arxiv.org/abs/2005.14165) (few-shot) | Brown et al., 2020 | 40.8 | 50.4 | 36.7 | 48.8 | 43.9 | [GPT-2](https://arxiv.org/abs/2005.14165) | Radford et al., 2019 | 32.8 | 33.3 | 30.2 | 33.1 | 32.4 | Random Baseline | N/A | 25.0 | 25.0 | 25.0 | 25.0 | 25.0 | 25.0 ### Languages English ## Dataset Structure ### Data Instances An example from anatomy subtask looks as follows: ``` { "question": "What is the embryological origin of the hyoid bone?", "choices": ["The first pharyngeal arch", "The first and second pharyngeal arches", "The second pharyngeal arch", "The second and third pharyngeal arches"], "answer": "D" } ``` ### Data Fields - `question`: a string feature - `choices`: a list of 4 string features - `answer`: a ClassLabel feature ### Data Splits - `auxiliary_train`: auxiliary multiple-choice training questions from ARC, MC_TEST, OBQA, RACE, etc. - `dev`: 5 examples per subtask, meant for few-shot setting - `test`: there are at least 100 examples per subtask | | auxiliary_train | dev | val | test | | ----- | :------: | :-----: | :-----: | :-----: | | TOTAL | 99842 | 285 | 1531 | 14042 ## Dataset Creation ### Curation Rationale Transformer models have driven this recent progress by pretraining on massive text corpora, including all of Wikipedia, thousands of books, and numerous websites. These models consequently see extensive information about specialized topics, most of which is not assessed by existing NLP benchmarks. To bridge the gap between the wide-ranging knowledge that models see during pretraining and the existing measures of success, we introduce a new benchmark for assessing models across a diverse set of subjects that humans learn. ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [MIT License](https://github.com/hendrycks/test/blob/master/LICENSE) ### Citation Information If you find this useful in your research, please consider citing the test and also the [ETHICS](https://arxiv.org/abs/2008.02275) dataset it draws from: ``` @article{hendryckstest2021, title={Measuring Massive Multitask Language Understanding}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } @article{hendrycks2021ethics, title={Aligning AI With Shared Human Values}, author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt}, journal={Proceedings of the International Conference on Learning Representations (ICLR)}, year={2021} } ``` ### Contributions Thanks to [@andyzoujm](https://github.com/andyzoujm) for adding this dataset.

parsee-mizuhashi/phony

parsee-mizuhashi

--- license: mit ---

asahi417/seamless-align-enA-jaA.speaker-embedding.w2vbert-600m

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8702948037 num_examples: 2073 download_size: 8727623134 dataset_size: 8702948037 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7741197905 num_examples: 1961 download_size: 7763639836 dataset_size: 7741197905 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7539350527 num_examples: 1757 download_size: 7561057648 dataset_size: 7539350527 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - 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name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8113098778 num_examples: 1887 download_size: 8136177900 dataset_size: 8113098778 - config_name: subset_84 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8028612558 num_examples: 1867 download_size: 8051652570 dataset_size: 8028612558 - config_name: subset_85 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8013488805 num_examples: 1881 download_size: 8036620744 dataset_size: 8013488805 - config_name: subset_86 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8003745635 num_examples: 1862 download_size: 8026803981 dataset_size: 8003745635 - config_name: subset_87 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8111430876 num_examples: 1897 download_size: 8134546716 dataset_size: 8111430876 - config_name: subset_88 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8169999635 num_examples: 1900 download_size: 8193073930 dataset_size: 8169999635 - config_name: subset_89 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8168994077 num_examples: 1886 download_size: 8192016527 dataset_size: 8168994077 - config_name: subset_9 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7774163187 num_examples: 1977 download_size: 7796635468 dataset_size: 7774163187 - config_name: subset_90 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8158902032 num_examples: 1913 download_size: 8182056469 dataset_size: 8158902032 - config_name: subset_91 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8216019083 num_examples: 1913 download_size: 8239110705 dataset_size: 8216019083 - config_name: subset_92 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8020696970 num_examples: 1886 download_size: 8043835828 dataset_size: 8020696970 - config_name: subset_93 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8156262613 num_examples: 1875 download_size: 8179255387 dataset_size: 8156262613 - config_name: subset_94 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8187014650 num_examples: 1900 download_size: 8210091027 dataset_size: 8187014650 - config_name: subset_95 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8012114087 num_examples: 1867 download_size: 8035176759 dataset_size: 8012114087 - config_name: subset_96 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8249310045 num_examples: 1900 download_size: 8272336908 dataset_size: 8249310045 - config_name: subset_97 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8256956441 num_examples: 1899 download_size: 8279963650 dataset_size: 8256956441 - config_name: subset_98 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8255128221 num_examples: 1904 download_size: 8278159024 dataset_size: 8255128221 - config_name: subset_99 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: jaA.id dtype: string - name: jaA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: jaA.audio.speaker_embedding sequence: float32 - name: jaA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8303626853 num_examples: 1901 download_size: 8326615297 dataset_size: 8303626853 configs: - config_name: subset_1 data_files: - split: train path: subset_1/train-* - config_name: subset_10 data_files: - split: train path: subset_10/train-* - config_name: subset_100 data_files: - split: train path: subset_100/train-* - config_name: subset_101 data_files: - split: train path: subset_101/train-* - config_name: subset_102 data_files: - split: train path: subset_102/train-* - config_name: subset_103 data_files: - split: train path: subset_103/train-* - config_name: subset_104 data_files: - split: train path: subset_104/train-* - config_name: subset_105 data_files: - split: train path: subset_105/train-* - config_name: subset_106 data_files: - split: train path: subset_106/train-* - config_name: subset_107 data_files: - split: train path: subset_107/train-* - config_name: subset_108 data_files: - split: train path: subset_108/train-* - config_name: subset_109 data_files: - split: train path: subset_109/train-* - config_name: subset_11 data_files: - split: train path: subset_11/train-* - config_name: subset_110 data_files: - split: train path: subset_110/train-* - config_name: subset_111 data_files: - split: train path: subset_111/train-* - config_name: subset_112 data_files: - split: train path: subset_112/train-* - config_name: subset_113 data_files: - split: train path: subset_113/train-* - config_name: subset_114 data_files: - split: train path: subset_114/train-* - config_name: subset_115 data_files: - split: train path: subset_115/train-* - config_name: subset_116 data_files: - split: train path: subset_116/train-* - config_name: subset_117 data_files: - split: train path: subset_117/train-* - config_name: subset_118 data_files: - split: train path: subset_118/train-* - config_name: subset_119 data_files: - split: train path: subset_119/train-* - config_name: subset_12 data_files: - split: train path: subset_12/train-* - config_name: subset_120 data_files: - split: train path: subset_120/train-* - config_name: subset_121 data_files: - split: train path: subset_121/train-* - config_name: subset_122 data_files: - split: train path: subset_122/train-* - config_name: subset_123 data_files: - split: train path: subset_123/train-* - config_name: subset_124 data_files: - split: train path: subset_124/train-* - config_name: subset_125 data_files: - split: train path: subset_125/train-* - config_name: subset_126 data_files: - split: train path: subset_126/train-* - config_name: subset_127 data_files: - split: train path: subset_127/train-* - config_name: subset_128 data_files: - split: train path: subset_128/train-* - config_name: subset_129 data_files: - split: train path: subset_129/train-* - config_name: subset_13 data_files: - split: train path: subset_13/train-* - config_name: subset_130 data_files: - split: train path: subset_130/train-* - config_name: subset_131 data_files: - split: train path: subset_131/train-* - config_name: subset_132 data_files: - split: train path: subset_132/train-* - config_name: subset_133 data_files: - split: train path: subset_133/train-* - config_name: subset_134 data_files: - split: train path: subset_134/train-* - config_name: subset_135 data_files: - split: train path: subset_135/train-* - config_name: subset_136 data_files: - split: train path: subset_136/train-* - config_name: subset_137 data_files: - split: train path: subset_137/train-* - config_name: subset_138 data_files: - split: train path: subset_138/train-* - config_name: subset_139 data_files: - split: train path: subset_139/train-* - config_name: subset_14 data_files: - split: train path: subset_14/train-* - config_name: subset_140 data_files: - split: train path: subset_140/train-* - config_name: subset_141 data_files: - split: train path: subset_141/train-* - config_name: subset_142 data_files: - split: train path: subset_142/train-* - config_name: subset_143 data_files: - split: train path: subset_143/train-* - config_name: subset_144 data_files: - split: train path: subset_144/train-* - config_name: subset_15 data_files: - split: train path: subset_15/train-* - config_name: subset_16 data_files: - split: train path: subset_16/train-* - config_name: subset_17 data_files: - split: train path: subset_17/train-* - config_name: subset_18 data_files: - split: train path: subset_18/train-* - config_name: subset_19 data_files: - split: train path: subset_19/train-* - config_name: subset_2 data_files: - split: train path: subset_2/train-* - config_name: subset_20 data_files: - split: train path: subset_20/train-* - config_name: subset_21 data_files: - split: train path: subset_21/train-* - config_name: subset_22 data_files: - split: train path: subset_22/train-* - config_name: subset_23 data_files: - split: train path: subset_23/train-* - config_name: subset_24 data_files: - split: train path: subset_24/train-* - config_name: subset_25 data_files: - split: train path: subset_25/train-* - config_name: subset_26 data_files: - split: train path: subset_26/train-* - config_name: subset_27 data_files: - split: train path: subset_27/train-* - config_name: subset_28 data_files: - split: train path: subset_28/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_35 data_files: - split: train path: subset_35/train-* - config_name: subset_36 data_files: - split: train path: subset_36/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_44 data_files: - split: train path: subset_44/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_46 data_files: - split: train path: subset_46/train-* - config_name: subset_47 data_files: - split: train path: subset_47/train-* - config_name: subset_48 data_files: - split: train path: subset_48/train-* - config_name: subset_49 data_files: - split: train path: subset_49/train-* - config_name: subset_5 data_files: - split: train path: subset_5/train-* - config_name: subset_50 data_files: - split: train path: subset_50/train-* - config_name: subset_51 data_files: - split: train path: subset_51/train-* - config_name: subset_52 data_files: - split: train path: subset_52/train-* - config_name: subset_53 data_files: - split: train path: subset_53/train-* - config_name: subset_54 data_files: - split: train path: subset_54/train-* - config_name: subset_55 data_files: - split: train path: subset_55/train-* - config_name: subset_56 data_files: - split: train path: subset_56/train-* - config_name: subset_57 data_files: - split: train path: subset_57/train-* - config_name: subset_58 data_files: - split: train path: subset_58/train-* - config_name: subset_59 data_files: - split: train path: subset_59/train-* - config_name: subset_6 data_files: - split: train path: subset_6/train-* - config_name: subset_60 data_files: - split: train path: subset_60/train-* - config_name: subset_61 data_files: - split: train path: subset_61/train-* - config_name: subset_62 data_files: - split: train path: subset_62/train-* - config_name: subset_63 data_files: - split: train path: subset_63/train-* - config_name: subset_64 data_files: - split: train path: subset_64/train-* - config_name: subset_65 data_files: - split: train path: subset_65/train-* - config_name: subset_66 data_files: - split: train path: subset_66/train-* - config_name: subset_67 data_files: - split: train path: subset_67/train-* - config_name: subset_68 data_files: - split: train path: subset_68/train-* - config_name: subset_69 data_files: - split: train path: subset_69/train-* - config_name: subset_7 data_files: - split: train path: subset_7/train-* - config_name: subset_70 data_files: - split: train path: subset_70/train-* - config_name: subset_71 data_files: - split: train path: subset_71/train-* - config_name: subset_72 data_files: - split: train path: subset_72/train-* - config_name: subset_73 data_files: - split: train path: subset_73/train-* - config_name: subset_74 data_files: - split: train path: subset_74/train-* - config_name: subset_75 data_files: - split: train path: subset_75/train-* - config_name: subset_76 data_files: - split: train path: subset_76/train-* - config_name: subset_77 data_files: - split: train path: subset_77/train-* - config_name: subset_78 data_files: - split: train path: subset_78/train-* - config_name: subset_79 data_files: - split: train path: subset_79/train-* - config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

wis-k/instruction-following-eval

wis-k

--- license: apache-2.0 ---

djstrong/oscar-small

djstrong

--- annotations_creators: - no-annotation language_creators: - found language: - af - am - ar - arz - as - az - azb - ba - be - bg - bn - bo - br - ca - ce - ceb - ckb - cs - cv - cy - da - de - dv - el - en - eo - es - et - eu - fa - fi - fr - fy - ga - gl - gu - he - hi - hr - hu - hy - id - is - it - ja - ka - kk - km - kn - ko - ku - ky - la - lb - lo - lt - lv - mg - mhr - mk - ml - mn - mr - ms - mt - my - nds - ne - nl - nn - 'no' - or - os - pa - pl - pnb - ps - pt - ro - ru - sa - sah - sd - sh - si - sk - sl - sq - sr - sv - sw - ta - te - tg - th - tk - tl - tr - tt - ug - uk - ur - uz - vi - yi - zh license: - cc0-1.0 multilinguality: - multilingual source_datasets: - oscar task_categories: - text-generation task_ids: - language-modeling paperswithcode_id: oscar pretty_name: OSCAR --- ## WARNING: this dataset is an extract of the OSCAR dataset published here to simulate the use of the full dataset in low-resource contexts. Using this dataset is equivalent to using a processed version of OSCAR legally speaking. I take no credit for the gathering of the original data and hence refer entirely to the original dataset in the card below. # Dataset Card for "oscar" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [https://oscar-corpus.com](https://oscar-corpus.com) - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Dataset Summary OSCAR or **O**pen **S**uper-large **C**rawled [**A**LMAnaCH](https://team.inria.fr/almanach/) co**R**pus is a huge multilingual corpus obtained by language classification and filtering of the [Common Crawl](https://commoncrawl.org/) corpus using the [goclassy](https://github.com/pjox/goclassy) architecture. Data is distributed by language in both original and deduplicated form. ### Supported Tasks and Leaderboards OSCAR is mainly inteded to pretrain language models and word represantations. ### Languages All the data is distributed by language, both the original and the deduplicated versions of the data are available. 166 different languages are available. The table in subsection [Data Splits Sample Size](#data-splits-sample-size) provides the language code for each subcorpus as well as the number of words (space separated tokens), lines and sizes for both the original and the deduplicated versions of OSCAR. ## Dataset Structure We show detailed information for all the configurations of the dataset. ## Dataset Creation ### Curation Rationale OSCAR was constructed new pipeline derived from the [fastText's one](https://github.com/facebookresearch/fastText), called [_goclassy_](https://github.com/pjox/goclassy). Goclassy reuses the [fastText linear classifier](https://fasttext.cc) and the pre-trained fastText model for language recognition, but it completely rewrites and parallelises their pipeline in an asynchronous manner. The order of operations is more or less the same as in the fastText pre-processing pipeline but instead of clustering multiple operations into a single blocking process, a worker is launched for each operation but bounding the number of possible parallel operations at a given time by the number of available threads instead of the number of CPUs. Goclassy is implemented in the [Go programming language](https://golang.org/) so it lets the [Go runtime](https://golang.org/src/runtime/mprof.go) handle the scheduling of the processes. Thus the goclassy's pipeline one does not have to wait for a whole WET file to download, decompress and classify in order to start downloading and processing the next one, a new file will start downloading and processing as soon as the scheduler is able to allocate a new process. Filtering and cleaning processes at line level are done before feeding each line to the classifier. Lines shorter than 100 UTF-8 characters and lines containing invalid UTF-8 characters are discarted and are not classified. After all files are proccesed the deduplicated versions are constructed and everything is then splitted in shards and compressed. ### Source Data #### Initial Data Collection and Normalization [Common Crawl](https://commoncrawl.org/) is a non-profit foundation which produces and maintains an open repository of web crawled data that is both accessible and analysable. Common Crawl's complete web archive consists of petabytes of data collected over 8 years of web crawling. The repository contains raw web page HTML data (WARC files), metdata extracts (WAT files) and plain text extracts (WET files). The organisation's crawlers has always respected [nofollow](http://microformats.org/wiki/rel-nofollow) and [robots.txt](https://www.robotstxt.org/) policies. Each monthly Common Crawl snapshot is in itself a massive multilingual corpus, where every single file contains data coming from multiple web pages written in a large variety of languages and covering all possible types of topics. To construct OSCAR the WET files of Common Crawl were used. These contain the extracted plain texts from the websites mostly converted to UTF-8, as well as headers containing the metatada of each crawled document. Each WET file comes compressed in gzip format and is stored on Amazon Web Services. In the case of OSCAR, the **November 2018** snapshot was used. It surpasses 20TB of uncompressed data and contains more than 50 thousand plain text files where each file consists of the plain text from multiple websites along its metadata header. #### Who are the source language producers? The data comes from multiple web pages in a large variety of languages. ### Annotations The dataset does not contain any additional annotations. #### Annotation process N/A #### Who are the annotators? N/A ### Personal and Sensitive Information Being constructed from Common Crawl, Personal and sensitive information might be present. This **must** be considered before training deep learning models with OSCAR, specially in the case of text-generation models. ## Considerations for Using the Data ### Social Impact of Dataset OSCAR is intended to bring more data to a wide variety of lanuages, the aim of the corpus is to make large amounts of data available to lower resource languages in order to facilitate the pre-training of state-of-the-art language modeling architectures. ### Discussion of Biases OSCAR is not properly filtered yet and this can be reflected on the models trained with it. Care is advised specially concerning biases of the resulting models. ### Other Known Limitations The [fastText linear classifier](https://fasttext.cc) is limed both in performance and the variety of languages it can recognize, so the quality of some OSCAR sub-corpora might be lower than expected, specially for the lowest-resource langiuages. Some audits have already been done by [third parties](https://arxiv.org/abs/2010.14571). ## Additional Information ### Dataset Curators The corpus was put together by [Pedro J. Ortiz](https://pjortiz.eu/), [Benoît Sagot](http://pauillac.inria.fr/~sagot/), and [Laurent Romary](https://cv.archives-ouvertes.fr/laurentromary), during work done at [Inria](https://www.inria.fr/en), particularly at the [ALMAnaCH team](https://team.inria.fr/almanach/). ### Licensing Information These data are released under this licensing scheme We do not own any of the text from which these data has been extracted. We license the actual packaging of these data under the Creative Commons CC0 license ("no rights reserved") http://creativecommons.org/publicdomain/zero/1.0/ To the extent possible under law, Inria has waived all copyright and related or neighboring rights to OSCAR This work is published from: France. Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: * Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. * Clearly identify the copyrighted work claimed to be infringed. * Clearly identify the material that is claimed to be infringing and information reasonably sufficient to allow us to locate the material. We will comply to legitimate requests by removing the affected sources from the next release of the corpus. ### Citation Information ``` @inproceedings{ortiz-suarez-etal-2020-monolingual, title = "A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages", author = "Ortiz Su{'a}rez, Pedro Javier and Romary, Laurent and Sagot, Benoit", booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics", month = jul, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.acl-main.156", pages = "1703--1714", abstract = "We use the multilingual OSCAR corpus, extracted from Common Crawl via language classification, filtering and cleaning, to train monolingual contextualized word embeddings (ELMo) for five mid-resource languages. We then compare the performance of OSCAR-based and Wikipedia-based ELMo embeddings for these languages on the part-of-speech tagging and parsing tasks. We show that, despite the noise in the Common-Crawl-based OSCAR data, embeddings trained on OSCAR perform much better than monolingual embeddings trained on Wikipedia. They actually equal or improve the current state of the art in tagging and parsing for all five languages. In particular, they also improve over multilingual Wikipedia-based contextual embeddings (multilingual BERT), which almost always constitutes the previous state of the art, thereby showing that the benefit of a larger, more diverse corpus surpasses the cross-lingual benefit of multilingual embedding architectures.", } @inproceedings{OrtizSuarezSagotRomary2019, author = {Pedro Javier {Ortiz Su{'a}rez} and Benoit Sagot and Laurent Romary}, title = {Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures}, series = {Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-7) 2019. Cardiff, 22nd July 2019}, editor = {Piotr Bański and Adrien Barbaresi and Hanno Biber and Evelyn Breiteneder and Simon Clematide and Marc Kupietz and Harald L{"u}ngen and Caroline Iliadi}, publisher = {Leibniz-Institut f{"u}r Deutsche Sprache}, address = {Mannheim}, doi = {10.14618/ids-pub-9021}, url = {http://nbn-resolving.de/urn:nbn:de:bsz:mh39-90215}, pages = {9 -- 16}, year = {2019}, abstract = {Common Crawl is a considerably large, heterogeneous multilingual corpus comprised of crawled documents from the internet, surpassing 20TB of data and distributed as a set of more than 50 thousand plain text files where each contains many documents written in a wide variety of languages. Even though each document has a metadata block associated to it, this data lacks any information about the language in which each document is written, making it extremely difficult to use Common Crawl for monolingual applications. We propose a general, highly parallel, multithreaded pipeline to clean and classify Common Crawl by language; we specifically design it so that it runs efficiently on medium to low resource infrastructures where I/O speeds are the main constraint. We develop the pipeline so that it can be easily reapplied to any kind of heterogeneous corpus and so that it can be parameterised to a wide range of infrastructures. We also distribute a 6.3TB version of Common Crawl, filtered, classified by language, shuffled at line level in order to avoid copyright issues, and ready to be used for NLP applications.}, language = {en} } ``` ### Contributions Thanks to [@pjox](https://github.com/pjox) and [@lhoestq](https://github.com/lhoestq) for adding this dataset.

Jiayi-Pan/Countdown-Tasks-3to4

Jiayi-Pan

--- dataset_info: features: - name: target dtype: int64 - name: nums sequence: int64 splits: - name: train num_bytes: 19650960 num_examples: 490364 download_size: 2845904 dataset_size: 19650960 configs: - config_name: default data_files: - split: train path: data/train-* ---

open-llm-leaderboard/contents

open-llm-leaderboard

--- dataset_info: features: - name: eval_name dtype: string - name: Precision dtype: string - name: Type dtype: string - name: T dtype: string - name: Weight type dtype: string - name: Architecture dtype: string - name: Model dtype: string - name: fullname dtype: string - name: Model sha dtype: string - name: Average ⬆️ dtype: float64 - name: Hub License dtype: string - name: Hub ❤️ dtype: int64 - name: '#Params (B)' dtype: float64 - name: Available on the hub dtype: bool - name: MoE dtype: bool - name: Flagged dtype: bool - name: Chat Template dtype: bool - name: CO₂ cost (kg) dtype: float64 - name: IFEval Raw dtype: float64 - name: IFEval dtype: float64 - name: BBH Raw dtype: float64 - name: BBH dtype: float64 - name: MATH Lvl 5 Raw dtype: float64 - name: MATH Lvl 5 dtype: float64 - name: GPQA Raw dtype: float64 - name: GPQA dtype: float64 - name: MUSR Raw dtype: float64 - name: MUSR dtype: float64 - name: MMLU-PRO Raw dtype: float64 - name: MMLU-PRO dtype: float64 - name: Merged dtype: bool - name: Official Providers dtype: bool - name: Upload To Hub Date dtype: string - name: Submission Date dtype: string - name: Generation dtype: int64 - name: Base Model dtype: string splits: - name: train num_bytes: 3423511 num_examples: 3913 download_size: 944370 dataset_size: 3423511 configs: - config_name: default data_files: - split: train path: data/train-* ---

Sterzhang/PVIT-3M

Sterzhang

--- configs: - config_name: PVIT-3M data_files: - split: all_data path: PVIT-3M.json language: - en task_categories: - visual-question-answering - image-text-to-text tags: - multi-modal - personalized license: apache-2.0 pretty_name: personalized visual instruction tuning size_categories: - 1M<n<10M --- # PVIT-3M The paper titled "[**Personalized Visual Instruction Tuning**](https://arxiv.org/abs/2410.07113)" introduces a novel dataset called PVIT-3M. This dataset is specifically designed for tuning MLLMs in the context of personalized visual instruction tasks. The dataset consists of 3 million image-text pairs that aim to improve MLLMs' abilities to generate responses based on personalized visual inputs, making them more tailored and adaptable to individual user needs and preferences. Here’s the PVIT-3M statistics: <img width="900" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/65d8b0f0661492b25c6623de/BLF2Uo72nqpvjPv_yplbt.png"> ## Directory The images in the PVIT-3M dataset have been organized into 40 separate folders, each named pvit-3m_0 to pvit-3m_39. After downloading, you can combine all the subfolders for a unified dataset structure. ``` Sterzhang/PVIT-3M └─ image └─ pvit-3m_0 └─ aug-face └─ coco └─ concat-person └─ crop-face └─ flickr30k └─ object365 └─ vg └─ pvit-3m_1 └─ ... └─ ... └─ PVIT-3M.json └─ README.md ``` ## Json Structure The PVIT-3M.json file contains structured data for each conversation instance in the PVIT-3M dataset. Below is an outline of the key fields: - `image`: A list of image file paths related to the conversation. - `conversations`: A list of dictionaries, each representing a turn in the conversation. - `from`: `human` or `gpt`. - `value`: The content of the conversation. - `type`: A string indicating the type. ## Example Here is an example from the PVIT-3M: ```json { "image": [ "crop-face/object365/objects365_v2_01169026/2.jpg", "object365/objects365_v2_01169026.jpg" ], "conversations": [ { "from": "human", "value": "<image>\nThis is a photo of Erin.\n<image>\nHow does Erin look in this photo?" }, { "from": "gpt", "value": "Erin is a woman with short, brown hair. She is wearing a dark blue dress with short sleeves and a ruffled design. She has a pearl necklace and a watch on her left wrist. She is also wearing a ring on her left hand." } ], "type": "crop description" } ``` "crop-face/object365/objects365_v2_01169026/2.jpg": <img width="100" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/65d8b0f0661492b25c6623de/lJi0aDYE44wyGP2QMZ13W.png"> "object365/objects365_v2_01169026.jpg": <img width="400" alt="image" src="https://cdn-uploads.huggingface.co/production/uploads/65d8b0f0661492b25c6623de/RY_80A5rSOO1vv6A6CuJy.png"> ## Script The script processes conversation data in the **PVIT-3M** dataset by adding personalized wrapper tokens (`<person_s>` and `<person_e>`) around specific segments. This helps the model correctly associate personalized text and images with each individual, reducing ambiguity in multimodal training. ```python import json def process_image_description(text): segments = text.split('<image>\n') processed_segments = [] for i, segment in enumerate(segments): if i == 0: processed_segments.append(segment) elif i == len(segments) - 1: continue else: last_newline_index = segment.rfind('\n') if last_newline_index != -1: segment = segment[:last_newline_index] + '<person_e>' + segment[last_newline_index:] else: segment += '<person_e>' processed_segments.append(f'<person_s><image>\n{segment}') processed_segments.append(f"<image>\n{segments[-1]}") return ''.join(processed_segments) def process_conversation_data(input_path, output_path): with open(input_path, 'r', encoding='utf-8') as f: data = json.load(f) for item in data: conversation_value = item["conversations"][0]["value"] item["conversations"][0]["value"] = process_image_description(conversation_value) with open(output_path, 'w', encoding='utf-8') as f: json.dump(data, f, ensure_ascii=False, indent=4) input_file = "" output_file = "" process_conversation_data(input_file, output_file) ``` # Code Our code will be released in [PVIT](https://github.com/sterzhang/PVIT), containing scripts for generating PVIT dataset as well as our code for training. # Case Study <img width="1000" alt="image" src="https://github.com/user-attachments/assets/d50fa03f-fdb6-41ff-ab25-806578d29f3e"> # Citation Our paper is now available at: [https://arxiv.org/abs/2410.07113](https://arxiv.org/abs/2410.07113) ```bibtex @misc{pi2024personalizedvisualinstructiontuning, title={Personalized Visual Instruction Tuning}, author={Renjie Pi and Jianshu Zhang and Tianyang Han and Jipeng Zhang and Rui Pan and Tong Zhang}, year={2024}, eprint={2410.07113}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2410.07113}, }

asahi417/seamless-align-enA-frA.speaker-embedding.w2vbert-600m

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9566368832 num_examples: 2343 download_size: 9594006755 dataset_size: 9566368832 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9055495714 num_examples: 2334 download_size: 9082072956 dataset_size: 9055495714 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8344151850 num_examples: 2309 download_size: 8368301727 dataset_size: 8344151850 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8292800434 num_examples: 2322 download_size: 8317633830 dataset_size: 8292800434 - config_name: subset_102 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8224967519 num_examples: 2291 download_size: 8249842240 dataset_size: 8224967519 - config_name: subset_103 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8339581413 num_examples: 2321 download_size: 8364550280 dataset_size: 8339581413 - config_name: subset_104 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8239856479 num_examples: 2314 download_size: 8264731163 dataset_size: 8239856479 - config_name: subset_105 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8325030279 num_examples: 2318 download_size: 8349920886 dataset_size: 8325030279 - config_name: subset_106 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8294529988 num_examples: 2314 download_size: 8319483916 dataset_size: 8294529988 - config_name: subset_107 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8451145911 num_examples: 2314 download_size: 8476011221 dataset_size: 8451145911 - config_name: subset_108 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8317793444 num_examples: 2315 download_size: 8342027520 dataset_size: 8317793444 - config_name: subset_109 features: - 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split: train path: subset_285/train-* - config_name: subset_286 data_files: - split: train path: subset_286/train-* - config_name: subset_287 data_files: - split: train path: subset_287/train-* - config_name: subset_288 data_files: - split: train path: subset_288/train-* - config_name: subset_289 data_files: - split: train path: subset_289/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_290 data_files: - split: train path: subset_290/train-* - config_name: subset_291 data_files: - split: train path: subset_291/train-* - config_name: subset_292 data_files: - split: train path: subset_292/train-* - config_name: subset_293 data_files: - split: train path: subset_293/train-* - config_name: subset_294 data_files: - split: train path: subset_294/train-* - config_name: subset_295 data_files: - split: train path: subset_295/train-* - config_name: subset_296 data_files: - split: train path: subset_296/train-* - config_name: subset_297 data_files: - split: train path: subset_297/train-* - config_name: subset_298 data_files: - split: train path: subset_298/train-* - config_name: subset_299 data_files: - split: train path: subset_299/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_300 data_files: - split: train path: subset_300/train-* - config_name: subset_301 data_files: - split: train path: subset_301/train-* - config_name: subset_302 data_files: - split: train path: subset_302/train-* - config_name: subset_303 data_files: - split: train path: subset_303/train-* - config_name: subset_304 data_files: - split: train path: subset_304/train-* - config_name: subset_305 data_files: - split: train path: subset_305/train-* - config_name: subset_306 data_files: - split: train path: subset_306/train-* - config_name: subset_307 data_files: - split: train path: subset_307/train-* - config_name: subset_308 data_files: - split: train path: subset_308/train-* - config_name: subset_309 data_files: - split: train path: subset_309/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_310 data_files: - split: train path: subset_310/train-* - config_name: subset_311 data_files: - split: train path: subset_311/train-* - config_name: subset_312 data_files: - split: train path: subset_312/train-* - config_name: subset_313 data_files: - split: train path: subset_313/train-* - config_name: subset_314 data_files: - split: train path: subset_314/train-* - config_name: subset_315 data_files: - split: train path: subset_315/train-* - config_name: subset_316 data_files: - split: train path: subset_316/train-* - config_name: subset_317 data_files: - split: train path: subset_317/train-* - config_name: subset_318 data_files: - split: train path: subset_318/train-* - config_name: subset_319 data_files: - split: train path: subset_319/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_320 data_files: - split: train path: subset_320/train-* - config_name: subset_321 data_files: - split: train path: subset_321/train-* - config_name: subset_322 data_files: - split: train path: subset_322/train-* - config_name: subset_323 data_files: - split: train path: subset_323/train-* - config_name: subset_324 data_files: - split: train path: subset_324/train-* - config_name: subset_325 data_files: - split: train path: subset_325/train-* - config_name: subset_326 data_files: - split: train path: subset_326/train-* - config_name: subset_327 data_files: - split: train path: subset_327/train-* - config_name: subset_328 data_files: - split: train path: subset_328/train-* - config_name: subset_329 data_files: - split: train path: subset_329/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_330 data_files: - split: train path: subset_330/train-* - config_name: subset_331 data_files: - split: train path: subset_331/train-* - config_name: subset_332 data_files: - split: train path: subset_332/train-* - config_name: subset_333 data_files: - split: train path: subset_333/train-* - config_name: subset_334 data_files: - split: train path: subset_334/train-* - config_name: subset_335 data_files: - split: train path: subset_335/train-* - config_name: subset_336 data_files: - split: train path: subset_336/train-* - config_name: subset_337 data_files: - split: train path: subset_337/train-* - config_name: subset_338 data_files: - split: train path: subset_338/train-* - config_name: subset_339 data_files: - split: train path: subset_339/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_340 data_files: - split: train path: subset_340/train-* - config_name: subset_341 data_files: - split: train path: subset_341/train-* - config_name: subset_342 data_files: - split: train path: subset_342/train-* - config_name: subset_343 data_files: - 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split: train path: subset_367/train-* - config_name: subset_368 data_files: - split: train path: subset_368/train-* - config_name: subset_369 data_files: - split: train path: subset_369/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_370 data_files: - split: train path: subset_370/train-* - config_name: subset_371 data_files: - split: train path: subset_371/train-* - config_name: subset_372 data_files: - split: train path: subset_372/train-* - config_name: subset_373 data_files: - split: train path: subset_373/train-* - config_name: subset_374 data_files: - split: train path: subset_374/train-* - config_name: subset_375 data_files: - split: train path: subset_375/train-* - config_name: subset_376 data_files: - split: train path: subset_376/train-* - config_name: subset_377 data_files: - split: train path: subset_377/train-* - config_name: subset_378 data_files: - split: train path: subset_378/train-* - config_name: subset_379 data_files: - split: train path: subset_379/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_380 data_files: - split: train path: subset_380/train-* - config_name: subset_381 data_files: - split: train path: subset_381/train-* - config_name: subset_382 data_files: - split: train path: subset_382/train-* - config_name: subset_383 data_files: - split: train path: subset_383/train-* - config_name: subset_384 data_files: - split: train path: subset_384/train-* - config_name: subset_385 data_files: - split: train path: subset_385/train-* - config_name: subset_386 data_files: - split: train path: subset_386/train-* - config_name: subset_387 data_files: - split: train path: subset_387/train-* - config_name: subset_388 data_files: - split: train path: subset_388/train-* - config_name: subset_389 data_files: - split: train path: subset_389/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_390 data_files: - split: train path: subset_390/train-* - config_name: subset_391 data_files: - split: train path: subset_391/train-* - config_name: subset_392 data_files: - split: train path: subset_392/train-* - config_name: subset_393 data_files: - split: train path: subset_393/train-* - config_name: subset_394 data_files: - split: train path: subset_394/train-* - config_name: subset_395 data_files: - split: train path: subset_395/train-* - config_name: subset_396 data_files: - split: train path: subset_396/train-* - config_name: subset_397 data_files: - split: train path: subset_397/train-* - config_name: subset_398 data_files: - split: train path: subset_398/train-* - config_name: subset_399 data_files: - split: train path: subset_399/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_400 data_files: - split: train path: subset_400/train-* - config_name: subset_401 data_files: - split: train path: subset_401/train-* - config_name: subset_402 data_files: - split: train path: subset_402/train-* - config_name: subset_403 data_files: - split: train path: subset_403/train-* - config_name: subset_404 data_files: - split: train path: subset_404/train-* - config_name: subset_405 data_files: - split: train path: subset_405/train-* - config_name: subset_406 data_files: - split: train path: subset_406/train-* - config_name: subset_407 data_files: - split: train path: subset_407/train-* - config_name: subset_408 data_files: - split: train path: subset_408/train-* - config_name: subset_409 data_files: - split: train path: subset_409/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_410 data_files: - split: train path: subset_410/train-* - config_name: subset_411 data_files: - split: train path: subset_411/train-* - config_name: subset_412 data_files: - split: train path: subset_412/train-* - config_name: subset_413 data_files: - split: train path: subset_413/train-* - config_name: subset_414 data_files: - split: train path: subset_414/train-* - config_name: subset_415 data_files: - split: train path: subset_415/train-* - config_name: subset_416 data_files: - split: train path: subset_416/train-* - config_name: subset_417 data_files: - split: train path: subset_417/train-* - config_name: subset_418 data_files: - split: train path: subset_418/train-* - config_name: subset_419 data_files: - split: train path: subset_419/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_420 data_files: - split: train path: subset_420/train-* - config_name: subset_421 data_files: - split: train path: subset_421/train-* - config_name: subset_422 data_files: - split: train path: subset_422/train-* - config_name: subset_423 data_files: - split: train path: subset_423/train-* - config_name: subset_424 data_files: - split: train path: subset_424/train-* - config_name: subset_425 data_files: - split: train path: subset_425/train-* - config_name: subset_426 data_files: - split: train path: subset_426/train-* - config_name: subset_427 data_files: - split: train path: subset_427/train-* - config_name: subset_428 data_files: - split: train path: subset_428/train-* - config_name: subset_429 data_files: - split: train path: subset_429/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_430 data_files: - split: train path: subset_430/train-* - config_name: subset_431 data_files: - split: train path: subset_431/train-* - config_name: subset_432 data_files: - split: train path: subset_432/train-* - config_name: subset_433 data_files: - split: train path: subset_433/train-* - config_name: subset_434 data_files: - split: train path: subset_434/train-* - config_name: subset_435 data_files: - split: train path: subset_435/train-* - config_name: subset_436 data_files: - split: train path: subset_436/train-* - config_name: subset_437 data_files: - 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split: train path: subset_449/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_450 data_files: - split: train path: subset_450/train-* - config_name: subset_451 data_files: - split: train path: subset_451/train-* - config_name: subset_452 data_files: - split: train path: subset_452/train-* - config_name: subset_453 data_files: - split: train path: subset_453/train-* - config_name: subset_454 data_files: - split: train path: subset_454/train-* - config_name: subset_455 data_files: - split: train path: subset_455/train-* - config_name: subset_456 data_files: - split: train path: subset_456/train-* - config_name: subset_457 data_files: - split: train path: subset_457/train-* - config_name: subset_458 data_files: - split: train path: subset_458/train-* - config_name: subset_459 data_files: - split: train path: subset_459/train-* - config_name: subset_46 data_files: - split: train path: subset_46/train-* - config_name: subset_460 data_files: - split: train path: subset_460/train-* - config_name: subset_461 data_files: - split: train path: subset_461/train-* - config_name: subset_462 data_files: - split: train path: subset_462/train-* - config_name: subset_463 data_files: - split: train path: subset_463/train-* - config_name: subset_464 data_files: - split: train path: subset_464/train-* - config_name: subset_465 data_files: - split: train path: subset_465/train-* - config_name: subset_466 data_files: - split: train path: subset_466/train-* - config_name: subset_467 data_files: - split: train path: subset_467/train-* - config_name: subset_468 data_files: - split: train path: subset_468/train-* - config_name: subset_469 data_files: - split: train path: subset_469/train-* - config_name: subset_47 data_files: - split: train path: subset_47/train-* - config_name: subset_470 data_files: - split: train path: subset_470/train-* - config_name: subset_471 data_files: - split: train path: subset_471/train-* - config_name: subset_472 data_files: - split: train path: subset_472/train-* - config_name: subset_473 data_files: - split: train path: subset_473/train-* - config_name: subset_474 data_files: - split: train path: subset_474/train-* - config_name: subset_475 data_files: - split: train path: subset_475/train-* - config_name: subset_476 data_files: - split: train path: subset_476/train-* - config_name: subset_477 data_files: - split: train path: subset_477/train-* - config_name: subset_478 data_files: - split: train path: subset_478/train-* - config_name: subset_479 data_files: - split: train path: subset_479/train-* - config_name: subset_48 data_files: - split: train path: subset_48/train-* - config_name: subset_480 data_files: - split: train path: subset_480/train-* - config_name: subset_481 data_files: - split: train path: subset_481/train-* - config_name: subset_482 data_files: - split: train path: subset_482/train-* - config_name: subset_483 data_files: - split: train path: subset_483/train-* - config_name: subset_484 data_files: - split: train path: subset_484/train-* - config_name: subset_485 data_files: - split: train path: subset_485/train-* - config_name: subset_486 data_files: - split: train path: subset_486/train-* - config_name: subset_487 data_files: - split: train path: subset_487/train-* - config_name: subset_488 data_files: - split: train path: subset_488/train-* - config_name: subset_489 data_files: - split: train path: subset_489/train-* - config_name: subset_49 data_files: - split: train path: subset_49/train-* - config_name: subset_490 data_files: - split: train path: subset_490/train-* - config_name: subset_491 data_files: - split: train path: subset_491/train-* - config_name: subset_492 data_files: - split: train path: subset_492/train-* - config_name: subset_493 data_files: - split: train path: subset_493/train-* - config_name: subset_494 data_files: - split: train path: subset_494/train-* - config_name: subset_495 data_files: - split: train path: subset_495/train-* - config_name: subset_496 data_files: - split: train path: subset_496/train-* - config_name: subset_497 data_files: - split: train path: subset_497/train-* - config_name: subset_498 data_files: - split: train path: subset_498/train-* - config_name: subset_499 data_files: - split: train path: subset_499/train-* - config_name: subset_5 data_files: - split: train path: subset_5/train-* - config_name: subset_50 data_files: - split: train path: subset_50/train-* - config_name: subset_500 data_files: - split: train path: subset_500/train-* - config_name: subset_501 data_files: - split: train path: subset_501/train-* - config_name: subset_502 data_files: - split: train path: subset_502/train-* - config_name: subset_503 data_files: - split: train path: subset_503/train-* - config_name: subset_504 data_files: - split: train path: subset_504/train-* - config_name: subset_505 data_files: - split: train path: subset_505/train-* - config_name: subset_506 data_files: - split: train path: subset_506/train-* - config_name: subset_507 data_files: - split: train path: subset_507/train-* - config_name: subset_508 data_files: - split: train path: subset_508/train-* - config_name: subset_509 data_files: - split: train path: subset_509/train-* - config_name: subset_51 data_files: - split: train path: subset_51/train-* - config_name: subset_510 data_files: - split: train path: subset_510/train-* - config_name: subset_511 data_files: - split: train path: subset_511/train-* - config_name: subset_512 data_files: - split: train path: subset_512/train-* - config_name: subset_513 data_files: - split: train path: subset_513/train-* - config_name: subset_514 data_files: - split: train path: subset_514/train-* - config_name: subset_515 data_files: - split: train path: subset_515/train-* - config_name: subset_516 data_files: - split: train path: subset_516/train-* - config_name: subset_517 data_files: - split: train path: subset_517/train-* - config_name: subset_518 data_files: - split: train path: subset_518/train-* - config_name: subset_519 data_files: - split: train path: subset_519/train-* - config_name: subset_52 data_files: - split: train path: subset_52/train-* - config_name: subset_520 data_files: - split: train path: subset_520/train-* - config_name: subset_521 data_files: - split: train path: subset_521/train-* - config_name: subset_522 data_files: - split: train path: subset_522/train-* - config_name: subset_523 data_files: - split: train path: subset_523/train-* - config_name: subset_524 data_files: - split: train path: subset_524/train-* - config_name: subset_525 data_files: - split: train path: subset_525/train-* - config_name: subset_526 data_files: - split: train path: subset_526/train-* - config_name: subset_527 data_files: - split: train path: subset_527/train-* - config_name: subset_528 data_files: - split: train path: subset_528/train-* - config_name: subset_529 data_files: - split: train path: subset_529/train-* - config_name: subset_53 data_files: - split: train path: subset_53/train-* - config_name: subset_530 data_files: - split: train path: subset_530/train-* - config_name: subset_531 data_files: - split: train path: subset_531/train-* - config_name: subset_532 data_files: - split: train path: subset_532/train-* - config_name: subset_533 data_files: - split: train path: subset_533/train-* - config_name: subset_534 data_files: - split: train path: subset_534/train-* - config_name: subset_535 data_files: - split: train path: subset_535/train-* - config_name: subset_536 data_files: - split: train path: subset_536/train-* - config_name: subset_537 data_files: - split: train path: subset_537/train-* - config_name: subset_538 data_files: - split: train path: subset_538/train-* - config_name: subset_539 data_files: - split: train path: subset_539/train-* - config_name: subset_54 data_files: - split: train path: subset_54/train-* - config_name: subset_540 data_files: - split: train path: subset_540/train-* - config_name: subset_541 data_files: - split: train path: subset_541/train-* - config_name: subset_542 data_files: - split: train path: subset_542/train-* - config_name: subset_543 data_files: - split: train path: subset_543/train-* - config_name: subset_544 data_files: - split: train path: subset_544/train-* - config_name: subset_545 data_files: - split: train path: subset_545/train-* - config_name: subset_546 data_files: - split: train path: subset_546/train-* - config_name: subset_547 data_files: - split: train path: subset_547/train-* - config_name: subset_548 data_files: - split: train path: subset_548/train-* - config_name: subset_549 data_files: - split: train path: subset_549/train-* - config_name: subset_55 data_files: - split: train path: subset_55/train-* - config_name: subset_550 data_files: - split: train path: subset_550/train-* - config_name: subset_551 data_files: - split: train path: subset_551/train-* - config_name: subset_552 data_files: - split: train path: subset_552/train-* - config_name: subset_553 data_files: - split: train path: subset_553/train-* - config_name: subset_554 data_files: - split: train path: subset_554/train-* - config_name: subset_555 data_files: - split: train path: subset_555/train-* - config_name: subset_556 data_files: - split: train path: subset_556/train-* - config_name: subset_557 data_files: - split: train path: subset_557/train-* - config_name: subset_558 data_files: - split: train path: subset_558/train-* - config_name: subset_559 data_files: - split: train path: subset_559/train-* - config_name: subset_56 data_files: - split: train path: subset_56/train-* - config_name: subset_560 data_files: - split: train path: subset_560/train-* - config_name: subset_561 data_files: - split: train path: subset_561/train-* - config_name: subset_562 data_files: - split: train path: subset_562/train-* - config_name: subset_563 data_files: - split: train path: subset_563/train-* - config_name: subset_564 data_files: - split: train path: subset_564/train-* - config_name: subset_565 data_files: - split: train path: subset_565/train-* - config_name: subset_566 data_files: - split: train path: subset_566/train-* - config_name: subset_567 data_files: - split: train path: subset_567/train-* - config_name: subset_568 data_files: - split: train path: subset_568/train-* - config_name: subset_569 data_files: - split: train path: subset_569/train-* - config_name: subset_57 data_files: - split: train path: subset_57/train-* - config_name: subset_570 data_files: - split: train path: subset_570/train-* - config_name: subset_571 data_files: - split: train path: subset_571/train-* - config_name: subset_572 data_files: - split: train path: subset_572/train-* - config_name: subset_573 data_files: - split: train path: subset_573/train-* - config_name: subset_574 data_files: - split: train path: subset_574/train-* - config_name: subset_575 data_files: - split: train path: subset_575/train-* - config_name: subset_576 data_files: - split: train path: subset_576/train-* - config_name: subset_577 data_files: - split: train path: subset_577/train-* - config_name: subset_578 data_files: - split: train path: subset_578/train-* - config_name: subset_579 data_files: - split: train path: subset_579/train-* - config_name: subset_58 data_files: - split: train path: subset_58/train-* - config_name: subset_580 data_files: - split: train path: subset_580/train-* - config_name: subset_581 data_files: - split: train path: subset_581/train-* - config_name: subset_582 data_files: - split: train path: subset_582/train-* - config_name: subset_583 data_files: - split: train path: subset_583/train-* - config_name: subset_584 data_files: - split: train path: subset_584/train-* - config_name: subset_585 data_files: - split: train path: subset_585/train-* - config_name: subset_586 data_files: - split: train path: subset_586/train-* - config_name: subset_587 data_files: - split: train path: subset_587/train-* - config_name: subset_588 data_files: - split: train path: subset_588/train-* - config_name: subset_589 data_files: - split: train path: subset_589/train-* - config_name: subset_59 data_files: - split: train path: subset_59/train-* - config_name: subset_590 data_files: - split: train path: subset_590/train-* - config_name: subset_591 data_files: - split: train path: subset_591/train-* - config_name: subset_592 data_files: - split: train path: subset_592/train-* - config_name: subset_593 data_files: - split: train path: subset_593/train-* - config_name: subset_594 data_files: - split: train path: subset_594/train-* - config_name: subset_595 data_files: - split: train path: subset_595/train-* - config_name: subset_596 data_files: - split: train path: subset_596/train-* - config_name: subset_597 data_files: - split: train path: subset_597/train-* - config_name: subset_598 data_files: - split: train path: subset_598/train-* - config_name: subset_599 data_files: - split: train path: subset_599/train-* - config_name: subset_6 data_files: - split: train path: subset_6/train-* - config_name: subset_60 data_files: - split: train path: subset_60/train-* - config_name: subset_600 data_files: - split: train path: subset_600/train-* - config_name: subset_61 data_files: - split: train path: subset_61/train-* - config_name: subset_62 data_files: - split: train path: subset_62/train-* - config_name: subset_63 data_files: - split: train path: subset_63/train-* - config_name: subset_64 data_files: - split: train path: subset_64/train-* - config_name: subset_65 data_files: - split: train path: subset_65/train-* - config_name: subset_66 data_files: - split: train path: subset_66/train-* - config_name: subset_67 data_files: - split: train path: subset_67/train-* - config_name: subset_68 data_files: - split: train path: subset_68/train-* - config_name: subset_69 data_files: - split: train path: subset_69/train-* - config_name: subset_7 data_files: - split: train path: subset_7/train-* - config_name: subset_70 data_files: - split: train path: subset_70/train-* - config_name: subset_71 data_files: - split: train path: subset_71/train-* - config_name: subset_72 data_files: - split: train path: subset_72/train-* - config_name: subset_73 data_files: - split: train path: subset_73/train-* - config_name: subset_74 data_files: - split: train path: subset_74/train-* - config_name: subset_75 data_files: - split: train path: subset_75/train-* - config_name: subset_76 data_files: - split: train path: subset_76/train-* - config_name: subset_77 data_files: - split: train path: subset_77/train-* - config_name: subset_78 data_files: - split: train path: subset_78/train-* - config_name: subset_79 data_files: - split: train path: subset_79/train-* - config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

claran/modular-s2orc-parquet

claran

--- license: odc-by dataset_info: - config_name: AgriculturalAndFoodSciences,1970-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 998442024 num_examples: 43346 - name: validation num_bytes: 2366417 num_examples: 106 - name: test num_bytes: 1910823 num_examples: 90 download_size: 504900073 dataset_size: 1002719264 - config_name: AgriculturalAndFoodSciences,2016-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1222592193 num_examples: 51765 - name: validation num_bytes: 4196305 num_examples: 165 - name: test num_bytes: 3271988 num_examples: 142 download_size: 606094130 dataset_size: 1230060486 - config_name: AgriculturalAndFoodSciences,2019-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2074304072 num_examples: 88385 - name: validation num_bytes: 5434770 num_examples: 230 - name: test num_bytes: 6541157 num_examples: 268 download_size: 1013180112 dataset_size: 2086279999 - config_name: AgriculturalAndFoodSciences,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1449111953 num_examples: 56755 - name: validation num_bytes: 4426655 num_examples: 153 - name: test num_bytes: 4185827 num_examples: 155 download_size: 706778721 dataset_size: 1457724435 - config_name: AgriculturalAndFoodSciences,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1006818544 num_examples: 32383 - name: validation num_bytes: 3475364 num_examples: 107 - name: test num_bytes: 3682828 num_examples: 118 download_size: 481809232 dataset_size: 1013976736 - config_name: Art,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 925031695 num_examples: 29369 - name: validation num_bytes: 2549649 num_examples: 83 - name: test num_bytes: 2742333 num_examples: 84 download_size: 512862602 dataset_size: 930323677 - config_name: Biology,1970-1993 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 888869120 num_examples: 34380 - name: validation num_bytes: 2170051 num_examples: 92 - name: test num_bytes: 3082360 num_examples: 116 download_size: 443978192 dataset_size: 894121531 - config_name: Biology,1994-1999 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 952297366 num_examples: 30613 - name: validation num_bytes: 2490479 num_examples: 79 - name: test num_bytes: 2264442 num_examples: 74 download_size: 470909458 dataset_size: 957052287 - config_name: Biology,2000-2003 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 981884207 num_examples: 31667 - name: validation num_bytes: 2323340 num_examples: 71 - name: test num_bytes: 2214573 num_examples: 69 download_size: 487600872 dataset_size: 986422120 - config_name: Biology,2004-2006 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1055117449 num_examples: 34717 - name: validation num_bytes: 2682802 num_examples: 90 - name: test num_bytes: 3726308 num_examples: 117 download_size: 529888848 dataset_size: 1061526559 - config_name: Biology,2007-2008 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1065365863 num_examples: 33939 - name: validation num_bytes: 3031246 num_examples: 106 - name: test num_bytes: 2907391 num_examples: 90 download_size: 537491034 dataset_size: 1071304500 - config_name: Biology,2009-2010 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1746004053 num_examples: 56633 - name: validation num_bytes: 4947420 num_examples: 161 - name: test num_bytes: 4880643 num_examples: 152 download_size: 886110144 dataset_size: 1755832116 - config_name: Biology,2011-2011 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1293777221 num_examples: 42178 - name: validation num_bytes: 3488838 num_examples: 114 - name: test num_bytes: 3114555 num_examples: 108 download_size: 657383479 dataset_size: 1300380614 - config_name: Biology,2012-2012 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1675263820 num_examples: 54682 - name: validation num_bytes: 3744956 num_examples: 124 - name: test num_bytes: 4584586 num_examples: 144 download_size: 852519673 dataset_size: 1683593362 - config_name: Biology,2013-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1954725426 num_examples: 64830 - name: validation num_bytes: 5625811 num_examples: 178 - name: test num_bytes: 5324123 num_examples: 194 download_size: 995767109 dataset_size: 1965675360 - config_name: Biology,2014-2014 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2185064712 num_examples: 72827 - name: validation num_bytes: 6182821 num_examples: 218 - name: test num_bytes: 5419942 num_examples: 181 download_size: 1113739580 dataset_size: 2196667475 - config_name: Biology,2015-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2352712258 num_examples: 79102 - name: validation num_bytes: 5930241 num_examples: 197 - name: test num_bytes: 6326102 num_examples: 221 download_size: 1197159680 dataset_size: 2364968601 - config_name: Biology,2016-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2553806533 num_examples: 85961 - name: validation num_bytes: 6807323 num_examples: 229 - name: test num_bytes: 6339865 num_examples: 216 download_size: 1291271066 dataset_size: 2566953721 - config_name: Biology,2017-2017 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2933160329 num_examples: 98250 - name: validation num_bytes: 8120173 num_examples: 272 - name: test num_bytes: 7560161 num_examples: 262 download_size: 1479304975 dataset_size: 2948840663 - config_name: Biology,2018-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 3093985356 num_examples: 101178 - name: validation num_bytes: 8992072 num_examples: 291 - name: test num_bytes: 8934258 num_examples: 296 download_size: 673029925 dataset_size: 3111911686 - config_name: Biology,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 3403107639 num_examples: 110354 - name: validation num_bytes: 10053465 num_examples: 322 - name: test num_bytes: 9889726 num_examples: 309 download_size: 1705817756 dataset_size: 3423050830 - config_name: Biology,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 4668003659 num_examples: 149329 - name: validation num_bytes: 12745266 num_examples: 423 - name: test num_bytes: 14492208 num_examples: 459 download_size: 2339737377 dataset_size: 4695241133 - config_name: Biology,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 5455165147 num_examples: 164651 - name: validation num_bytes: 15909996 num_examples: 484 - name: test num_bytes: 16773260 num_examples: 500 download_size: 2735380664 dataset_size: 5487848403 - config_name: Biology,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - 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name: test num_bytes: 2183784 num_examples: 82 download_size: 470346532 dataset_size: 950272692 - config_name: Business,2018-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 912151313 num_examples: 32818 - name: validation num_bytes: 2771875 num_examples: 94 - name: test num_bytes: 2756245 num_examples: 94 download_size: 444897266 dataset_size: 917679433 - config_name: Business,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1185735674 num_examples: 39443 - name: validation num_bytes: 3457871 num_examples: 111 - name: test num_bytes: 3417615 num_examples: 107 download_size: 576236826 dataset_size: 1192611160 - config_name: Business,2021-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1972500703 num_examples: 59680 - name: validation num_bytes: 6799710 num_examples: 188 - name: test num_bytes: 6327836 num_examples: 192 download_size: 958714880 dataset_size: 1985628249 - config_name: Chemistry,1970-2014 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 818454073 num_examples: 40722 - name: validation num_bytes: 2485832 num_examples: 124 - name: test num_bytes: 2287304 num_examples: 108 download_size: 418727288 dataset_size: 823227209 - config_name: Chemistry,2015-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 995430262 num_examples: 42807 - name: validation num_bytes: 2837006 num_examples: 120 - name: test num_bytes: 3114786 num_examples: 129 download_size: 488526891 dataset_size: 1001382054 - config_name: Chemistry,2019-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1012644735 num_examples: 40396 - name: validation num_bytes: 2512817 num_examples: 93 - name: test num_bytes: 2508547 num_examples: 96 download_size: 484528399 dataset_size: 1017666099 - config_name: Chemistry,2021-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1222717233 num_examples: 42413 - name: validation num_bytes: 4114879 num_examples: 137 - name: test num_bytes: 3133434 num_examples: 106 download_size: 582171929 dataset_size: 1229965546 - config_name: ComputerScience,1970-2008 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 889392884 num_examples: 33431 - name: validation num_bytes: 2141031 num_examples: 91 - name: test num_bytes: 2167507 num_examples: 86 download_size: 452156131 dataset_size: 893701422 - config_name: ComputerScience,2009-2011 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 867281031 num_examples: 28912 - name: validation num_bytes: 2044173 num_examples: 63 - name: test num_bytes: 1654441 num_examples: 61 download_size: 434687368 dataset_size: 870979645 - config_name: ComputerScience,2012-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 949604761 num_examples: 31467 - name: validation num_bytes: 2218627 num_examples: 79 - name: test num_bytes: 2409454 num_examples: 75 download_size: 476058620 dataset_size: 954232842 - config_name: ComputerScience,2014-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1325207987 num_examples: 43232 - name: validation num_bytes: 4027599 num_examples: 121 - name: test num_bytes: 3024457 num_examples: 106 download_size: 663240721 dataset_size: 1332260043 - config_name: ComputerScience,2016-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 885721996 num_examples: 28402 - name: validation num_bytes: 1961663 num_examples: 50 - name: test num_bytes: 2335512 num_examples: 71 download_size: 440587199 dataset_size: 890019171 - config_name: ComputerScience,2017-2017 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1085420885 num_examples: 35290 - name: validation num_bytes: 3036041 num_examples: 101 - name: test num_bytes: 2803898 num_examples: 77 download_size: 540311199 dataset_size: 1091260824 - config_name: ComputerScience,2018-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1485669170 num_examples: 48321 - name: validation num_bytes: 4507358 num_examples: 131 - name: test num_bytes: 3798344 num_examples: 133 download_size: 4126375 dataset_size: 1493974872 - config_name: ComputerScience,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1870072707 num_examples: 61617 - name: validation num_bytes: 4853818 num_examples: 166 - name: test num_bytes: 5514604 num_examples: 185 download_size: 924785698 dataset_size: 1880441129 - config_name: ComputerScience,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 3552101836 num_examples: 110259 - name: validation num_bytes: 9626264 num_examples: 301 - name: test num_bytes: 10544621 num_examples: 317 download_size: 1757235886 dataset_size: 3572272721 - config_name: ComputerScience,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 4582839113 num_examples: 136470 - name: validation num_bytes: 11409640 num_examples: 344 - name: test num_bytes: 12223638 num_examples: 354 download_size: 2269512635 dataset_size: 4606472391 - config_name: ComputerScience,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 4004246776 num_examples: 110170 - name: validation num_bytes: 11587308 num_examples: 304 - name: test num_bytes: 11727271 num_examples: 326 download_size: 1979954172 dataset_size: 4027561355 - config_name: Economics,1970-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 959346661 num_examples: 27851 - name: validation num_bytes: 2254555 num_examples: 70 - name: test num_bytes: 2144217 num_examples: 60 download_size: 486684561 dataset_size: 963745433 - config_name: Economics,2017-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - 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config_name: Economics,2021-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1705879165 num_examples: 48421 - name: validation num_bytes: 4852604 num_examples: 140 - name: test num_bytes: 4857638 num_examples: 137 download_size: 841917279 dataset_size: 1715589407 - config_name: Education,1970-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1201419492 num_examples: 44679 - name: validation num_bytes: 3266840 num_examples: 132 - name: test num_bytes: 2946567 num_examples: 108 download_size: 607172003 dataset_size: 1207632899 - config_name: Education,2019-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - 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name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1367524169 num_examples: 52607 - name: validation num_bytes: 4347869 num_examples: 166 - name: test num_bytes: 3460260 num_examples: 137 download_size: 620929938 dataset_size: 1375332298 - config_name: Engineering,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1457434608 num_examples: 53806 - name: validation num_bytes: 4955759 num_examples: 169 - name: test num_bytes: 4686725 num_examples: 172 download_size: 669719414 dataset_size: 1467077092 - config_name: Engineering,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 855739822 num_examples: 25494 - name: validation num_bytes: 2234029 num_examples: 68 - name: test num_bytes: 2249580 num_examples: 64 download_size: 384898749 dataset_size: 860223431 - config_name: EnvironmentalScience,1970-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1055164036 num_examples: 34552 - name: validation num_bytes: 2754850 num_examples: 88 - name: test num_bytes: 2289086 num_examples: 80 download_size: 539948007 dataset_size: 1060207972 - config_name: EnvironmentalScience,2014-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1152744925 num_examples: 36710 - name: validation num_bytes: 2333008 num_examples: 73 - name: test num_bytes: 2830297 num_examples: 91 download_size: 1406766 dataset_size: 1157908230 - config_name: EnvironmentalScience,2017-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1231600262 num_examples: 40299 - name: validation num_bytes: 3276640 num_examples: 113 - name: test num_bytes: 3341680 num_examples: 109 download_size: 614999736 dataset_size: 1238218582 - config_name: EnvironmentalScience,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 937901998 num_examples: 30827 - name: validation num_bytes: 2804937 num_examples: 91 - name: test num_bytes: 2376218 num_examples: 68 download_size: 463259737 dataset_size: 943083153 - config_name: EnvironmentalScience,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1651737543 num_examples: 52226 - name: validation num_bytes: 4824616 num_examples: 140 - name: test num_bytes: 4749967 num_examples: 156 download_size: 810352665 dataset_size: 1661312126 - config_name: EnvironmentalScience,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1774514885 num_examples: 55234 - name: validation num_bytes: 5249619 num_examples: 155 - name: test num_bytes: 5966185 num_examples: 178 download_size: 875311800 dataset_size: 1785730689 - config_name: EnvironmentalScience,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1001566163 num_examples: 28712 - name: validation num_bytes: 3040047 num_examples: 89 - name: test num_bytes: 3637076 num_examples: 102 download_size: 490528236 dataset_size: 1008243286 - config_name: Geology,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1535334229 num_examples: 52252 - name: validation num_bytes: 4627919 num_examples: 160 - name: test num_bytes: 3748880 num_examples: 138 download_size: 1861317 dataset_size: 1543711028 - config_name: History,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 593119807 num_examples: 16571 - name: validation num_bytes: 998664 num_examples: 32 - name: test num_bytes: 2122443 num_examples: 51 download_size: 329614856 dataset_size: 596240914 - config_name: Linguistics,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 702861668 num_examples: 22730 - name: validation num_bytes: 1860899 num_examples: 54 - name: test num_bytes: 1725350 num_examples: 56 download_size: 360980655 dataset_size: 706447917 - config_name: MaterialsScience,1970-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1064761631 num_examples: 51178 - name: validation num_bytes: 2945233 num_examples: 143 - name: test num_bytes: 2913700 num_examples: 133 download_size: 534451144 dataset_size: 1070620564 - config_name: MaterialsScience,2016-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1352059727 num_examples: 58515 - name: validation num_bytes: 3564600 num_examples: 158 - name: test num_bytes: 3301368 num_examples: 134 download_size: 633992451 dataset_size: 1358925695 - config_name: MaterialsScience,2019-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2050286158 num_examples: 80015 - name: validation num_bytes: 5255914 num_examples: 206 - name: test num_bytes: 5827718 num_examples: 223 download_size: 931611635 dataset_size: 2061369790 - config_name: MaterialsScience,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1367377287 num_examples: 48883 - name: validation num_bytes: 3868183 num_examples: 138 - name: test num_bytes: 3501025 num_examples: 133 download_size: 630397590 dataset_size: 1374746495 - config_name: MaterialsScience,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1013794974 num_examples: 30824 - name: validation num_bytes: 3164759 num_examples: 99 - name: test num_bytes: 3127971 num_examples: 88 download_size: 453004497 dataset_size: 1020087704 - config_name: Mathematics,1970-2002 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 846480469 num_examples: 29186 - name: validation num_bytes: 2069056 num_examples: 70 - name: test num_bytes: 2392862 num_examples: 80 download_size: 426147719 dataset_size: 850942387 - config_name: Mathematics,2003-2006 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 830661116 num_examples: 27584 - name: validation num_bytes: 2478133 num_examples: 87 - name: test num_bytes: 2018333 num_examples: 64 download_size: 415498823 dataset_size: 835157582 - config_name: Mathematics,2007-2009 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 919320593 num_examples: 30061 - name: validation num_bytes: 2188054 num_examples: 67 - name: test num_bytes: 1975845 num_examples: 77 download_size: 458235420 dataset_size: 923484492 - config_name: Mathematics,2010-2011 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 887913728 num_examples: 28403 - name: validation num_bytes: 2238031 num_examples: 68 - name: test num_bytes: 2163251 num_examples: 72 download_size: 441244863 dataset_size: 892315010 - config_name: Mathematics,2012-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1126142302 num_examples: 36204 - name: validation num_bytes: 2656159 num_examples: 78 - name: test num_bytes: 2652778 num_examples: 83 download_size: 558691314 dataset_size: 1131451239 - config_name: Mathematics,2014-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1341829009 num_examples: 43291 - name: validation num_bytes: 3162993 num_examples: 109 - name: test num_bytes: 3267577 num_examples: 115 download_size: 665313022 dataset_size: 1348259579 - config_name: Mathematics,2016-2017 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1450557097 num_examples: 46835 - name: validation num_bytes: 3415426 num_examples: 115 - name: test num_bytes: 3538559 num_examples: 117 download_size: 717663207 dataset_size: 1457511082 - config_name: Mathematics,2018-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 845215007 num_examples: 26529 - name: validation num_bytes: 2507379 num_examples: 79 - name: test num_bytes: 2322503 num_examples: 72 download_size: 418428368 dataset_size: 850044889 - config_name: Mathematics,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 959002271 num_examples: 30028 - name: validation num_bytes: 1867573 num_examples: 70 - name: test num_bytes: 2758013 num_examples: 96 download_size: 1385268 dataset_size: 963627857 - config_name: Mathematics,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1379043155 num_examples: 43442 - name: validation num_bytes: 3907532 num_examples: 124 - name: test num_bytes: 3931391 num_examples: 133 download_size: 679711638 dataset_size: 1386882078 - config_name: Mathematics,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1572102919 num_examples: 48926 - name: validation num_bytes: 3674120 num_examples: 119 - name: test num_bytes: 4727864 num_examples: 137 download_size: 775185943 dataset_size: 1580504903 - config_name: Mathematics,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1338821191 num_examples: 40114 - name: validation num_bytes: 2676885 num_examples: 90 - name: test num_bytes: 3272973 num_examples: 98 download_size: 659773444 dataset_size: 1344771049 - config_name: Medicine,1970-2006 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 990607945 num_examples: 50184 - name: validation num_bytes: 2386409 num_examples: 130 - name: test num_bytes: 2986872 num_examples: 139 download_size: 508761803 dataset_size: 995981226 - config_name: Medicine,2007-2009 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 996357425 num_examples: 48764 - name: validation num_bytes: 2597882 num_examples: 126 - name: test num_bytes: 2493760 num_examples: 129 download_size: 508861165 dataset_size: 1001449067 - config_name: Medicine,2010-2011 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1434685997 num_examples: 69379 - name: validation num_bytes: 3397637 num_examples: 162 - name: test num_bytes: 3796283 num_examples: 175 download_size: 732595115 dataset_size: 1441879917 - config_name: Medicine,2012-2012 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1123710075 num_examples: 54263 - name: validation num_bytes: 3010698 num_examples: 145 - name: test num_bytes: 2790452 num_examples: 135 download_size: 382795913 dataset_size: 1129511225 - config_name: Medicine,2013-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1416231720 num_examples: 68831 - name: validation num_bytes: 3513360 num_examples: 150 - name: test num_bytes: 3060734 num_examples: 158 download_size: 719406611 dataset_size: 1422805814 - config_name: Medicine,2014-2014 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1716387018 num_examples: 84039 - name: validation num_bytes: 4445950 num_examples: 225 - name: test num_bytes: 4735154 num_examples: 220 download_size: 873757854 dataset_size: 1725568122 - config_name: Medicine,2015-2015 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2007835413 num_examples: 99661 - name: validation num_bytes: 6075038 num_examples: 287 - name: test num_bytes: 5299538 num_examples: 262 download_size: 1021954243 dataset_size: 2019209989 - config_name: Medicine,2016-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2302308148 num_examples: 114798 - name: validation num_bytes: 5549132 num_examples: 292 - name: test num_bytes: 5976797 num_examples: 316 download_size: 1170729155 dataset_size: 2313834077 - config_name: Medicine,2017-2017 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2662110123 num_examples: 132983 - name: validation num_bytes: 7078602 num_examples: 355 - name: test num_bytes: 7502718 num_examples: 374 download_size: 1351442447 dataset_size: 2676691443 - config_name: Medicine,2018-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2918960091 num_examples: 144691 - name: validation num_bytes: 8372854 num_examples: 424 - name: test num_bytes: 7290243 num_examples: 372 download_size: 1478352248 dataset_size: 2934623188 - config_name: Medicine,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 3449427826 num_examples: 168195 - name: validation num_bytes: 9077710 num_examples: 456 - name: test num_bytes: 9319315 num_examples: 445 download_size: 1740957753 dataset_size: 3467824851 - config_name: Medicine,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 5601562513 num_examples: 276750 - name: validation num_bytes: 15089143 num_examples: 748 - name: test num_bytes: 17209190 num_examples: 839 download_size: 2841240978 dataset_size: 5633860846 - config_name: Medicine,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 6336342818 num_examples: 294031 - name: validation num_bytes: 20389330 num_examples: 910 - name: test num_bytes: 19544674 num_examples: 884 download_size: 19990518 dataset_size: 6376276822 - config_name: Medicine,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 5127847171 num_examples: 222968 - name: validation num_bytes: 15389268 num_examples: 674 - name: test num_bytes: 17145287 num_examples: 739 download_size: 2574155290 dataset_size: 5160381726 - config_name: NA,1970-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: 'null' - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1087169582 num_examples: 43379 - name: validation num_bytes: 2815881 num_examples: 113 - name: test num_bytes: 2715252 num_examples: 103 download_size: 563431199 dataset_size: 1092700715 - config_name: NA,2020-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: 'null' - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 935408928 num_examples: 38294 - name: validation num_bytes: 2447639 num_examples: 97 - name: test num_bytes: 2699763 num_examples: 120 download_size: 480518253 dataset_size: 940556330 - config_name: Philosophy,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 699782975 num_examples: 16720 - name: validation num_bytes: 2151362 num_examples: 50 - name: test num_bytes: 2081933 num_examples: 54 download_size: 364987559 dataset_size: 704016270 - config_name: Physics,1970-1997 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 996712343 num_examples: 40356 - name: validation num_bytes: 3022483 num_examples: 103 - name: test num_bytes: 2975836 num_examples: 117 download_size: 511993878 dataset_size: 1002710662 - config_name: Physics,1998-2000 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1175695732 num_examples: 47324 - name: validation num_bytes: 3314041 num_examples: 136 - name: test num_bytes: 3022527 num_examples: 111 download_size: 602264027 dataset_size: 1182032300 - config_name: Physics,2001-2002 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 953095112 num_examples: 38372 - name: validation num_bytes: 2526388 num_examples: 88 - name: test num_bytes: 2623271 num_examples: 96 download_size: 487658058 dataset_size: 958244771 - config_name: Physics,2003-2004 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1118679015 num_examples: 43838 - name: validation num_bytes: 2592724 num_examples: 103 - name: test num_bytes: 3018238 num_examples: 110 download_size: 571711813 dataset_size: 1124289977 - config_name: Physics,2005-2006 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1264243180 num_examples: 49373 - name: validation num_bytes: 2877851 num_examples: 116 - name: test num_bytes: 3055750 num_examples: 125 download_size: 645341608 dataset_size: 1270176781 - config_name: Physics,2007-2008 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1531662184 num_examples: 57443 - name: validation num_bytes: 4458826 num_examples: 170 - name: test num_bytes: 4382777 num_examples: 162 download_size: 782320301 dataset_size: 1540503787 - config_name: Physics,2009-2009 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 923997630 num_examples: 33644 - name: validation num_bytes: 2333875 num_examples: 91 - name: test num_bytes: 3631904 num_examples: 122 download_size: 472489971 dataset_size: 929963409 - config_name: Physics,2010-2010 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 986468513 num_examples: 35414 - name: validation num_bytes: 2466434 num_examples: 94 - name: test num_bytes: 2512360 num_examples: 86 download_size: 501960266 dataset_size: 991447307 - config_name: Physics,2011-2011 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1042729692 num_examples: 36926 - name: validation num_bytes: 2592409 num_examples: 93 - name: test num_bytes: 2624595 num_examples: 104 download_size: 530566944 dataset_size: 1047946696 - config_name: Physics,2012-2012 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1131491509 num_examples: 39311 - name: validation num_bytes: 3124299 num_examples: 102 - name: test num_bytes: 3286609 num_examples: 103 download_size: 575451292 dataset_size: 1137902417 - config_name: Physics,2013-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1215679307 num_examples: 41820 - name: validation num_bytes: 3371577 num_examples: 121 - name: test num_bytes: 2818658 num_examples: 94 download_size: 617356578 dataset_size: 1221869542 - config_name: Physics,2014-2014 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1264940702 num_examples: 43698 - 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name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1444896563 num_examples: 48744 - name: validation num_bytes: 3790598 num_examples: 126 - name: test num_bytes: 4306073 num_examples: 140 download_size: 729465421 dataset_size: 1452993234 - config_name: Physics,2017-2017 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1488446507 num_examples: 50248 - name: validation num_bytes: 4572417 num_examples: 150 - name: test num_bytes: 3963215 num_examples: 134 download_size: 749795624 dataset_size: 1496982139 - config_name: Physics,2018-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1599118343 num_examples: 52807 - name: validation num_bytes: 4936857 num_examples: 150 - name: test num_bytes: 4342191 num_examples: 146 download_size: 802446836 dataset_size: 1608397391 - config_name: Physics,2019-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1578125347 num_examples: 54381 - name: validation num_bytes: 4343180 num_examples: 141 - name: test num_bytes: 4215930 num_examples: 139 download_size: 4281057 dataset_size: 1586684457 - config_name: Physics,2020-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2207397136 num_examples: 70544 - name: validation num_bytes: 5124805 num_examples: 162 - name: test num_bytes: 5921102 num_examples: 187 download_size: 1099589886 dataset_size: 2218443043 - config_name: Physics,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2593752465 num_examples: 78070 - name: validation num_bytes: 7459400 num_examples: 217 - name: test num_bytes: 7444774 num_examples: 225 download_size: 1294995936 dataset_size: 2608656639 - config_name: Physics,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 2047567138 num_examples: 59784 - name: validation num_bytes: 5270232 num_examples: 171 - name: test num_bytes: 5717602 num_examples: 171 download_size: 1022712988 dataset_size: 2058554972 - config_name: PoliticalScience,1970-2019 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1006892286 num_examples: 28541 - name: validation num_bytes: 2647698 num_examples: 74 - name: test num_bytes: 3599529 num_examples: 98 download_size: 530667465 dataset_size: 1013139513 - config_name: PoliticalScience,2020-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1310619817 num_examples: 36103 - name: validation num_bytes: 3991340 num_examples: 106 - name: test num_bytes: 4235433 num_examples: 111 download_size: 685209845 dataset_size: 1318846590 - config_name: Psychology,1970-2013 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1117411430 num_examples: 36287 - name: validation num_bytes: 2510181 num_examples: 85 - name: test num_bytes: 2853532 num_examples: 89 download_size: 562508752 dataset_size: 1122775143 - config_name: Psychology,2014-2016 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1373846789 num_examples: 42327 - name: validation num_bytes: 3565404 num_examples: 111 - name: test num_bytes: 4218171 num_examples: 119 download_size: 686592853 dataset_size: 1381630364 - config_name: Psychology,2017-2018 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1277136501 num_examples: 38942 - name: validation num_bytes: 2908448 num_examples: 89 - name: test num_bytes: 3062923 num_examples: 106 download_size: 426756281 dataset_size: 1283107872 - config_name: Psychology,2019-2020 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1888854114 num_examples: 58291 - name: validation num_bytes: 5510898 num_examples: 176 - name: test num_bytes: 6525937 num_examples: 183 download_size: 943916499 dataset_size: 1900890949 - config_name: Psychology,2021-2021 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1355151368 num_examples: 40768 - name: validation num_bytes: 4574498 num_examples: 131 - name: test num_bytes: 4888404 num_examples: 147 download_size: 677289085 dataset_size: 1364614270 - config_name: Psychology,2022-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1108745002 num_examples: 32538 - name: validation num_bytes: 4590296 num_examples: 126 - name: test num_bytes: 3695430 num_examples: 105 download_size: 550402476 dataset_size: 1117030728 - config_name: Sociology,1970-2022 features: - name: added dtype: string - name: attributes struct: - name: bff_duplicate_paragraph_spans_decontamination sequence: 'null' - name: bff_contained_ngram_count dtype: int64 - name: bff_duplicate_spans sequence: 'null' - name: created dtype: string - name: id dtype: string - name: metadata struct: - name: extfieldsofstudy sequence: string - name: provenance dtype: string - name: s2fieldsofstudy sequence: string - name: sha1 dtype: string - name: year dtype: int64 - name: source dtype: string - name: text dtype: string - name: version dtype: string splits: - name: train num_bytes: 1244403684 num_examples: 32482 - name: validation num_bytes: 3129941 num_examples: 81 - name: test num_bytes: 3541910 num_examples: 101 download_size: 664065280 dataset_size: 1251075535 configs: - config_name: AgriculturalAndFoodSciences,1970-2015 data_files: - split: train path: AgriculturalAndFoodSciences,1970-2015/train-* - split: validation path: AgriculturalAndFoodSciences,1970-2015/validation-* - split: test path: AgriculturalAndFoodSciences,1970-2015/test-* - config_name: AgriculturalAndFoodSciences,2016-2018 data_files: - split: train path: AgriculturalAndFoodSciences,2016-2018/train-* - split: validation path: AgriculturalAndFoodSciences,2016-2018/validation-* - split: test path: AgriculturalAndFoodSciences,2016-2018/test-* - config_name: AgriculturalAndFoodSciences,2019-2020 data_files: - split: train path: AgriculturalAndFoodSciences,2019-2020/train-* - split: validation path: AgriculturalAndFoodSciences,2019-2020/validation-* - split: test path: AgriculturalAndFoodSciences,2019-2020/test-* - config_name: AgriculturalAndFoodSciences,2021-2021 data_files: - split: train path: AgriculturalAndFoodSciences,2021-2021/train-* - split: validation path: AgriculturalAndFoodSciences,2021-2021/validation-* - split: test path: AgriculturalAndFoodSciences,2021-2021/test-* - config_name: AgriculturalAndFoodSciences,2022-2022 data_files: - split: train path: AgriculturalAndFoodSciences,2022-2022/train-* - split: validation path: AgriculturalAndFoodSciences,2022-2022/validation-* - split: test path: AgriculturalAndFoodSciences,2022-2022/test-* - config_name: Art,1970-2022 data_files: - split: train path: Art,1970-2022/train-* - split: validation path: Art,1970-2022/validation-* - split: test path: Art,1970-2022/test-* - config_name: Biology,1970-1993 data_files: - split: train path: Biology,1970-1993/train-* - split: validation path: Biology,1970-1993/validation-* - split: test path: Biology,1970-1993/test-* - config_name: Biology,1994-1999 data_files: - split: train path: Biology,1994-1999/train-* - split: validation path: Biology,1994-1999/validation-* - split: test path: Biology,1994-1999/test-* - config_name: Biology,2000-2003 data_files: - split: train path: Biology,2000-2003/train-* - split: validation path: Biology,2000-2003/validation-* - split: test path: Biology,2000-2003/test-* - config_name: Biology,2004-2006 data_files: - split: train path: Biology,2004-2006/train-* - split: validation path: Biology,2004-2006/validation-* - split: test path: Biology,2004-2006/test-* - config_name: Biology,2007-2008 data_files: - split: train path: Biology,2007-2008/train-* - split: validation path: Biology,2007-2008/validation-* - split: test path: Biology,2007-2008/test-* - config_name: Biology,2009-2010 data_files: - split: train path: Biology,2009-2010/train-* - split: validation path: Biology,2009-2010/validation-* - split: test path: Biology,2009-2010/test-* - config_name: Biology,2011-2011 data_files: - split: train path: Biology,2011-2011/train-* - split: validation path: Biology,2011-2011/validation-* - split: test path: Biology,2011-2011/test-* - config_name: Biology,2012-2012 data_files: - split: train path: Biology,2012-2012/train-* - split: validation path: Biology,2012-2012/validation-* - split: test path: Biology,2012-2012/test-* - config_name: Biology,2013-2013 data_files: - split: train path: Biology,2013-2013/train-* - split: validation path: Biology,2013-2013/validation-* - split: test path: Biology,2013-2013/test-* - config_name: Biology,2014-2014 data_files: - split: train path: Biology,2014-2014/train-* - split: validation path: Biology,2014-2014/validation-* - split: test path: Biology,2014-2014/test-* - config_name: Biology,2015-2015 data_files: - split: train path: Biology,2015-2015/train-* - split: validation path: Biology,2015-2015/validation-* - split: test path: Biology,2015-2015/test-* - config_name: Biology,2016-2016 data_files: - split: train path: Biology,2016-2016/train-* - split: validation path: Biology,2016-2016/validation-* - split: test path: Biology,2016-2016/test-* - config_name: Biology,2017-2017 data_files: - split: train path: Biology,2017-2017/train-* - split: validation path: Biology,2017-2017/validation-* - split: test path: Biology,2017-2017/test-* - config_name: Biology,2018-2018 data_files: - split: train path: Biology,2018-2018/train-* - split: validation path: Biology,2018-2018/validation-* - split: test path: Biology,2018-2018/test-* - config_name: Biology,2019-2019 data_files: - split: train path: Biology,2019-2019/train-* - split: validation path: Biology,2019-2019/validation-* - split: test path: Biology,2019-2019/test-* - config_name: Biology,2020-2020 data_files: - split: train path: Biology,2020-2020/train-* - split: validation path: Biology,2020-2020/validation-* - split: test path: Biology,2020-2020/test-* - config_name: Biology,2021-2021 data_files: - split: train path: Biology,2021-2021/train-* - split: validation path: Biology,2021-2021/validation-* - split: test path: Biology,2021-2021/test-* - config_name: Biology,2022-2022 data_files: - split: train path: Biology,2022-2022/train-* - split: validation path: Biology,2022-2022/validation-* - split: test path: Biology,2022-2022/test-* - config_name: Business,1970-2017 data_files: - split: train path: Business,1970-2017/train-* - split: validation path: Business,1970-2017/validation-* - split: test path: Business,1970-2017/test-* - config_name: Business,2018-2019 data_files: - split: train path: Business,2018-2019/train-* - split: validation path: Business,2018-2019/validation-* - split: test path: Business,2018-2019/test-* - config_name: Business,2020-2020 data_files: - split: train path: Business,2020-2020/train-* - split: validation path: Business,2020-2020/validation-* - split: test path: Business,2020-2020/test-* - config_name: Business,2021-2022 data_files: - split: train path: Business,2021-2022/train-* - split: validation path: Business,2021-2022/validation-* - split: test path: Business,2021-2022/test-* - config_name: Chemistry,1970-2014 data_files: - split: train path: Chemistry,1970-2014/train-* - split: validation path: Chemistry,1970-2014/validation-* - split: test path: Chemistry,1970-2014/test-* - config_name: Chemistry,2015-2018 data_files: - split: train path: Chemistry,2015-2018/train-* - split: validation path: Chemistry,2015-2018/validation-* - split: test path: Chemistry,2015-2018/test-* - config_name: Chemistry,2019-2020 data_files: - split: train path: Chemistry,2019-2020/train-* - split: validation path: Chemistry,2019-2020/validation-* - split: test path: Chemistry,2019-2020/test-* - config_name: Chemistry,2021-2022 data_files: - split: train path: Chemistry,2021-2022/train-* - split: validation path: Chemistry,2021-2022/validation-* - split: test path: Chemistry,2021-2022/test-* - config_name: ComputerScience,1970-2008 data_files: - split: train path: ComputerScience,1970-2008/train-* - split: validation path: ComputerScience,1970-2008/validation-* - split: test path: ComputerScience,1970-2008/test-* - config_name: ComputerScience,2009-2011 data_files: - split: train path: ComputerScience,2009-2011/train-* - split: validation path: ComputerScience,2009-2011/validation-* - split: test path: ComputerScience,2009-2011/test-* - config_name: ComputerScience,2012-2013 data_files: - split: train path: ComputerScience,2012-2013/train-* - split: validation path: ComputerScience,2012-2013/validation-* - split: test path: ComputerScience,2012-2013/test-* - config_name: ComputerScience,2014-2015 data_files: - split: train path: ComputerScience,2014-2015/train-* - split: validation path: ComputerScience,2014-2015/validation-* - split: test path: ComputerScience,2014-2015/test-* - config_name: ComputerScience,2016-2016 data_files: - split: train path: ComputerScience,2016-2016/train-* - split: validation path: ComputerScience,2016-2016/validation-* - split: test path: ComputerScience,2016-2016/test-* - config_name: ComputerScience,2017-2017 data_files: - split: train path: ComputerScience,2017-2017/train-* - split: validation path: ComputerScience,2017-2017/validation-* - split: test path: ComputerScience,2017-2017/test-* - config_name: ComputerScience,2018-2018 data_files: - split: train path: ComputerScience,2018-2018/train-* - split: validation path: ComputerScience,2018-2018/validation-* - split: test path: ComputerScience,2018-2018/test-* - config_name: ComputerScience,2019-2019 data_files: - split: train path: ComputerScience,2019-2019/train-* - split: validation path: ComputerScience,2019-2019/validation-* - split: test path: ComputerScience,2019-2019/test-* - config_name: ComputerScience,2020-2020 data_files: - split: train path: ComputerScience,2020-2020/train-* - split: validation path: ComputerScience,2020-2020/validation-* - split: test path: ComputerScience,2020-2020/test-* - config_name: ComputerScience,2021-2021 data_files: - split: train path: ComputerScience,2021-2021/train-* - split: validation path: ComputerScience,2021-2021/validation-* - split: test path: ComputerScience,2021-2021/test-* - config_name: ComputerScience,2022-2022 data_files: - split: train path: ComputerScience,2022-2022/train-* - split: validation path: ComputerScience,2022-2022/validation-* - split: test path: ComputerScience,2022-2022/test-* - config_name: Economics,1970-2016 data_files: - split: train path: Economics,1970-2016/train-* - split: validation path: Economics,1970-2016/validation-* - split: test path: Economics,1970-2016/test-* - config_name: Economics,2017-2019 data_files: - split: train path: Economics,2017-2019/train-* - split: validation path: Economics,2017-2019/validation-* - split: test path: Economics,2017-2019/test-* - config_name: Economics,2020-2020 data_files: - split: train path: Economics,2020-2020/train-* - split: validation path: Economics,2020-2020/validation-* - split: test path: Economics,2020-2020/test-* - config_name: Economics,2021-2022 data_files: - split: train path: Economics,2021-2022/train-* - split: validation path: Economics,2021-2022/validation-* - split: test path: Economics,2021-2022/test-* - config_name: Education,1970-2018 data_files: - split: train path: Education,1970-2018/train-* - split: validation path: Education,1970-2018/validation-* - split: test path: Education,1970-2018/test-* - config_name: Education,2019-2020 data_files: - split: train path: Education,2019-2020/train-* - split: validation path: Education,2019-2020/validation-* - split: test path: Education,2019-2020/test-* - config_name: Education,2021-2022 data_files: - split: train path: Education,2021-2022/train-* - split: validation path: Education,2021-2022/validation-* - split: test path: Education,2021-2022/test-* - config_name: Engineering,1970-2016 data_files: - split: train path: Engineering,1970-2016/train-* - split: validation path: Engineering,1970-2016/validation-* - split: test path: Engineering,1970-2016/test-* - config_name: Engineering,2017-2019 data_files: - split: train path: Engineering,2017-2019/train-* - split: validation path: Engineering,2017-2019/validation-* - split: test path: Engineering,2017-2019/test-* - config_name: Engineering,2020-2020 data_files: - split: train path: Engineering,2020-2020/train-* - split: validation path: Engineering,2020-2020/validation-* - split: test path: Engineering,2020-2020/test-* - config_name: Engineering,2021-2021 data_files: - split: train path: Engineering,2021-2021/train-* - split: validation path: Engineering,2021-2021/validation-* - split: test path: Engineering,2021-2021/test-* - config_name: Engineering,2022-2022 data_files: - split: train path: Engineering,2022-2022/train-* - split: validation path: Engineering,2022-2022/validation-* - split: test path: Engineering,2022-2022/test-* - config_name: EnvironmentalScience,1970-2013 data_files: - split: train path: EnvironmentalScience,1970-2013/train-* - split: validation path: EnvironmentalScience,1970-2013/validation-* - split: test path: EnvironmentalScience,1970-2013/test-* - config_name: EnvironmentalScience,2014-2016 data_files: - split: train path: EnvironmentalScience,2014-2016/train-* - split: validation path: EnvironmentalScience,2014-2016/validation-* - split: test path: EnvironmentalScience,2014-2016/test-* - config_name: EnvironmentalScience,2017-2018 data_files: - split: train path: EnvironmentalScience,2017-2018/train-* - split: validation path: EnvironmentalScience,2017-2018/validation-* - split: test path: EnvironmentalScience,2017-2018/test-* - config_name: EnvironmentalScience,2019-2019 data_files: - split: train path: EnvironmentalScience,2019-2019/train-* - split: validation path: EnvironmentalScience,2019-2019/validation-* - split: test path: EnvironmentalScience,2019-2019/test-* - config_name: EnvironmentalScience,2020-2020 data_files: - split: train path: EnvironmentalScience,2020-2020/train-* - split: validation path: EnvironmentalScience,2020-2020/validation-* - split: test path: EnvironmentalScience,2020-2020/test-* - config_name: EnvironmentalScience,2021-2021 data_files: - split: train path: EnvironmentalScience,2021-2021/train-* - split: validation path: EnvironmentalScience,2021-2021/validation-* - split: test path: EnvironmentalScience,2021-2021/test-* - config_name: EnvironmentalScience,2022-2022 data_files: - split: train path: EnvironmentalScience,2022-2022/train-* - split: validation path: EnvironmentalScience,2022-2022/validation-* - split: test path: EnvironmentalScience,2022-2022/test-* - config_name: Geology,1970-2022 data_files: - split: train path: Geology,1970-2022/train-* - split: validation path: Geology,1970-2022/validation-* - split: test path: Geology,1970-2022/test-* - config_name: History,1970-2022 data_files: - split: train path: History,1970-2022/train-* - split: validation path: History,1970-2022/validation-* - split: test path: History,1970-2022/test-* - config_name: Linguistics,1970-2022 data_files: - split: train path: Linguistics,1970-2022/train-* - split: validation path: Linguistics,1970-2022/validation-* - split: test path: Linguistics,1970-2022/test-* - config_name: MaterialsScience,1970-2015 data_files: - split: train path: MaterialsScience,1970-2015/train-* - split: validation path: MaterialsScience,1970-2015/validation-* - split: test path: MaterialsScience,1970-2015/test-* - config_name: MaterialsScience,2016-2018 data_files: - split: train path: MaterialsScience,2016-2018/train-* - split: validation path: MaterialsScience,2016-2018/validation-* - split: test path: MaterialsScience,2016-2018/test-* - config_name: MaterialsScience,2019-2020 data_files: - split: train path: MaterialsScience,2019-2020/train-* - split: validation path: MaterialsScience,2019-2020/validation-* - split: test path: MaterialsScience,2019-2020/test-* - config_name: MaterialsScience,2021-2021 data_files: - split: train path: MaterialsScience,2021-2021/train-* - split: validation path: MaterialsScience,2021-2021/validation-* - split: test path: MaterialsScience,2021-2021/test-* - config_name: MaterialsScience,2022-2022 data_files: - split: train path: MaterialsScience,2022-2022/train-* - split: validation path: MaterialsScience,2022-2022/validation-* - split: test path: MaterialsScience,2022-2022/test-* - config_name: Mathematics,1970-2002 data_files: - split: train path: Mathematics,1970-2002/train-* - split: validation path: Mathematics,1970-2002/validation-* - split: test path: Mathematics,1970-2002/test-* - config_name: Mathematics,2003-2006 data_files: - split: train path: Mathematics,2003-2006/train-* - split: validation path: Mathematics,2003-2006/validation-* - split: test path: Mathematics,2003-2006/test-* - config_name: Mathematics,2007-2009 data_files: - split: train path: Mathematics,2007-2009/train-* - split: validation path: Mathematics,2007-2009/validation-* - split: test path: Mathematics,2007-2009/test-* - config_name: Mathematics,2010-2011 data_files: - split: train path: Mathematics,2010-2011/train-* - split: validation path: Mathematics,2010-2011/validation-* - split: test path: Mathematics,2010-2011/test-* - config_name: Mathematics,2012-2013 data_files: - split: train path: Mathematics,2012-2013/train-* - split: validation path: Mathematics,2012-2013/validation-* - split: test path: Mathematics,2012-2013/test-* - config_name: Mathematics,2014-2015 data_files: - split: train path: Mathematics,2014-2015/train-* - split: validation path: Mathematics,2014-2015/validation-* - split: test path: Mathematics,2014-2015/test-* - config_name: Mathematics,2016-2017 data_files: - split: train path: Mathematics,2016-2017/train-* - split: validation path: Mathematics,2016-2017/validation-* - split: test path: Mathematics,2016-2017/test-* - config_name: Mathematics,2018-2018 data_files: - split: train path: Mathematics,2018-2018/train-* - split: validation path: Mathematics,2018-2018/validation-* - split: test path: Mathematics,2018-2018/test-* - config_name: Mathematics,2019-2019 data_files: - split: train path: Mathematics,2019-2019/train-* - split: validation path: Mathematics,2019-2019/validation-* - split: test path: Mathematics,2019-2019/test-* - config_name: Mathematics,2020-2020 data_files: - split: train path: Mathematics,2020-2020/train-* - split: validation path: Mathematics,2020-2020/validation-* - split: test path: Mathematics,2020-2020/test-* - config_name: Mathematics,2021-2021 data_files: - split: train path: Mathematics,2021-2021/train-* - split: validation path: Mathematics,2021-2021/validation-* - split: test path: Mathematics,2021-2021/test-* - config_name: Mathematics,2022-2022 data_files: - split: train path: Mathematics,2022-2022/train-* - split: validation path: Mathematics,2022-2022/validation-* - split: test path: Mathematics,2022-2022/test-* - config_name: Medicine,1970-2006 data_files: - split: train path: Medicine,1970-2006/train-* - split: validation path: Medicine,1970-2006/validation-* - split: test path: Medicine,1970-2006/test-* - config_name: Medicine,2007-2009 data_files: - split: train path: Medicine,2007-2009/train-* - split: validation path: Medicine,2007-2009/validation-* - split: test path: Medicine,2007-2009/test-* - config_name: Medicine,2010-2011 data_files: - split: train path: Medicine,2010-2011/train-* - split: validation path: Medicine,2010-2011/validation-* - split: test path: Medicine,2010-2011/test-* - config_name: Medicine,2012-2012 data_files: - split: train path: Medicine,2012-2012/train-* - split: validation path: Medicine,2012-2012/validation-* - split: test path: Medicine,2012-2012/test-* - config_name: Medicine,2013-2013 data_files: - split: train path: Medicine,2013-2013/train-* - split: validation path: Medicine,2013-2013/validation-* - split: test path: Medicine,2013-2013/test-* - config_name: Medicine,2014-2014 data_files: - split: train path: Medicine,2014-2014/train-* - split: validation path: Medicine,2014-2014/validation-* - split: test path: Medicine,2014-2014/test-* - config_name: Medicine,2015-2015 data_files: - split: train path: Medicine,2015-2015/train-* - split: validation path: Medicine,2015-2015/validation-* - split: test path: Medicine,2015-2015/test-* - config_name: Medicine,2016-2016 data_files: - split: train path: Medicine,2016-2016/train-* - split: validation path: Medicine,2016-2016/validation-* - split: test path: Medicine,2016-2016/test-* - config_name: Medicine,2017-2017 data_files: - split: train path: Medicine,2017-2017/train-* - split: validation path: Medicine,2017-2017/validation-* - split: test path: Medicine,2017-2017/test-* - config_name: Medicine,2018-2018 data_files: - split: train path: Medicine,2018-2018/train-* - split: validation path: Medicine,2018-2018/validation-* - split: test path: Medicine,2018-2018/test-* - config_name: Medicine,2019-2019 data_files: - split: train path: Medicine,2019-2019/train-* - split: validation path: Medicine,2019-2019/validation-* - split: test path: Medicine,2019-2019/test-* - config_name: Medicine,2020-2020 data_files: - split: train path: Medicine,2020-2020/train-* - split: validation path: Medicine,2020-2020/validation-* - split: test path: Medicine,2020-2020/test-* - config_name: Medicine,2021-2021 data_files: - split: train path: Medicine,2021-2021/train-* - split: validation path: Medicine,2021-2021/validation-* - split: test path: Medicine,2021-2021/test-* - config_name: Medicine,2022-2022 data_files: - split: train path: Medicine,2022-2022/train-* - split: validation path: Medicine,2022-2022/validation-* - split: test path: Medicine,2022-2022/test-* - config_name: NA,1970-2019 data_files: - split: train path: NA,1970-2019/train-* - split: validation path: NA,1970-2019/validation-* - split: test path: NA,1970-2019/test-* - config_name: NA,2020-2022 data_files: - split: train path: NA,2020-2022/train-* - split: validation path: NA,2020-2022/validation-* - split: test path: NA,2020-2022/test-* - config_name: Philosophy,1970-2022 data_files: - split: train path: Philosophy,1970-2022/train-* - split: validation path: Philosophy,1970-2022/validation-* - split: test path: Philosophy,1970-2022/test-* - config_name: Physics,1970-1997 data_files: - split: train path: Physics,1970-1997/train-* - split: validation path: Physics,1970-1997/validation-* - split: test path: Physics,1970-1997/test-* - config_name: Physics,1998-2000 data_files: - split: train path: Physics,1998-2000/train-* - split: validation path: Physics,1998-2000/validation-* - split: test path: Physics,1998-2000/test-* - config_name: Physics,2001-2002 data_files: - split: train path: Physics,2001-2002/train-* - split: validation path: Physics,2001-2002/validation-* - split: test path: Physics,2001-2002/test-* - config_name: Physics,2003-2004 data_files: - split: train path: Physics,2003-2004/train-* - split: validation path: Physics,2003-2004/validation-* - split: test path: Physics,2003-2004/test-* - config_name: Physics,2005-2006 data_files: - split: train path: Physics,2005-2006/train-* - split: validation path: Physics,2005-2006/validation-* - split: test path: Physics,2005-2006/test-* - config_name: Physics,2007-2008 data_files: - split: train path: Physics,2007-2008/train-* - split: validation path: Physics,2007-2008/validation-* - split: test path: Physics,2007-2008/test-* - config_name: Physics,2009-2009 data_files: - split: train path: Physics,2009-2009/train-* - split: validation path: Physics,2009-2009/validation-* - split: test path: Physics,2009-2009/test-* - config_name: Physics,2010-2010 data_files: - split: train path: Physics,2010-2010/train-* - split: validation path: Physics,2010-2010/validation-* - split: test path: Physics,2010-2010/test-* - config_name: Physics,2011-2011 data_files: - split: train path: Physics,2011-2011/train-* - split: validation path: Physics,2011-2011/validation-* - split: test path: Physics,2011-2011/test-* - config_name: Physics,2012-2012 data_files: - split: train path: Physics,2012-2012/train-* - split: validation path: Physics,2012-2012/validation-* - split: test path: Physics,2012-2012/test-* - config_name: Physics,2013-2013 data_files: - split: train path: Physics,2013-2013/train-* - split: validation path: Physics,2013-2013/validation-* - split: test path: Physics,2013-2013/test-* - config_name: Physics,2014-2014 data_files: - split: train path: Physics,2014-2014/train-* - split: validation path: Physics,2014-2014/validation-* - split: test path: Physics,2014-2014/test-* - config_name: Physics,2015-2015 data_files: - split: train path: Physics,2015-2015/train-* - split: validation path: Physics,2015-2015/validation-* - split: test path: Physics,2015-2015/test-* - config_name: Physics,2016-2016 data_files: - split: train path: Physics,2016-2016/train-* - split: validation path: Physics,2016-2016/validation-* - split: test path: Physics,2016-2016/test-* - config_name: Physics,2017-2017 data_files: - split: train path: Physics,2017-2017/train-* - split: validation path: Physics,2017-2017/validation-* - split: test path: Physics,2017-2017/test-* - config_name: Physics,2018-2018 data_files: - split: train path: Physics,2018-2018/train-* - split: validation path: Physics,2018-2018/validation-* - split: test path: Physics,2018-2018/test-* - config_name: Physics,2019-2019 data_files: - split: train path: Physics,2019-2019/train-* - split: validation path: Physics,2019-2019/validation-* - split: test path: Physics,2019-2019/test-* - config_name: Physics,2020-2020 data_files: - split: train path: Physics,2020-2020/train-* - split: validation path: Physics,2020-2020/validation-* - split: test path: Physics,2020-2020/test-* - config_name: Physics,2021-2021 data_files: - split: train path: Physics,2021-2021/train-* - split: validation path: Physics,2021-2021/validation-* - split: test path: Physics,2021-2021/test-* - config_name: Physics,2022-2022 data_files: - split: train path: Physics,2022-2022/train-* - split: validation path: Physics,2022-2022/validation-* - split: test path: Physics,2022-2022/test-* - config_name: PoliticalScience,1970-2019 data_files: - split: train path: PoliticalScience,1970-2019/train-* - split: validation path: PoliticalScience,1970-2019/validation-* - split: test path: PoliticalScience,1970-2019/test-* - config_name: PoliticalScience,2020-2022 data_files: - split: train path: PoliticalScience,2020-2022/train-* - split: validation path: PoliticalScience,2020-2022/validation-* - split: test path: PoliticalScience,2020-2022/test-* - config_name: Psychology,1970-2013 data_files: - split: train path: Psychology,1970-2013/train-* - split: validation path: Psychology,1970-2013/validation-* - split: test path: Psychology,1970-2013/test-* - config_name: Psychology,2014-2016 data_files: - split: train path: Psychology,2014-2016/train-* - split: validation path: Psychology,2014-2016/validation-* - split: test path: Psychology,2014-2016/test-* - config_name: Psychology,2017-2018 data_files: - split: train path: Psychology,2017-2018/train-* - split: validation path: Psychology,2017-2018/validation-* - split: test path: Psychology,2017-2018/test-* - config_name: Psychology,2019-2020 data_files: - split: train path: Psychology,2019-2020/train-* - split: validation path: Psychology,2019-2020/validation-* - split: test path: Psychology,2019-2020/test-* - config_name: Psychology,2021-2021 data_files: - split: train path: Psychology,2021-2021/train-* - split: validation path: Psychology,2021-2021/validation-* - split: test path: Psychology,2021-2021/test-* - config_name: Psychology,2022-2022 data_files: - split: train path: Psychology,2022-2022/train-* - split: validation path: Psychology,2022-2022/validation-* - split: test path: Psychology,2022-2022/test-* - config_name: Sociology,1970-2022 data_files: - split: train path: Sociology,1970-2022/train-* - split: validation path: Sociology,1970-2022/validation-* - split: test path: Sociology,1970-2022/test-* ---

open-rl-leaderboard/results_v2

open-rl-leaderboard

--- dataset_info: features: - name: user_id dtype: string - name: model_id dtype: string - name: sha dtype: string - name: status dtype: string - name: env_id dtype: string - name: episodic_returns sequence: float64 splits: - name: train num_bytes: 17423994045 num_examples: 46711176 download_size: 14153678919 dataset_size: 17423994045 configs: - config_name: default data_files: - split: train path: data/train-* --- # Dataset Card for "results_v2" [Leaderboard](https://huggingface.co/spaces/open-rl-leaderboard/leaderboard) [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

ncoop57/mmmlu

ncoop57

--- license: mit ---

rethinklab/Bench2Drive-Full

rethinklab

--- license: apache-2.0 ---

fixie-ai/gigaspeech

fixie-ai

--- dataset_info: - config_name: dev features: - name: segment_id dtype: string - name: speaker dtype: string - name: text dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: begin_time dtype: float32 - name: end_time dtype: float32 - name: audio_id dtype: string - name: title dtype: string - name: url dtype: string - name: source dtype: class_label: names: '0': audiobook '1': podcast '2': youtube - name: category dtype: class_label: names: '0': People and Blogs '1': Business '2': Nonprofits and Activism '3': Crime '4': History '5': Pets and Animals '6': News and Politics '7': Travel and Events '8': Kids and Family '9': Leisure '10': N/A '11': Comedy '12': News and Politics '13': Sports '14': Arts '15': Science and Technology '16': Autos and Vehicles '17': Science and Technology '18': People and Blogs '19': Music '20': Society and Culture '21': Education '22': Howto and Style '23': Film and Animation '24': Gaming '25': Entertainment '26': Travel and Events '27': Health and Fitness '28': audiobook - name: original_full_path dtype: string - name: continuation dtype: string splits: - name: dev num_bytes: 1312654399.91 num_examples: 5715 download_size: 1301358984 dataset_size: 1312654399.91 - config_name: xl features: - name: segment_id dtype: string - name: speaker dtype: string - name: text dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: begin_time dtype: float32 - name: end_time dtype: float32 - name: audio_id dtype: string - name: title dtype: string - name: url dtype: string - name: source dtype: class_label: names: '0': audiobook '1': podcast '2': youtube - name: category dtype: class_label: names: '0': People and Blogs '1': Business '2': Nonprofits and Activism '3': Crime '4': History '5': Pets and Animals '6': News and Politics '7': Travel and Events '8': Kids and Family '9': Leisure '10': N/A '11': Comedy '12': News and Politics '13': Sports '14': Arts '15': Science and Technology '16': Autos and Vehicles '17': Science and Technology '18': People and Blogs '19': Music '20': Society and Culture '21': Education '22': Howto and Style '23': Film and Animation '24': Gaming '25': Entertainment '26': Travel and Events '27': Health and Fitness '28': audiobook - name: original_full_path dtype: string - name: continuation dtype: string splits: - name: train num_bytes: 1139131922662.928 num_examples: 8282988 - name: validation num_bytes: 1430434665.0 num_examples: 6750 - name: test num_bytes: 4697631895.032 num_examples: 25619 download_size: 1154360220896 dataset_size: 1145259989222.96 - config_name: xl-empty-audio-removed features: - name: segment_id dtype: string - name: speaker dtype: string - name: text dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: begin_time dtype: float32 - name: end_time dtype: float32 - name: audio_id dtype: string - name: title dtype: string - name: url dtype: string - name: source dtype: class_label: names: '0': audiobook '1': podcast '2': youtube - name: category dtype: class_label: names: '0': People and Blogs '1': Business '2': Nonprofits and Activism '3': Crime '4': History '5': Pets and Animals '6': News and Politics '7': Travel and Events '8': Kids and Family '9': Leisure '10': N/A '11': Comedy '12': News and Politics '13': Sports '14': Arts '15': Science and Technology '16': Autos and Vehicles '17': Science and Technology '18': People and Blogs '19': Music '20': Society and Culture '21': Education '22': Howto and Style '23': Film and Animation '24': Gaming '25': Entertainment '26': Travel and Events '27': Health and Fitness '28': audiobook - name: original_full_path dtype: string - name: continuation dtype: string splits: - name: train num_bytes: 1155056052120.0 num_examples: 8266422 download_size: 1146019390890 dataset_size: 1155056052120.0 configs: - config_name: dev data_files: - split: dev path: dev/dev-* - config_name: xl data_files: - split: train path: xl/train-* - split: validation path: xl/validation-* - split: test path: xl/test-* - config_name: xl-empty-audio-removed data_files: - split: train path: xl-empty-audio-removed/train/** ---

HuggingFaceM4/OBELICS

HuggingFaceM4

--- language: - en license: cc-by-4.0 size_categories: - 100M<n<1B pretty_name: OBELICS configs: - config_name: default data_files: - split: train path: data/train-* - config_name: opt_out_docs_removed_2023_07_12 data_files: - split: train path: opt_out_docs_removed_2023_07_12/train-* dataset_info: - config_name: default features: - name: images sequence: string - name: metadata dtype: string - name: general_metadata dtype: string - name: texts sequence: string splits: - name: train num_bytes: 715724717192 num_examples: 141047697 download_size: 71520629655 dataset_size: 715724717192 - config_name: opt_out_docs_removed_2023_07_12 features: - name: images sequence: string - name: metadata dtype: string - name: general_metadata dtype: string - name: texts sequence: string splits: - name: train num_bytes: 684638314215 num_examples: 134648855 download_size: 266501092920 dataset_size: 684638314215 --- # Dataset Card for OBELICS ## Dataset Description - **Visualization of OBELICS web documents:** https://huggingface.co/spaces/HuggingFaceM4/obelics_visualization - **Paper:** [OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents](https://arxiv.org/abs/2306.16527) - **Repository:** https://github.com/huggingface/OBELICS - **Point of Contact: [email protected]** `OBELICS` is an open, massive, and curated collection of interleaved image-text web documents, containing 141M English documents, 115B text tokens, and 353M images, extracted from Common Crawl dumps between February 2020 and February 2023. The collection and filtering steps are described in our [paper](https://huggingface.co/papers/2306.16527). Interleaved image-text web documents are a succession of text paragraphs interleaved by images, such as web pages that contain images. Models trained on these web documents outperform vision and language models trained solely on image-text pairs on various benchmarks. They can also generate long and coherent text about a set of multiple images. As an example, we trained [IDEFICS](https://huggingface.co/HuggingFaceM4/idefics-80b), a visual language model that accepts arbitrary sequences of image and text inputs and produces text outputs. We provide an [interactive visualization](https://atlas.nomic.ai/map/f2fba2aa-3647-4f49-a0f3-9347daeee499/ee4a84bd-f125-4bcc-a683-1b4e231cb10f) of OBELICS that allows exploring the content of OBELICS. The map shows a subset of 11M of the 141M documents. [](https://atlas.nomic.ai/map/f2fba2aa-3647-4f49-a0f3-9347daeee499/ee4a84bd-f125-4bcc-a683-1b4e231cb10f) ## Data Fields An example of a sample looks as follows: ``` # The example has been cropped { 'images': [ 'https://cdn.motor1.com/images/mgl/oRKO0/s1/lamborghini-urus-original-carbon-fiber-accessories.jpg', None ], 'metadata': '[{"document_url": "https://lamborghinichat.com/forum/news/vw-group-allegedly-receives-offer-to-sell-lamborghini-for-9-2-billion.728/", "unformatted_src": "https://cdn.motor1.com/images/mgl/oRKO0/s1/lamborghini-urus-original-carbon-fiber-accessories.jpg", "src": "https://cdn.motor1.com/images/mgl/oRKO0/s1/lamborghini-urus-original-carbon-fiber-accessories.jpg", "formatted_filename": "lamborghini urus original carbon fiber accessories", "alt_text": "VW Group Allegedly Receives Offer To Sell Lamborghini For $9.2 Billion", "original_width": 1920, "original_height": 1080, "format": "jpeg"}, null]', 'general_metadata': '{"url": "https://lamborghinichat.com/forum/news/vw-group-allegedly-receives-offer-to-sell-lamborghini-for-9-2-billion.728/", "warc_filename": "crawl-data/CC-MAIN-2021-25/segments/1623488528979.69/warc/CC-MAIN-20210623011557-20210623041557-00312.warc.gz", "warc_record_offset": 322560850, "warc_record_length": 17143}', 'texts': [ None, 'The buyer would get everything, including Lambo\'s headquarters.\n\nThe investment groupQuantum Group AG has submitted a€7.5 billion ($9.2 billion at current exchange rates) offer to purchase Lamborghini from Volkswagen Group, Autocar reports. There\'s no info yet about whether VW intends to accept the offer or further negotiate the deal.\n\nQuantum ... Group Chief Executive Herbert Diess said at the time.' ] } ``` Each sample is composed of the same 4 fields: `images`, `texts`, `metadata`, and `general_metadata`. `images` and `texts` are two lists of the same size, where for each index, one element and only one is not `None`. For example, for the interleaved web document `<image_1>text<image_2>`, we would find `[image_1, None, image_2]` in `images` and `[None, text, None]` in `texts`. The images are replaced by their URLs, and the users need to download the images, for instance, with the library [img2dataset](https://github.com/rom1504/img2dataset). `metadata` is the string representation of a list containing information about each of the images. It has the same length as `texts` and `images` and logs for each image relevant information such as original source document, unformatted source, alternative text if present, etc. `general_metadata` is the string representation of a dictionary containing the URL of the document, and information regarding the extraction from Common Crawl snapshots. ## Size and Data Splits There is only one split, `train`, that contains 141,047,697 documents. `OBELICS` with images replaced by their URLs weighs 666.6 GB (😈) in arrow format and 377 GB in the uploaded `parquet` format. ## Considerations for Using the Data ### Discussion of Biases A subset of this dataset `train`, of ~50k was evaluated using the Data Measurements Tool, with a particular focus on the nPMI metric > nPMI scores for a word help to identify potentially problematic associations, ranked by how close the association is. > nPMI bias scores for paired words help to identify how word associations are skewed between the selected selected words (Aka et al., 2021). > You can select from gender and sexual orientation identity terms that appear in the dataset at least 10 times. > The resulting ranked words are those that co-occur with both identity terms. > The more positive the score, the more associated the word is with the first identity term. The more negative the score, the more associated the word is with the second identity term. While there was a positive skew of words relating occupations e.g _`government`_, _`jobs`_ towards she, her, and similar attributions of the masculine and feminine words to they and them, more harmful words attributions such as _`escort`_ and even _`colour`_ presented with greater attributions to she, her and him, his, respectively.  We welcome users to explore the [Data Measurements nPMI Visualitons for OBELICS](https://huggingface.co/spaces/HuggingFaceM4/IDEFICS_Data_Measurement_Tool) further and to see the [idefics-9b model card](https://huggingface.co/HuggingFaceM4/idefics-9b) for further Bias considerations. ## Opted-out content To respect the preferences of content creators, we removed from OBELICS all images for which creators explicitly opted out of AI model training. We used the [Spawning API](https://api.spawning.ai/spawning-api) to verify that the images in the dataset respect the original copyright owners’ choices. However, due to an error on our side, we did not remove entire documents (i.e., URLs) that opted out of AI model training. As of July 12, 2023, it represents 4.25% of the totality of OBELICS. The config `opt_out_docs_removed_2023_07_12` applies the correct filtering at the web document level as of July 2023: `ds = load_dataset("HuggingFaceM4/OBELICS", "opt_out_docs_removed_2023_07_12")`. We recommend users of OBELICS to regularly check every document against the API. ## Content warnings Despite our efforts in filtering, OBELICS contains a small proportion of documents that are not suitable for all audiences. For instance, while navigating the interactive map, you might find the cluster named "Sex" which predominantly contains descriptions of pornographic movies along with pornographic images. Other clusters would contain advertising for sex workers or reports of violent shootings. In our experience, these documents represent a small proportion of all the documents. ## Terms of Use By using the dataset, you agree to comply with the original licenses of the source content as well as the dataset license (CC-BY-4.0). Additionally, if you use this dataset to train a Machine Learning model, you agree to disclose your use of the dataset when releasing the model or an ML application using the model. ### Licensing Information License CC-BY-4.0. ### Citation Information If you are using this dataset, please cite ``` @misc{laurencon2023obelics, title={OBELICS: An Open Web-Scale Filtered Dataset of Interleaved Image-Text Documents}, author={Hugo Laurençon and Lucile Saulnier and Léo Tronchon and Stas Bekman and Amanpreet Singh and Anton Lozhkov and Thomas Wang and Siddharth Karamcheti and Alexander M. Rush and Douwe Kiela and Matthieu Cord and Victor Sanh}, year={2023}, eprint={2306.16527}, archivePrefix={arXiv}, primaryClass={cs.IR} } ```

Antreas/TALI

Antreas

--- configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* - split: test path: data/test-* dataset_info: features: - name: image dtype: image - name: image_url dtype: string - name: item_idx dtype: int64 - name: wit_features struct: - name: attribution_passes_lang_id sequence: bool - name: caption_alt_text_description sequence: string - name: caption_reference_description sequence: string - name: caption_title_and_reference_description sequence: string - name: context_page_description sequence: string - name: context_section_description sequence: string - name: hierarchical_section_title sequence: string - name: is_main_image sequence: bool - name: language sequence: string - name: page_changed_recently sequence: bool - name: page_title sequence: string - name: page_url sequence: string - name: section_title sequence: string - name: wit_idx dtype: int64 - name: youtube_title_text dtype: string - name: youtube_description_text dtype: string - name: youtube_video_content dtype: binary - name: youtube_video_starting_time dtype: string - name: youtube_subtitle_text dtype: string - name: youtube_video_size dtype: int64 - name: youtube_video_file_path dtype: string splits: - name: train num_bytes: 1902638101655.625 num_examples: 1052915 - name: val num_bytes: 104485442867.25 num_examples: 57958 - name: test num_bytes: 111107332347.375 num_examples: 61389 download_size: 2058391040534 dataset_size: 2118230876870.25 license: cc-by-4.0 task_categories: - zero-shot-classification tags: - video - audio - text - image - tetramodal - multimodal - youtube - wikipedia pretty_name: TALI size_categories: - 1M<n<10M --- # Dataset Card for "TALI" ## Table of Contents 1. Dataset Description 1. Abstract 2. Brief Description 2. Dataset Information 1. Modalities 2. Dataset Variants 3. Dataset Statistics 4. Data Fields 5. Data Splits 3. Dataset Creation 4. Dataset Use 5. Additional Information ## Dataset Description ### Abstract TALI is a large-scale, tetramodal dataset designed to facilitate a shift from unimodal and duomodal to tetramodal research in deep learning. It aligns text, video, images, and audio, providing a rich resource for innovative self-supervised learning tasks and multimodal research. TALI enables exploration of how different modalities and data/model scaling affect downstream performance, with the aim of inspiring diverse research ideas and enhancing understanding of model capabilities and robustness in deep learning. ### Brief Description TALI (Temporally and semantically Aligned Audio, Language and Images) is a dataset that uses the Wikipedia Image Text (WIT) captions and article titles to search Youtube for videos that match the captions. It then downloads the video, audio, and subtitles from these videos. The result is a rich multimodal dataset that has multiple caption types related to both the WiT Images, and the Youtube videos. This enables learning to take place between either temporally or semantically aligned text, images, audio and video. ## Dataset Information ### Modalities The TALI dataset consists of the following modalities: 1. Image: 1. Wikipedia caption image 2. Randomly sampled image from youtube video 2. Text 1. Wikipedia Caption Text 2. Wikipedia Title Text 3. Wikipedia Main Body Text 4. YouTube Subtitle Text 5. YouTube Description Text 6. YouTube Title Text 3. Audio 1. YouTube Content Audio 4. Video 1. YouTube Content Video ## Usage: To get started with TALI, you can load the dataset via Hugging Face's `datasets` library through our helper functions. The reason we don't use `datasets` directly is because we found huggingface_hub downloads much faster and reliable. For a full set of possible configurations look at [examples.py](examples.py). Here's a basic usage example: First install the tali package: ### Installation For the default install use: ```bash pip install git+https://github.com/AntreasAntoniou/TALI ``` For the dev install use: ```bash pip install git+https://github.com/AntreasAntoniou/TALI[dev] ``` Then use the dataset using: ### Examples Import relevant helper functions ```python import pathlib from enum import Enum import torch from tqdm.auto import tqdm from tali.data import ( SubModalityTypes, TALIBaseTransform, TALIBaseTransformConfig, VideoFramesFormat, default_transforms, load_dataset_via_hub, ) ``` #### TALI with default transforms (CLIP and Whisper) and no streaming ```python def tali_with_transforms_no_streaming( dataset_storage_path: pathlib.Path | str, ): if isinstance(dataset_storage_path, str): dataset_storage_path = pathlib.Path(dataset_storage_path) dataset = load_dataset_via_hub( dataset_storage_path, dataset_name="Antreas/TALI" )["train"] ( image_transforms, text_transforms, audio_transforms, video_transforms, ) = default_transforms() preprocessing_transform = TALIBaseTransform( cache_dir=dataset_storage_path / "cache", text_tokenizer=text_transforms, image_tokenizer=image_transforms, audio_tokenizer=audio_transforms, video_tokenizer=video_transforms, config=TALIBaseTransformConfig( root_filepath=dataset_storage_path, modality_list=[ SubModalityTypes.youtube_content_video, SubModalityTypes.youtube_content_audio, SubModalityTypes.youtube_random_video_frame, SubModalityTypes.youtube_subtitle_text, SubModalityTypes.youtube_description_text, SubModalityTypes.youtube_title_text, SubModalityTypes.wikipedia_caption_image, SubModalityTypes.wikipedia_caption_text, SubModalityTypes.wikipedia_main_body_text, SubModalityTypes.wikipedia_title_text, ], video_frames_format=VideoFramesFormat.PIL, ), ) for sample in tqdm(dataset): sample = preprocessing_transform(sample) print(list(sample.keys())) for key, value in sample.items(): if hasattr(value, "shape"): print(key, value.shape) elif isinstance(value, torch.Tensor): print(key, value.shape) elif hasattr(value, "__len__"): print(key, len(value)) print(key, type(value)) break ``` #### TALI with no transforms and no streaming, returning text as text, images as PIL images, videos as a list of PIL images, and audio as a sequence of floats ```python def tali_without_transforms_no_streaming( dataset_storage_path: pathlib.Path | str, ): if isinstance(dataset_storage_path, str): dataset_storage_path = pathlib.Path(dataset_storage_path) dataset = load_dataset_via_hub( dataset_storage_path, dataset_name="Antreas/TALI" )["train"] preprocessing_transform = TALIBaseTransform( cache_dir=dataset_storage_path / "cache", text_tokenizer=None, image_tokenizer=None, audio_tokenizer=None, video_tokenizer=None, config=TALIBaseTransformConfig( root_filepath=dataset_storage_path, modality_list=[ SubModalityTypes.youtube_content_video, SubModalityTypes.youtube_content_audio, SubModalityTypes.youtube_random_video_frame, SubModalityTypes.youtube_subtitle_text, SubModalityTypes.youtube_description_text, SubModalityTypes.youtube_title_text, SubModalityTypes.wikipedia_caption_image, SubModalityTypes.wikipedia_caption_text, SubModalityTypes.wikipedia_main_body_text, SubModalityTypes.wikipedia_title_text, ], video_frames_format=VideoFramesFormat.PIL, ), ) for sample in tqdm(dataset): sample = preprocessing_transform(sample) print(list(sample.keys())) for key, value in sample.items(): if hasattr(value, "shape"): print(key, value.shape) elif isinstance(value, torch.Tensor): print(key, value.shape) elif hasattr(value, "__len__"): print(key, len(value)) print(key, type(value)) break ``` #### TALI with default transforms and streaming ```python def tali_with_transforms_streaming( dataset_storage_path: pathlib.Path | str, ): if isinstance(dataset_storage_path, str): dataset_storage_path = pathlib.Path(dataset_storage_path) dataset = load_dataset_via_hub( dataset_storage_path, dataset_name="Antreas/TALI", streaming=True )["train"] ( image_transforms, text_transforms, audio_transforms, video_transforms, ) = default_transforms() preprocessing_transform = TALIBaseTransform( cache_dir=dataset_storage_path / "cache", text_tokenizer=text_transforms, image_tokenizer=image_transforms, audio_tokenizer=audio_transforms, video_tokenizer=video_transforms, config=TALIBaseTransformConfig( root_filepath=dataset_storage_path, modality_list=[ SubModalityTypes.youtube_content_video, SubModalityTypes.youtube_content_audio, SubModalityTypes.youtube_random_video_frame, SubModalityTypes.youtube_subtitle_text, SubModalityTypes.youtube_description_text, SubModalityTypes.youtube_title_text, SubModalityTypes.wikipedia_caption_image, SubModalityTypes.wikipedia_caption_text, SubModalityTypes.wikipedia_main_body_text, SubModalityTypes.wikipedia_title_text, ], video_frames_format=VideoFramesFormat.PIL, ), ) for sample in tqdm(dataset): sample = preprocessing_transform(sample) print(list(sample.keys())) for key, value in sample.items(): if hasattr(value, "shape"): print(key, value.shape) elif isinstance(value, torch.Tensor): print(key, value.shape) elif hasattr(value, "__len__"): print(key, len(value)) print(key, type(value)) break ``` #### TALI with no transforms and streaming, returning text as text, images as PIL images, videos as a list of PIL images, and audio as a sequence of floats ```python def tali_without_transforms_streaming( dataset_storage_path: pathlib.Path | str, ): if isinstance(dataset_storage_path, str): dataset_storage_path = pathlib.Path(dataset_storage_path) dataset = load_dataset_via_hub( dataset_storage_path, dataset_name="Antreas/TALI", streaming=True )["train"] preprocessing_transform = TALIBaseTransform( cache_dir=dataset_storage_path / "cache", text_tokenizer=None, image_tokenizer=None, audio_tokenizer=None, video_tokenizer=None, config=TALIBaseTransformConfig( root_filepath=dataset_storage_path, modality_list=[ SubModalityTypes.youtube_content_video, SubModalityTypes.youtube_content_audio, SubModalityTypes.youtube_random_video_frame, SubModalityTypes.youtube_subtitle_text, SubModalityTypes.youtube_description_text, SubModalityTypes.youtube_title_text, SubModalityTypes.wikipedia_caption_image, SubModalityTypes.wikipedia_caption_text, SubModalityTypes.wikipedia_main_body_text, SubModalityTypes.wikipedia_title_text, ], video_frames_format=VideoFramesFormat.PIL, ), ) for sample in tqdm(dataset): sample = preprocessing_transform(sample) print(list(sample.keys())) for key, value in sample.items(): if hasattr(value, "shape"): print(key, value.shape) elif isinstance(value, torch.Tensor): print(key, value.shape) elif hasattr(value, "__len__"): print(key, len(value)) print(key, type(value)) break ``` ### Dataset Statistics TBA ## Dataset Creation The TALI dataset was created by starting from the WiT dataset and using either the context_page_description or page_title as a source-query to search YouTube for video that were creative commons opted-in, and, not age restricted. The top 100 result titles were returned and compared with the source-query using the CLIP text embeddings of the largest CLIP model available. The top-1 title’s video based on the CLIP ranking was chosen and downloaded. The video was broken into 30-second segments and the top-10 segments for eachvideo were chosen based on the distance between the CLIP image embedding of the first image of each segment and the video’s title text. The image, audio, and subtitle frames were extracted from these segments. At sampling time, one of these 10 segments is randomly selected, and a 10-second segment is chosen out of the 30-second clip. The result is 200 video frames (spread throughout the 10-second segment), and 160000 audio frames (10 seconds). ## Dataset Use TALI is designed for use in a wide range of multimodal research tasks, including but not limited to: - Multimodal understanding and reasoning - Self-supervised learning - Multimodal alignment and translation - Multimodal summarization - Multimodal question answering ## Dataset Curators: Antreas Antoniou Citation Information: TBA Contributions: Thanks to all contributors including data curators, annotators, and software developers. [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

Cohere/wikipedia-2023-11-embed-multilingual-v3

Cohere

--- configs: - config_name: "ab" data_files: - split: train path: ab/* - config_name: "ace" data_files: - split: train path: ace/* - config_name: "ady" data_files: - split: train path: ady/* - config_name: "af" data_files: - split: train path: af/* - config_name: "als" data_files: - split: train path: als/* - config_name: "alt" data_files: - split: train path: alt/* - config_name: "am" data_files: - split: train path: am/* - config_name: "ami" data_files: - split: train path: ami/* - config_name: "an" data_files: - split: train path: an/* - config_name: "ang" data_files: - split: train path: ang/* - config_name: "anp" data_files: - split: train path: anp/* - config_name: "ar" data_files: - split: train path: ar/* - config_name: "arc" data_files: - split: train path: arc/* - config_name: "ary" data_files: - split: train path: ary/* - config_name: "arz" data_files: - split: train path: arz/* - config_name: "as" data_files: - split: train path: as/* - config_name: "ast" data_files: - split: train path: ast/* - config_name: "atj" data_files: - split: train path: atj/* - config_name: "av" data_files: - split: train path: av/* - config_name: "avk" data_files: - split: train path: avk/* - config_name: "awa" data_files: - split: train path: awa/* - config_name: "ay" data_files: - split: train path: ay/* - config_name: "az" data_files: - split: train path: az/* - config_name: "azb" data_files: - split: train path: azb/* - config_name: "ba" data_files: - split: train path: ba/* - config_name: "ban" data_files: - split: train path: ban/* - config_name: "bar" data_files: - split: train path: bar/* - config_name: "bat-smg" data_files: - split: train path: bat-smg/* - config_name: "bcl" data_files: - split: train path: bcl/* - config_name: "be" data_files: - split: train path: be/* - config_name: "be-x-old" data_files: - split: train path: be-x-old/* - config_name: "bg" data_files: - split: train path: bg/* - config_name: "bh" data_files: - split: train path: bh/* - config_name: "bi" data_files: - split: train path: bi/* - config_name: "bjn" data_files: - split: train path: bjn/* - config_name: "blk" data_files: - split: train path: blk/* - config_name: "bm" data_files: - split: train path: bm/* - config_name: "bn" data_files: - split: train path: bn/* - config_name: "bo" data_files: - split: train path: bo/* - config_name: "bpy" data_files: - split: train path: bpy/* - config_name: "br" data_files: - split: train path: br/* - config_name: "bs" data_files: - split: train path: bs/* - config_name: "bug" data_files: - split: train path: bug/* - config_name: "bxr" data_files: - split: train path: bxr/* - config_name: "ca" data_files: - split: train path: ca/* - config_name: "cbk-zam" data_files: - split: train path: cbk-zam/* - config_name: "cdo" data_files: - split: train path: cdo/* - config_name: "ce" data_files: - split: train path: ce/* - config_name: "ceb" data_files: - split: train path: ceb/* - config_name: "ch" data_files: - split: train path: ch/* - config_name: "chr" data_files: - split: train path: chr/* - config_name: "chy" data_files: - split: train path: chy/* - config_name: "ckb" data_files: - split: train path: ckb/* - config_name: "co" data_files: - split: train path: co/* - config_name: "cr" data_files: - split: train path: cr/* - config_name: "crh" data_files: - split: train path: crh/* - config_name: "cs" data_files: - split: train path: cs/* - config_name: "csb" data_files: - split: train path: csb/* - config_name: "cu" data_files: - split: train path: cu/* - config_name: "cv" data_files: - split: train path: cv/* - config_name: "cy" data_files: - split: train path: cy/* - config_name: "da" data_files: - split: train path: da/* - config_name: "dag" data_files: - split: train path: dag/* - config_name: "de" data_files: - split: train path: de/* - config_name: "din" data_files: - split: train path: din/* - config_name: "diq" data_files: - split: train path: diq/* - config_name: "dsb" data_files: - split: train path: dsb/* - config_name: "dty" data_files: - split: train path: dty/* - config_name: "dv" data_files: - split: train path: dv/* - config_name: "dz" data_files: - split: train path: dz/* - config_name: "ee" data_files: - split: train path: ee/* - config_name: "el" data_files: - split: train path: el/* - config_name: "eml" data_files: - split: train path: eml/* - config_name: "en" data_files: - split: train path: en/* - config_name: "eo" data_files: - split: train path: eo/* - config_name: "es" data_files: - split: train path: es/* - config_name: "et" data_files: - split: train path: et/* - config_name: "eu" data_files: - split: train path: eu/* - config_name: "ext" data_files: - split: train path: ext/* - config_name: "fa" data_files: - split: train path: fa/* - config_name: "fat" data_files: - split: train path: fat/* - config_name: "ff" data_files: - split: train path: ff/* - config_name: "fi" data_files: - split: train path: fi/* - config_name: "fiu-vro" data_files: - split: train path: fiu-vro/* - config_name: "fj" data_files: - split: train path: fj/* - config_name: "fo" data_files: - split: train path: fo/* - config_name: "fon" data_files: - split: train path: fon/* - config_name: "fr" data_files: - split: train path: fr/* - config_name: "frp" data_files: - split: train path: frp/* - config_name: "frr" data_files: - split: train path: frr/* - config_name: "fur" data_files: - split: train path: fur/* - config_name: "fy" data_files: - split: train path: fy/* - config_name: "ga" data_files: - split: train path: ga/* - config_name: "gag" data_files: - split: train path: gag/* - config_name: "gan" data_files: - split: train path: gan/* - config_name: "gcr" data_files: - split: train path: gcr/* - config_name: "gd" data_files: - split: train path: gd/* - config_name: "gl" data_files: - split: train path: gl/* - config_name: "glk" data_files: - split: train path: glk/* - config_name: "gn" data_files: - split: train path: gn/* - config_name: "gom" data_files: - split: train path: gom/* - config_name: "gor" data_files: - split: train path: gor/* - config_name: "got" data_files: - split: train path: got/* - config_name: "gpe" data_files: - split: train path: gpe/* - config_name: "gu" data_files: - split: train path: gu/* - config_name: "guc" data_files: - split: train path: guc/* - config_name: "gur" data_files: - split: train path: gur/* - config_name: "guw" data_files: - split: train path: guw/* - config_name: "gv" data_files: - split: train path: gv/* - config_name: "ha" data_files: - split: train path: ha/* - config_name: "hak" data_files: - split: train path: hak/* - config_name: "haw" data_files: - split: train path: haw/* - config_name: "he" data_files: - split: train path: he/* - config_name: "hi" data_files: - split: train path: hi/* - config_name: "hif" data_files: - split: train path: hif/* - config_name: "hr" data_files: - split: train path: hr/* - config_name: "hsb" data_files: - split: train path: hsb/* - config_name: "ht" data_files: - split: train path: ht/* - config_name: "hu" data_files: - split: train path: hu/* - config_name: "hy" data_files: - split: train path: hy/* - config_name: "hyw" data_files: - split: train path: hyw/* - config_name: "ia" data_files: - split: train path: ia/* - config_name: "id" data_files: - split: train path: id/* - config_name: "ie" data_files: - split: train path: ie/* - config_name: "ig" data_files: - split: train path: ig/* - config_name: "ik" data_files: - split: train path: ik/* - config_name: "ilo" data_files: - split: train path: ilo/* - config_name: "inh" data_files: - split: train path: inh/* - config_name: "io" data_files: - split: train path: io/* - config_name: "is" data_files: - split: train path: is/* - config_name: "it" data_files: - split: train path: it/* - config_name: "iu" data_files: - split: train path: iu/* - config_name: "ja" data_files: - split: train path: ja/* - config_name: "jam" data_files: - split: train path: jam/* - config_name: "jbo" data_files: - split: train path: jbo/* - config_name: "jv" data_files: - split: train path: jv/* - config_name: "ka" data_files: - split: train path: ka/* - config_name: "kaa" data_files: - split: train path: kaa/* - config_name: "kab" data_files: - split: train path: kab/* - config_name: "kbd" data_files: - split: train path: kbd/* - config_name: "kbp" data_files: - split: train path: kbp/* - config_name: "kcg" data_files: - split: train path: kcg/* - config_name: "kg" data_files: - split: train path: kg/* - config_name: "ki" data_files: - split: train path: ki/* - config_name: "kk" data_files: - split: train path: kk/* - config_name: "kl" data_files: - split: train path: kl/* - config_name: "km" data_files: - split: train path: km/* - config_name: "kn" data_files: - split: train path: kn/* - config_name: "ko" data_files: - split: train path: ko/* - config_name: "koi" data_files: - split: train path: koi/* - config_name: "krc" data_files: - split: train path: krc/* - config_name: "ks" data_files: - split: train path: ks/* - config_name: "ksh" data_files: - split: train path: ksh/* - config_name: "ku" data_files: - split: train path: ku/* - config_name: "kv" data_files: - split: train path: kv/* - config_name: "kw" data_files: - split: train path: kw/* - config_name: "ky" data_files: - split: train path: ky/* - config_name: "la" data_files: - split: train path: la/* - config_name: "lad" data_files: - split: train path: lad/* - config_name: "lb" data_files: - split: train path: lb/* - config_name: "lbe" data_files: - split: train path: lbe/* - config_name: "lez" data_files: - split: train path: lez/* - config_name: "lfn" data_files: - split: train path: lfn/* - config_name: "lg" data_files: - split: train path: lg/* - config_name: "li" data_files: - split: train path: li/* - config_name: "lij" data_files: - split: train path: lij/* - config_name: "lld" data_files: - split: train path: lld/* - config_name: "lmo" data_files: - split: train path: lmo/* - config_name: "ln" data_files: - split: train path: ln/* - config_name: "lo" data_files: - split: train path: lo/* - config_name: "lt" data_files: - split: train path: lt/* - config_name: "ltg" data_files: - split: train path: ltg/* - config_name: "lv" data_files: - split: train path: lv/* - config_name: "mad" data_files: - split: train path: mad/* - config_name: "mai" data_files: - split: train path: mai/* - config_name: "map-bms" data_files: - split: train path: map-bms/* - config_name: "mdf" data_files: - split: train path: mdf/* - config_name: "mg" data_files: - split: train path: mg/* - config_name: "mhr" data_files: - split: train path: mhr/* - config_name: "mi" data_files: - split: train path: mi/* - config_name: "min" data_files: - split: train path: min/* - config_name: "mk" data_files: - split: train path: mk/* - config_name: "ml" data_files: - split: train path: ml/* - config_name: "mn" data_files: - split: train path: mn/* - config_name: "mni" data_files: - split: train path: mni/* - config_name: "mnw" data_files: - split: train path: mnw/* - config_name: "mr" data_files: - split: train path: mr/* - config_name: "mrj" data_files: - split: train path: mrj/* - config_name: "ms" data_files: - split: train path: ms/* - config_name: "mt" data_files: - split: train path: mt/* - config_name: "mwl" data_files: - split: train path: mwl/* - config_name: "my" data_files: - split: train path: my/* - config_name: "myv" data_files: - split: train path: myv/* - config_name: "mzn" data_files: - split: train path: mzn/* - config_name: "nah" data_files: - split: train path: nah/* - config_name: "nap" data_files: - split: train path: nap/* - config_name: "nds" data_files: - split: train path: nds/* - config_name: "nds-nl" data_files: - split: train path: nds-nl/* - config_name: "ne" data_files: - split: train path: ne/* - config_name: "new" data_files: - split: train path: new/* - config_name: "nia" data_files: - split: train path: nia/* - config_name: "nl" data_files: - split: train path: nl/* - config_name: "nn" data_files: - split: train path: nn/* - config_name: "no" data_files: - split: train path: no/* - config_name: "nov" data_files: - split: train path: nov/* - config_name: "nqo" data_files: - split: train path: nqo/* - config_name: "nrm" data_files: - split: train path: nrm/* - config_name: "nso" data_files: - split: train path: nso/* - config_name: "nv" data_files: - split: train path: nv/* - config_name: "ny" data_files: - split: train path: ny/* - config_name: "oc" data_files: - split: train path: oc/* - config_name: "olo" data_files: - split: train path: olo/* - config_name: "om" data_files: - split: train path: om/* - config_name: "or" data_files: - split: train path: or/* - config_name: "os" data_files: - split: train path: os/* - config_name: "pa" data_files: - split: train path: pa/* - config_name: "pag" data_files: - split: train path: pag/* - config_name: "pam" data_files: - split: train path: pam/* - config_name: "pap" data_files: - split: train path: pap/* - config_name: "pcd" data_files: - split: train path: pcd/* - config_name: "pcm" data_files: - split: train path: pcm/* - config_name: "pdc" data_files: - split: train path: pdc/* - config_name: "pfl" data_files: - split: train path: pfl/* - config_name: "pi" data_files: - split: train path: pi/* - config_name: "pih" data_files: - split: train path: pih/* - config_name: "pl" data_files: - split: train path: pl/* - config_name: "pms" data_files: - split: train path: pms/* - config_name: "pnb" data_files: - split: train path: pnb/* - config_name: "pnt" data_files: - split: train path: pnt/* - config_name: "ps" data_files: - split: train path: ps/* - config_name: "pt" data_files: - split: train path: pt/* - config_name: "pwn" data_files: - split: train path: pwn/* - config_name: "qu" data_files: - split: train path: qu/* - config_name: "rm" data_files: - split: train path: rm/* - config_name: "rmy" data_files: - split: train path: rmy/* - config_name: "rn" data_files: - split: train path: rn/* - config_name: "ro" data_files: - split: train path: ro/* - config_name: "roa-rup" data_files: - split: train path: roa-rup/* - config_name: "roa-tara" data_files: - split: train path: roa-tara/* - config_name: "ru" data_files: - split: train path: ru/* - config_name: "rue" data_files: - split: train path: rue/* - config_name: "rw" data_files: - split: train path: rw/* - config_name: "sa" data_files: - split: train path: sa/* - config_name: "sah" data_files: - split: train path: sah/* - config_name: "sat" data_files: - split: train path: sat/* - config_name: "sc" data_files: - split: train path: sc/* - config_name: "scn" data_files: - split: train path: scn/* - config_name: "sco" data_files: - split: train path: sco/* - config_name: "sd" data_files: - split: train path: sd/* - config_name: "se" data_files: - split: train path: se/* - config_name: "sg" data_files: - split: train path: sg/* - config_name: "sh" data_files: - split: train path: sh/* - config_name: "shi" data_files: - split: train path: shi/* - config_name: "shn" data_files: - split: train path: shn/* - config_name: "si" data_files: - split: train path: si/* - config_name: "simple" data_files: - split: train path: simple/* - config_name: "sk" data_files: - split: train path: sk/* - config_name: "skr" data_files: - split: train path: skr/* - config_name: "sl" data_files: - split: train path: sl/* - config_name: "sm" data_files: - split: train path: sm/* - config_name: "smn" data_files: - split: train path: smn/* - config_name: "sn" data_files: - split: train path: sn/* - config_name: "so" data_files: - split: train path: so/* - config_name: "sq" data_files: - split: train path: sq/* - config_name: "sr" data_files: - split: train path: sr/* - config_name: "srn" data_files: - split: train path: srn/* - config_name: "ss" data_files: - split: train path: ss/* - config_name: "st" data_files: - split: train path: st/* - config_name: "stq" data_files: - split: train path: stq/* - config_name: "su" data_files: - split: train path: su/* - config_name: "sv" data_files: - split: train path: sv/* - config_name: "sw" data_files: - split: train path: sw/* - config_name: "szl" data_files: - split: train path: szl/* - config_name: "szy" data_files: - split: train path: szy/* - config_name: "ta" data_files: - split: train path: ta/* - config_name: "tay" data_files: - split: train path: tay/* - config_name: "tcy" data_files: - split: train path: tcy/* - config_name: "te" data_files: - split: train path: te/* - config_name: "tet" data_files: - split: train path: tet/* - config_name: "tg" data_files: - split: train path: tg/* - config_name: "th" data_files: - split: train path: th/* - config_name: "ti" data_files: - split: train path: ti/* - config_name: "tk" data_files: - split: train path: tk/* - config_name: "tl" data_files: - split: train path: tl/* - config_name: "tly" data_files: - split: train path: tly/* - config_name: "tn" data_files: - split: train path: tn/* - config_name: "to" data_files: - split: train path: to/* - config_name: "tpi" data_files: - split: train path: tpi/* - config_name: "tr" data_files: - split: train path: tr/* - config_name: "trv" data_files: - split: train path: trv/* - config_name: "ts" data_files: - split: train path: ts/* - config_name: "tt" data_files: - split: train path: tt/* - config_name: "tum" data_files: - split: train path: tum/* - config_name: "tw" data_files: - split: train path: tw/* - config_name: "ty" data_files: - split: train path: ty/* - config_name: "tyv" data_files: - split: train path: tyv/* - config_name: "udm" data_files: - split: train path: udm/* - config_name: "ug" data_files: - split: train path: ug/* - config_name: "uk" data_files: - split: train path: uk/* - config_name: "ur" data_files: - split: train path: ur/* - config_name: "uz" data_files: - split: train path: uz/* - config_name: "ve" data_files: - split: train path: ve/* - config_name: "vec" data_files: - split: train path: vec/* - config_name: "vep" data_files: - split: train path: vep/* - config_name: "vi" data_files: - split: train path: vi/* - config_name: "vls" data_files: - split: train path: vls/* - config_name: "vo" data_files: - split: train path: vo/* - config_name: "wa" data_files: - split: train path: wa/* - config_name: "war" data_files: - split: train path: war/* - config_name: "wo" data_files: - split: train path: wo/* - config_name: "wuu" data_files: - split: train path: wuu/* - config_name: "xal" data_files: - split: train path: xal/* - config_name: "xh" data_files: - split: train path: xh/* - config_name: "xmf" data_files: - split: train path: xmf/* - config_name: "yi" data_files: - split: train path: yi/* - config_name: "yo" data_files: - split: train path: yo/* - config_name: "za" data_files: - split: train path: za/* - config_name: "zea" data_files: - split: train path: zea/* - config_name: "zh" data_files: - split: train path: zh/* - config_name: "zh-classical" data_files: - split: train path: zh-classical/* - config_name: "zh-min-nan" data_files: - split: train path: zh-min-nan/* - config_name: "zh-yue" data_files: - split: train path: zh-yue/* - config_name: "zu" data_files: - split: train path: zu/* --- # Multilingual Embeddings for Wikipedia in 300+ Languages This dataset contains the [wikimedia/wikipedia](https://huggingface.co/datasets/wikimedia/wikipedia) dataset dump from 2023-11-01 from Wikipedia in all 300+ languages. The individual articles have been chunked and embedded with the state-of-the-art multilingual [Cohere Embed V3 embedding model](https://txt.cohere.com/introducing-embed-v3/). This enables an easy way to semantically search across all of Wikipedia or to use it as a knowledge source for your RAG application. In total is it close to 250M paragraphs / embeddings. You can also use the model to perform cross-lingual search: Enter your search query in any language and get the most relevant results back. ## Loading the dataset ### Loading the document embeddings You can either load the dataset like this: ```python from datasets import load_dataset lang = "simple" #Use the Simple English Wikipedia subset docs = load_dataset("Cohere/wikipedia-2023-11-embed-multilingual-v3", lang, split="train") ``` Or you can also stream it without downloading it before: ```python from datasets import load_dataset lang = "simple" #Use the Simple English Wikipedia subset docs = load_dataset("Cohere/wikipedia-2023-11-embed-multilingual-v3", lang, split="train", streaming=True) for doc in docs: doc_id = doc['_id'] title = doc['title'] text = doc['text'] emb = doc['emb'] ``` Note, depending on the language, the download can be quite large. ## Search A full search example (on the first 1,000 paragraphs): ```python #Run: pip install cohere datasets numpy from datasets import load_dataset import numpy as np import cohere co = cohere.Client("YOUR_COHERE_API_KEY") # Add your cohere API key from www.cohere.com lang = "simple" top_k = 3 #Load at max 1000 chunks + embeddings max_docs = 1000 docs_stream = load_dataset(f"Cohere/wikipedia-2023-11-embed-multilingual-v3", lang, split="train", streaming=True) docs = [] doc_embeddings = [] for doc in docs_stream: docs.append(doc) doc_embeddings.append(doc['emb']) if len(docs) >= max_docs: break doc_embeddings = np.asarray(doc_embeddings) query = 'Who was Alan Turing' response = co.embed(texts=[query], model='embed-multilingual-v3.0', input_type="search_query") query_embedding = response.embeddings query_embedding = np.asarray(query_embedding) # Compute dot score between query embedding and document embeddings dot_scores = np.matmul(query_embedding, doc_embeddings.transpose())[0] top_k_hits = np.argpartition(dot_scores, -top_k)[-top_k:].tolist() # Sort top_k_hits by dot score top_k_hits.sort(key=lambda x: dot_scores[x], reverse=True) # Print results print("Query:", query) for doc_id in top_k_hits: print(docs[doc_id]['title']) print(docs[doc_id]['text']) print(docs[doc_id]['url'], "\n") ``` ## Overview The following table contains all language codes together with the total numbers of passages. | Language | #Docs | |---|:---:| | en | 41,488,110 | | de | 20,772,081 | | fr | 17,813,768 | | ru | 13,734,543 | | es | 12,905,284 | | it | 10,462,162 | | ceb | 9,818,657 | | uk | 6,901,192 | | ja | 6,626,537 | | nl | 6,101,353 | | pl | 5,973,650 | | pt | 5,637,930 | | sv | 4,911,480 | | ca | 4,156,889 | | ar | 3,691,451 | | cs | 3,118,524 | | he | 2,948,882 | | hu | 2,924,609 | | vi | 2,835,049 | | zh | 2,775,260 | | fi | 2,427,097 | | id | 2,358,335 | | no | 2,211,270 | | sr | 2,154,631 | | fa | 2,073,154 | | tr | 1,775,036 | | ro | 1,770,527 | | el | 1,599,770 | | ko | 1,513,291 | | bg | 1,455,765 | | hy | 1,386,140 | | eu | 1,327,579 | | da | 1,224,982 | | eo | 1,216,706 | | war | 1,185,097 | | sh | 1,139,309 | | tt | 1,119,546 | | arz | 1,089,164 | | gl | 1,056,990 | | et | 1,054,770 | | ce | 1,013,217 | | ast | 1,010,445 | | sl | 984,855 | | hr | 910,923 | | sk | 874,014 | | ms | 869,579 | | be | 857,033 | | th | 839,712 | | az | 817,631 | | uz | 811,028 | | mk | 784,576 | | lt | 770,069 | | bn | 767,965 | | cy | 762,338 | | ta | 685,975 | | simple | 646,424 | | te | 634,778 | | kk | 627,085 | | ka | 595,401 | | hi | 541,822 | | nn | 530,590 | | lv | 484,957 | | af | 461,674 | | ba | 434,939 | | ur | 434,269 | | bs | 396,692 | | sq | 388,788 | | ml | 384,795 | | min | 373,156 | | la | 340,521 | | pnb | 335,958 | | be-x-old | 314,600 | | kn | 309,085 | | azb | 294,248 | | oc | 283,297 | | zh-min-nan | 278,547 | | fy | 248,075 | | my | 241,025 | | lb | 216,558 | | ky | 216,344 | | als | 206,387 | | mr | 203,479 | | br | 200,486 | | pa | 188,091 | | is | 177,272 | | mg | 171,947 | | sw | 171,650 | | ha | 167,807 | | tl | 166,907 | | nds | 166,019 | | an | 143,163 | | jv | 142,104 | | ps | 138,240 | | ig | 132,250 | | new | 128,696 | | tg | 128,237 | | ga | 125,456 | | lld | 125,094 | | su | 124,390 | | cv | 122,671 | | ckb | 120,886 | | si | 119,223 | | mn | 114,878 | | lmo | 103,836 | | io | 101,713 | | gu | 99,450 | | vec | 95,072 | | zh-yue | 89,145 | | bar | 88,238 | | sco | 83,906 | | ne | 83,598 | | ku | 82,935 | | hyw | 82,343 | | pms | 77,834 | | as | 76,093 | | km | 74,177 | | sah | 71,599 | | li | 69,267 | | or | 65,510 | | mt | 64,038 | | szl | 56,836 | | yi | 55,375 | | ht | 55,079 | | dag | 53,343 | | sa | 51,735 | | nv | 49,355 | | bpy | 47,757 | | vo | 47,375 | | ug | 44,764 | | sat | 43,500 | | ia | 42,012 | | bo | 41,438 | | mwl | 41,273 | | sd | 40,395 | | bcl | 39,967 | | mnw | 39,578 | | hsb | 39,560 | | avk | 39,001 | | scn | 38,359 | | rm | 37,436 | | diq | 34,743 | | vep | 33,654 | | xmf | 33,238 | | ban | 32,320 | | wa | 32,132 | | ilo | 31,046 | | nds-nl | 30,918 | | qu | 30,529 | | so | 29,936 | | mhr | 29,619 | | vls | 29,227 | | sc | 28,977 | | fo | 28,809 | | gd | 28,149 | | rw | 28,037 | | gom | 27,792 | | yo | 27,789 | | tum | 26,743 | | wuu | 26,532 | | frr | 26,010 | | sn | 25,941 | | tk | 24,269 | | blk | 24,194 | | mzn | 23,837 | | co | 23,065 | | szy | 22,854 | | am | 22,467 | | shn | 22,432 | | skr | 21,081 | | lfn | 20,781 | | tyv | 20,762 | | lij | 20,553 | | ie | 19,994 | | rue | 19,916 | | crh | 19,016 | | gor | 18,146 | | ary | 17,463 | | dv | 16,941 | | lg | 16,751 | | roa-tara | 16,572 | | bjn | 16,429 | | tw | 16,304 | | bh | 15,938 | | pam | 15,134 | | os | 15,096 | | myv | 15,062 | | gn | 14,983 | | lez | 14,152 | | mai | 13,806 | | kv | 13,534 | | pcd | 13,057 | | zh-classical | 12,791 | | zea | 12,528 | | lo | 12,525 | | gv | 12,074 | | stq | 11,890 | | zu | 11,680 | | smn | 11,672 | | kw | 11,539 | | bat-smg | 11,240 | | hif | 11,215 | | ext | 10,967 | | ace | 10,821 | | trv | 10,546 | | ami | 10,538 | | tcy | 10,531 | | lad | 10,386 | | alt | 10,256 | | pap | 10,187 | | kab | 10,179 | | fur | 10,148 | | nap | 10,079 | | mrj | 9,771 | | kaa | 9,548 | | nqo | 9,153 | | glk | 9,120 | | pfl | 8,790 | | fiu-vro | 8,757 | | nso | 8,635 | | jbo | 8,577 | | bxr | 8,549 | | wo | 8,549 | | olo | 8,530 | | map-bms | 8,393 | | ksh | 8,226 | | csb | 8,085 | | av | 7,873 | | mni | 7,740 | | udm | 7,730 | | mi | 7,643 | | kbp | 7,616 | | dsb | 7,536 | | frp | 7,294 | | om | 7,045 | | ang | 7,023 | | hak | 6,866 | | gur | 6,761 | | se | 6,733 | | anp | 6,704 | | tay | 6,434 | | mdf | 6,351 | | gcr | 6,347 | | koi | 6,300 | | krc | 6,293 | | ay | 5,985 | | cdo | 5,917 | | nrm | 5,786 | | xh | 5,756 | | tn | 5,712 | | tly | 5,598 | | shi | 5,179 | | pcm | 5,076 | | fat | 4,968 | | nia | 4,795 | | dty | 4,728 | | kbd | 4,667 | | gpe | 4,289 | | cbk-zam | 4,224 | | ff | 4,166 | | dz | 4,117 | | guw | 3,982 | | eml | 3,979 | | ln | 3,774 | | inh | 3,768 | | nah | 3,720 | | ab | 3,465 | | ks | 3,255 | | mad | 3,236 | | haw | 3,227 | | gag | 3,076 | | tet | 3,030 | | ny | 2,933 | | pag | 2,727 | | guc | 2,454 | | roa-rup | 2,409 | | jam | 2,387 | | awa | 2,242 | | pdc | 2,239 | | to | 2,165 | | za | 2,132 | | st | 2,051 | | ltg | 2,005 | | atj | 1,967 | | nov | 1,916 | | ss | 1,904 | | pwn | 1,881 | | ee | 1,819 | | sm | 1,659 | | ts | 1,645 | | gan | 1,626 | | xal | 1,619 | | kcg | 1,555 | | cu | 1,477 | | srn | 1,395 | | got | 1,280 | | fon | 1,247 | | din | 1,214 | | arc | 1,167 | | fj | 1,164 | | rmy | 1,113 | | ady | 1,040 | | rn | 1,033 | | bm | 1,017 | | tpi | 957 | | ve | 919 | | ki | 798 | | pnt | 796 | | chr | 788 | | kl | 770 | | lbe | 766 | | bi | 718 | | ti | 706 | | kg | 609 | | pih | 606 | | ch | 513 | | bug | 429 | | ty | 297 | | ik | 275 | | iu | 263 | | pi | 260 | | sg | 204 | | chy | 57 | | cr | 41 | | Total | 247,154,006 |

FreedomIntelligence/medical-o1-reasoning-SFT

FreedomIntelligence

--- license: apache-2.0 task_categories: - question-answering - text-generation language: - en - zh tags: - medical - biology configs: - config_name: en data_files: medical_o1_sft.json - config_name: zh data_files: medical_o1_sft_Chinese.json --- ## News [2025/02/22] We released the [distilled dataset from Deepseek-R1](https://huggingface.co/datasets/FreedomIntelligence/Medical-R1-Distill-Data) based on medical verifiable problems. You can use it to initialize your models with the reasoning chain from `Deepseek-R1`. [2024/12/25] We open-sourced the medical reasoning dataset for SFT, built on medical verifiable problems and an LLM verifier. ## Introduction This dataset is used to fine-tune HuatuoGPT-o1, a medical LLM designed for advanced medical reasoning. This dataset is constructed using GPT-4o, which searches for solutions to [verifiable medical problems](https://huggingface.co/datasets/FreedomIntelligence/medical-o1-verifiable-problem) and validates them through a medical verifier. For details, see our [paper](https://arxiv.org/pdf/2412.18925) and [GitHub repository](https://github.com/FreedomIntelligence/HuatuoGPT-o1). ## Citation If you find our data useful, please consider citing our work! ``` @misc{chen2024huatuogpto1medicalcomplexreasoning, title={HuatuoGPT-o1, Towards Medical Complex Reasoning with LLMs}, author={Junying Chen and Zhenyang Cai and Ke Ji and Xidong Wang and Wanlong Liu and Rongsheng Wang and Jianye Hou and Benyou Wang}, year={2024}, eprint={2412.18925}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2412.18925}, } ```

EPFL-CVLAB-SPACECRAFT/SwissCube

EPFL-CVLAB-SPACECRAFT

--- license: mit ---

asahi417/seamless-align-deA-enA.speaker-embedding.xlsr-2b

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: deA.id dtype: string - name: deA.laser_score dtype: float64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: deA.audio.speaker_embedding sequence: float32 - name: deA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 16496072358 num_examples: 2064 download_size: 16544774466 dataset_size: 16496072358 - config_name: subset_10 features: - name: line_no dtype: int64 - name: deA.id dtype: string - name: deA.laser_score dtype: float64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: deA.audio.speaker_embedding sequence: float32 - name: deA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 16105175291 num_examples: 2106 download_size: 16153856631 dataset_size: 16105175291 - config_name: subset_100 features: - name: line_no dtype: int64 - name: deA.id dtype: string - name: deA.laser_score dtype: float64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: deA.audio.speaker_embedding sequence: float32 - name: deA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11700093808 num_examples: 1944 download_size: 11740547200 dataset_size: 11700093808 - config_name: subset_101 features: - name: line_no dtype: int64 - name: deA.id dtype: string - name: deA.laser_score dtype: float64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: deA.audio.speaker_embedding sequence: float32 - 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config_name: subset_199 data_files: - split: train path: subset_199/train-* - config_name: subset_2 data_files: - split: train path: subset_2/train-* - config_name: subset_20 data_files: - split: train path: subset_20/train-* - config_name: subset_200 data_files: - split: train path: subset_200/train-* - config_name: subset_201 data_files: - split: train path: subset_201/train-* - config_name: subset_202 data_files: - split: train path: subset_202/train-* - config_name: subset_203 data_files: - split: train path: subset_203/train-* - config_name: subset_204 data_files: - split: train path: subset_204/train-* - config_name: subset_205 data_files: - split: train path: subset_205/train-* - config_name: subset_206 data_files: - split: train path: subset_206/train-* - config_name: subset_207 data_files: - split: train path: subset_207/train-* - config_name: subset_208 data_files: - split: train path: subset_208/train-* - config_name: subset_209 data_files: - split: train path: subset_209/train-* - config_name: subset_21 data_files: - split: train path: subset_21/train-* - config_name: subset_210 data_files: - split: train path: subset_210/train-* - config_name: subset_211 data_files: - split: train path: subset_211/train-* - config_name: subset_212 data_files: - split: train path: subset_212/train-* - config_name: subset_213 data_files: - split: train path: subset_213/train-* - config_name: subset_214 data_files: - split: train path: subset_214/train-* - config_name: subset_215 data_files: - split: train path: subset_215/train-* - config_name: subset_216 data_files: - split: train path: subset_216/train-* - config_name: subset_217 data_files: - split: train path: subset_217/train-* - config_name: subset_218 data_files: - split: train path: subset_218/train-* - config_name: subset_219 data_files: - split: train path: subset_219/train-* - config_name: subset_22 data_files: - split: train path: subset_22/train-* - config_name: subset_220 data_files: - split: train path: subset_220/train-* - config_name: subset_221 data_files: - split: train path: subset_221/train-* - config_name: subset_222 data_files: - split: train path: subset_222/train-* - config_name: subset_223 data_files: - split: train path: subset_223/train-* - config_name: subset_224 data_files: - split: train path: subset_224/train-* - config_name: subset_225 data_files: - split: train path: subset_225/train-* - config_name: subset_226 data_files: - split: train path: subset_226/train-* - config_name: subset_227 data_files: - split: train path: subset_227/train-* - config_name: subset_228 data_files: - split: train path: subset_228/train-* - config_name: subset_229 data_files: - split: train path: subset_229/train-* - config_name: subset_23 data_files: - split: train path: subset_23/train-* - config_name: subset_230 data_files: - split: train path: subset_230/train-* - config_name: subset_231 data_files: - split: train path: subset_231/train-* - config_name: subset_232 data_files: - split: train path: subset_232/train-* - config_name: subset_233 data_files: - split: train path: subset_233/train-* - config_name: subset_234 data_files: - split: train path: subset_234/train-* - config_name: subset_235 data_files: - split: train path: subset_235/train-* - config_name: subset_236 data_files: - split: train path: subset_236/train-* - config_name: subset_237 data_files: - split: train path: subset_237/train-* - config_name: subset_238 data_files: - split: train path: subset_238/train-* - config_name: subset_239 data_files: - split: train path: subset_239/train-* - config_name: subset_24 data_files: - split: train path: subset_24/train-* - config_name: subset_240 data_files: - split: train path: subset_240/train-* - config_name: subset_241 data_files: - split: train path: subset_241/train-* - config_name: subset_242 data_files: - split: train path: subset_242/train-* - config_name: subset_243 data_files: - split: train path: subset_243/train-* - config_name: subset_244 data_files: - split: train path: subset_244/train-* - config_name: subset_245 data_files: - split: train path: subset_245/train-* - config_name: subset_246 data_files: - split: train path: subset_246/train-* - config_name: subset_247 data_files: - split: train path: subset_247/train-* - config_name: subset_248 data_files: - split: train path: subset_248/train-* - config_name: subset_249 data_files: - split: train path: subset_249/train-* - config_name: subset_25 data_files: - split: train path: subset_25/train-* - config_name: subset_250 data_files: - split: train path: subset_250/train-* - config_name: subset_251 data_files: - split: train path: subset_251/train-* - config_name: subset_252 data_files: - split: train path: subset_252/train-* - config_name: subset_253 data_files: - split: train path: subset_253/train-* - config_name: subset_254 data_files: - split: train path: subset_254/train-* - config_name: subset_255 data_files: - split: train path: subset_255/train-* - config_name: subset_256 data_files: - split: train path: subset_256/train-* - config_name: subset_257 data_files: - split: train path: subset_257/train-* - config_name: subset_258 data_files: - split: train path: subset_258/train-* - config_name: subset_259 data_files: - split: train path: subset_259/train-* - config_name: subset_26 data_files: - split: train path: subset_26/train-* - config_name: subset_260 data_files: - split: train path: subset_260/train-* - config_name: subset_261 data_files: - split: train path: subset_261/train-* - config_name: subset_262 data_files: - split: train path: subset_262/train-* - config_name: subset_263 data_files: - split: train path: subset_263/train-* - config_name: subset_264 data_files: - split: train path: subset_264/train-* - config_name: subset_265 data_files: - split: train path: subset_265/train-* - config_name: subset_266 data_files: - split: train path: subset_266/train-* - config_name: subset_267 data_files: - split: train path: subset_267/train-* - config_name: subset_268 data_files: - split: train path: subset_268/train-* - config_name: subset_269 data_files: - split: train path: subset_269/train-* - config_name: subset_27 data_files: - split: train path: subset_27/train-* - config_name: subset_270 data_files: - split: train path: subset_270/train-* - config_name: subset_271 data_files: - split: train path: subset_271/train-* - config_name: subset_272 data_files: - split: train path: subset_272/train-* - config_name: subset_273 data_files: - split: train path: subset_273/train-* - config_name: subset_274 data_files: - split: train path: subset_274/train-* - config_name: subset_275 data_files: - split: train path: subset_275/train-* - config_name: subset_276 data_files: - split: train path: subset_276/train-* - config_name: subset_277 data_files: - split: train path: subset_277/train-* - config_name: subset_278 data_files: - split: train path: subset_278/train-* - config_name: subset_279 data_files: - split: train path: subset_279/train-* - config_name: subset_28 data_files: - split: train path: subset_28/train-* - config_name: subset_280 data_files: - split: train path: subset_280/train-* - config_name: subset_281 data_files: - split: train path: subset_281/train-* - config_name: subset_282 data_files: - split: train path: subset_282/train-* - config_name: subset_283 data_files: - split: train path: subset_283/train-* - config_name: subset_284 data_files: - split: train path: subset_284/train-* - config_name: subset_285 data_files: - split: train path: subset_285/train-* - config_name: subset_286 data_files: - split: train path: subset_286/train-* - config_name: subset_287 data_files: - split: train path: subset_287/train-* - config_name: subset_288 data_files: - split: train path: subset_288/train-* - config_name: subset_289 data_files: - split: train path: subset_289/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_290 data_files: - split: train path: subset_290/train-* - config_name: subset_291 data_files: - split: train path: subset_291/train-* - config_name: subset_292 data_files: - split: train path: subset_292/train-* - config_name: subset_293 data_files: - split: train path: subset_293/train-* - config_name: subset_294 data_files: - split: train path: subset_294/train-* - config_name: subset_295 data_files: - split: train path: subset_295/train-* - config_name: subset_296 data_files: - split: train path: subset_296/train-* - config_name: subset_297 data_files: - split: train path: subset_297/train-* - config_name: subset_298 data_files: - split: train path: subset_298/train-* - config_name: subset_299 data_files: - split: train path: subset_299/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_300 data_files: - split: train path: subset_300/train-* - config_name: subset_301 data_files: - split: train path: subset_301/train-* - config_name: subset_302 data_files: - split: train path: subset_302/train-* - config_name: subset_303 data_files: - split: train path: subset_303/train-* - config_name: subset_304 data_files: - split: train path: subset_304/train-* - config_name: subset_305 data_files: - split: train path: subset_305/train-* - config_name: subset_306 data_files: - split: train path: subset_306/train-* - config_name: subset_307 data_files: - split: train path: subset_307/train-* - config_name: subset_308 data_files: - split: train path: subset_308/train-* - config_name: subset_309 data_files: - split: train path: subset_309/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_310 data_files: - split: train path: subset_310/train-* - config_name: subset_311 data_files: - split: train path: subset_311/train-* - config_name: subset_312 data_files: - split: train path: subset_312/train-* - config_name: subset_313 data_files: - split: train path: subset_313/train-* - config_name: subset_314 data_files: - split: train path: subset_314/train-* - config_name: subset_315 data_files: - split: train path: subset_315/train-* - config_name: subset_316 data_files: - split: train path: subset_316/train-* - config_name: subset_317 data_files: - split: train path: subset_317/train-* - config_name: subset_318 data_files: - split: train path: subset_318/train-* - config_name: subset_319 data_files: - split: train path: subset_319/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_320 data_files: - split: train path: subset_320/train-* - config_name: subset_321 data_files: - split: train path: subset_321/train-* - config_name: subset_322 data_files: - split: train path: subset_322/train-* - config_name: subset_323 data_files: - split: train path: subset_323/train-* - config_name: subset_324 data_files: - split: train path: subset_324/train-* - config_name: subset_325 data_files: - split: train path: subset_325/train-* - config_name: subset_326 data_files: - split: train path: subset_326/train-* - config_name: subset_327 data_files: - split: train path: subset_327/train-* - config_name: subset_328 data_files: - split: train path: subset_328/train-* - config_name: subset_329 data_files: - split: train path: subset_329/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_330 data_files: - split: train path: subset_330/train-* - config_name: subset_331 data_files: - split: train path: subset_331/train-* - config_name: subset_332 data_files: - split: train path: subset_332/train-* - config_name: subset_333 data_files: - split: train path: subset_333/train-* - config_name: subset_334 data_files: - split: train path: subset_334/train-* - config_name: subset_335 data_files: - split: train path: subset_335/train-* - config_name: subset_336 data_files: - split: train path: subset_336/train-* - config_name: subset_337 data_files: - split: train path: subset_337/train-* - config_name: subset_338 data_files: - split: train path: subset_338/train-* - config_name: subset_339 data_files: - split: train path: subset_339/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_340 data_files: - split: train path: subset_340/train-* - config_name: subset_341 data_files: - split: train path: subset_341/train-* - config_name: subset_342 data_files: - split: train path: subset_342/train-* - config_name: subset_343 data_files: - split: train path: subset_343/train-* - config_name: subset_344 data_files: - split: train path: subset_344/train-* - config_name: subset_345 data_files: - split: train path: subset_345/train-* - config_name: subset_346 data_files: - split: train path: subset_346/train-* - config_name: subset_347 data_files: - split: train path: subset_347/train-* - config_name: subset_348 data_files: - split: train path: subset_348/train-* - config_name: subset_349 data_files: - split: train path: subset_349/train-* - config_name: subset_35 data_files: - split: train path: subset_35/train-* - config_name: subset_350 data_files: - split: train path: subset_350/train-* - config_name: subset_351 data_files: - split: train path: subset_351/train-* - config_name: subset_352 data_files: - split: train path: subset_352/train-* - config_name: subset_353 data_files: - split: train path: subset_353/train-* - config_name: subset_354 data_files: - split: train path: subset_354/train-* - config_name: subset_355 data_files: - split: train path: subset_355/train-* - config_name: subset_356 data_files: - split: train path: subset_356/train-* - config_name: subset_357 data_files: - split: train path: subset_357/train-* - config_name: subset_358 data_files: - split: train path: subset_358/train-* - config_name: subset_359 data_files: - split: train path: subset_359/train-* - config_name: subset_36 data_files: - split: train path: subset_36/train-* - config_name: subset_360 data_files: - split: train path: subset_360/train-* - config_name: subset_361 data_files: - split: train path: subset_361/train-* - config_name: subset_362 data_files: - split: train path: subset_362/train-* - config_name: subset_363 data_files: - split: train path: subset_363/train-* - config_name: subset_364 data_files: - split: train path: subset_364/train-* - config_name: subset_365 data_files: - split: train path: subset_365/train-* - config_name: subset_366 data_files: - split: train path: subset_366/train-* - config_name: subset_367 data_files: - split: train path: subset_367/train-* - config_name: subset_368 data_files: - split: train path: subset_368/train-* - config_name: subset_369 data_files: - split: train path: subset_369/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_370 data_files: - split: train path: subset_370/train-* - config_name: subset_371 data_files: - split: train path: subset_371/train-* - config_name: subset_372 data_files: - split: train path: subset_372/train-* - config_name: subset_373 data_files: - split: train path: subset_373/train-* - config_name: subset_374 data_files: - split: train path: subset_374/train-* - config_name: subset_375 data_files: - split: train path: subset_375/train-* - config_name: subset_376 data_files: - split: train path: subset_376/train-* - config_name: subset_377 data_files: - split: train path: subset_377/train-* - config_name: subset_378 data_files: - split: train path: subset_378/train-* - config_name: subset_379 data_files: - split: train path: subset_379/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_380 data_files: - split: train path: subset_380/train-* - config_name: subset_381 data_files: - split: train path: subset_381/train-* - config_name: subset_382 data_files: - split: train path: subset_382/train-* - config_name: subset_383 data_files: - split: train path: subset_383/train-* - config_name: subset_384 data_files: - split: train path: subset_384/train-* - config_name: subset_385 data_files: - split: train path: subset_385/train-* - config_name: subset_386 data_files: - split: train path: subset_386/train-* - config_name: subset_387 data_files: - split: train path: subset_387/train-* - config_name: subset_388 data_files: - split: train path: subset_388/train-* - config_name: subset_389 data_files: - split: train path: subset_389/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_390 data_files: - split: train path: subset_390/train-* - config_name: subset_391 data_files: - split: train path: subset_391/train-* - config_name: subset_392 data_files: - split: train path: subset_392/train-* - config_name: subset_393 data_files: - split: train path: subset_393/train-* - config_name: subset_394 data_files: - split: train path: subset_394/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_44 data_files: - split: train path: subset_44/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_46 data_files: - split: train path: subset_46/train-* - config_name: subset_47 data_files: - split: train path: subset_47/train-* - config_name: subset_48 data_files: - split: train path: subset_48/train-* - config_name: subset_49 data_files: - split: train path: subset_49/train-* - config_name: subset_5 data_files: - split: train path: subset_5/train-* - config_name: subset_50 data_files: - split: train path: subset_50/train-* - config_name: subset_51 data_files: - split: train path: subset_51/train-* - config_name: subset_52 data_files: - split: train path: subset_52/train-* - config_name: subset_53 data_files: - split: train path: subset_53/train-* - config_name: subset_54 data_files: - split: train path: subset_54/train-* - config_name: subset_55 data_files: - split: train path: subset_55/train-* - config_name: subset_56 data_files: - split: train path: subset_56/train-* - config_name: subset_57 data_files: - split: train path: subset_57/train-* - config_name: subset_58 data_files: - split: train path: subset_58/train-* - config_name: subset_59 data_files: - split: train path: subset_59/train-* - config_name: subset_6 data_files: - split: train path: subset_6/train-* - config_name: subset_60 data_files: - split: train path: subset_60/train-* - config_name: subset_61 data_files: - split: train path: subset_61/train-* - config_name: subset_62 data_files: - split: train path: subset_62/train-* - config_name: subset_63 data_files: - split: train path: subset_63/train-* - config_name: subset_64 data_files: - split: train path: subset_64/train-* - config_name: subset_65 data_files: - split: train path: subset_65/train-* - config_name: subset_66 data_files: - split: train path: subset_66/train-* - config_name: subset_67 data_files: - split: train path: subset_67/train-* - config_name: subset_68 data_files: - split: train path: subset_68/train-* - config_name: subset_69 data_files: - split: train path: subset_69/train-* - config_name: subset_7 data_files: - split: train path: subset_7/train-* - config_name: subset_70 data_files: - split: train path: subset_70/train-* - config_name: subset_71 data_files: - split: train path: subset_71/train-* - config_name: subset_72 data_files: - split: train path: subset_72/train-* - config_name: subset_73 data_files: - split: train path: subset_73/train-* - config_name: subset_74 data_files: - split: train path: subset_74/train-* - config_name: subset_75 data_files: - split: train path: subset_75/train-* - config_name: subset_76 data_files: - split: train path: subset_76/train-* - config_name: subset_77 data_files: - split: train path: subset_77/train-* - config_name: subset_78 data_files: - split: train path: subset_78/train-* - config_name: subset_79 data_files: - split: train path: subset_79/train-* - config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

dsfsi/vukuzenzele-sentence-aligned

dsfsi

--- language: - eng - afr - nbl - xho - zul - sot - nso - tsn - ssw - ven - tso license: cc-by-4.0 task_categories: - sentence-similarity - translation pretty_name: The Vuk'uzenzele South African Multilingual Corpus tags: - multilingual - government arxiv: 2303.0375 configs: - config_name: afr-eng data_files: - split: train path: afr-eng/train-* - split: test path: afr-eng/test-* - split: eval path: afr-eng/eval-* - config_name: afr-nbl data_files: - split: train path: afr-nbl/train-* - split: test path: afr-nbl/test-* - split: eval path: afr-nbl/eval-* - config_name: afr-nso data_files: - split: train path: afr-nso/train-* - split: test path: afr-nso/test-* - split: eval path: afr-nso/eval-* - config_name: afr-sot data_files: - split: train path: afr-sot/train-* - split: test path: afr-sot/test-* - split: eval path: afr-sot/eval-* - config_name: afr-ssw data_files: - split: train path: afr-ssw/train-* - split: test path: afr-ssw/test-* - split: eval path: afr-ssw/eval-* - config_name: afr-tsn data_files: - split: train path: afr-tsn/train-* - split: test path: afr-tsn/test-* - split: eval path: afr-tsn/eval-* - config_name: afr-tso data_files: - split: train path: afr-tso/train-* - split: test path: afr-tso/test-* - split: eval path: afr-tso/eval-* - config_name: afr-ven data_files: - split: train path: afr-ven/train-* - split: test path: afr-ven/test-* - split: eval path: afr-ven/eval-* - config_name: afr-xho data_files: - split: train path: afr-xho/train-* - split: test path: afr-xho/test-* - split: eval path: afr-xho/eval-* - config_name: afr-zul data_files: - split: train path: afr-zul/train-* - split: test path: afr-zul/test-* - split: eval path: afr-zul/eval-* - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* - config_name: eng-nbl data_files: - split: train path: eng-nbl/train-* - split: test path: eng-nbl/test-* - split: eval path: eng-nbl/eval-* - config_name: eng-nso data_files: - split: train path: eng-nso/train-* - split: test path: eng-nso/test-* - split: eval path: eng-nso/eval-* - config_name: eng-sot data_files: - split: train path: eng-sot/train-* - split: test path: eng-sot/test-* - split: eval path: eng-sot/eval-* - config_name: eng-ssw data_files: - split: train path: eng-ssw/train-* - split: test path: eng-ssw/test-* - split: eval path: eng-ssw/eval-* - config_name: eng-tsn data_files: - split: train path: eng-tsn/train-* - split: test path: eng-tsn/test-* - split: eval path: eng-tsn/eval-* - config_name: eng-tso data_files: - split: train path: eng-tso/train-* - split: test path: eng-tso/test-* - split: eval path: eng-tso/eval-* - config_name: eng-ven data_files: - split: train path: eng-ven/train-* - split: test path: eng-ven/test-* - split: eval path: eng-ven/eval-* - config_name: eng-xho data_files: - split: train path: eng-xho/train-* - split: test path: eng-xho/test-* - split: eval path: eng-xho/eval-* - config_name: eng-zul data_files: - split: train path: eng-zul/train-* - split: test path: eng-zul/test-* - split: eval path: eng-zul/eval-* - config_name: nbl-nso data_files: - split: train path: nbl-nso/train-* - split: test path: nbl-nso/test-* - split: eval path: nbl-nso/eval-* - config_name: nbl-sot data_files: - split: train path: nbl-sot/train-* - split: test path: nbl-sot/test-* - split: eval path: nbl-sot/eval-* - config_name: nbl-ssw data_files: - split: train path: nbl-ssw/train-* - split: test path: nbl-ssw/test-* - split: eval path: nbl-ssw/eval-* - config_name: nbl-tsn data_files: - split: train path: nbl-tsn/train-* - split: test path: nbl-tsn/test-* - split: eval path: nbl-tsn/eval-* - config_name: nbl-tso data_files: - split: train path: nbl-tso/train-* - split: test path: nbl-tso/test-* - split: eval path: nbl-tso/eval-* - config_name: nbl-ven data_files: - split: train path: nbl-ven/train-* - split: test path: nbl-ven/test-* - split: eval path: nbl-ven/eval-* - config_name: nbl-xho data_files: - split: train path: nbl-xho/train-* - split: test path: nbl-xho/test-* - split: eval path: nbl-xho/eval-* - config_name: nbl-zul data_files: - split: train path: nbl-zul/train-* - split: test path: nbl-zul/test-* - split: eval path: nbl-zul/eval-* - config_name: nso-sot data_files: - split: train path: nso-sot/train-* - split: test path: nso-sot/test-* - split: eval path: nso-sot/eval-* - config_name: nso-ssw data_files: - split: train path: nso-ssw/train-* - split: test path: nso-ssw/test-* - split: eval path: nso-ssw/eval-* - config_name: nso-tsn data_files: - split: train path: nso-tsn/train-* - split: test path: nso-tsn/test-* - split: eval path: nso-tsn/eval-* - config_name: nso-tso data_files: - split: train path: nso-tso/train-* - split: test path: nso-tso/test-* - split: eval path: nso-tso/eval-* - config_name: nso-ven data_files: - split: train path: nso-ven/train-* - split: test path: nso-ven/test-* - split: eval path: nso-ven/eval-* - config_name: nso-xho data_files: - split: train path: nso-xho/train-* - split: test path: nso-xho/test-* - split: eval path: nso-xho/eval-* - config_name: nso-zul data_files: - split: train path: nso-zul/train-* - split: test path: nso-zul/test-* - split: eval path: nso-zul/eval-* - config_name: sot-ssw data_files: - split: train path: sot-ssw/train-* - split: test path: sot-ssw/test-* - split: eval path: sot-ssw/eval-* - config_name: sot-tsn data_files: - split: train path: sot-tsn/train-* - split: test path: sot-tsn/test-* - split: eval path: sot-tsn/eval-* - config_name: sot-tso data_files: - split: train path: sot-tso/train-* - split: test path: sot-tso/test-* - split: eval path: sot-tso/eval-* - config_name: sot-ven data_files: - split: train path: sot-ven/train-* - split: test path: sot-ven/test-* - split: eval path: sot-ven/eval-* - config_name: sot-xho data_files: - split: train path: sot-xho/train-* - split: test path: sot-xho/test-* - split: eval path: sot-xho/eval-* - config_name: sot-zul data_files: - split: train path: sot-zul/train-* - split: test path: sot-zul/test-* - split: eval path: sot-zul/eval-* - config_name: ssw-tsn data_files: - split: train path: ssw-tsn/train-* - split: test path: ssw-tsn/test-* - split: eval path: ssw-tsn/eval-* - config_name: ssw-tso data_files: - split: train path: ssw-tso/train-* - split: test path: ssw-tso/test-* - split: eval path: ssw-tso/eval-* - config_name: ssw-ven data_files: - split: train path: ssw-ven/train-* - split: test path: ssw-ven/test-* - split: eval path: ssw-ven/eval-* - config_name: ssw-xho data_files: - split: train path: ssw-xho/train-* - split: test path: ssw-xho/test-* - split: eval path: ssw-xho/eval-* - config_name: ssw-zul data_files: - split: train path: ssw-zul/train-* - split: test path: ssw-zul/test-* - split: eval path: ssw-zul/eval-* - config_name: tsn-tso data_files: - split: train path: tsn-tso/train-* - split: test path: tsn-tso/test-* - split: eval path: tsn-tso/eval-* - config_name: tsn-ven data_files: - split: train path: tsn-ven/train-* - split: test path: tsn-ven/test-* - split: eval path: tsn-ven/eval-* - config_name: tsn-xho data_files: - split: train path: tsn-xho/train-* - split: test path: tsn-xho/test-* - split: eval path: tsn-xho/eval-* - config_name: tsn-zul data_files: - split: train path: tsn-zul/train-* - split: test path: tsn-zul/test-* - split: eval path: tsn-zul/eval-* - config_name: tso-ven data_files: - split: train path: tso-ven/train-* - split: test path: tso-ven/test-* - split: eval path: tso-ven/eval-* - config_name: tso-xho data_files: - split: train path: tso-xho/train-* - split: test path: tso-xho/test-* - split: eval path: tso-xho/eval-* - config_name: tso-zul data_files: - split: train path: tso-zul/train-* - split: test path: tso-zul/test-* - split: eval path: tso-zul/eval-* - config_name: ven-xho data_files: - split: train path: ven-xho/train-* - split: test path: ven-xho/test-* - split: eval path: ven-xho/eval-* - config_name: ven-zul data_files: - split: train path: ven-zul/train-* - split: test path: ven-zul/test-* - split: eval path: ven-zul/eval-* - config_name: xho-zul data_files: - split: train path: xho-zul/train-* - split: test path: xho-zul/test-* - split: eval path: xho-zul/eval-* dataset_info: - config_name: afr-eng features: - name: afr dtype: string - name: eng dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 793530 num_examples: 2660 - name: test num_bytes: 171644 num_examples: 570 - name: eval num_bytes: 172132 num_examples: 571 download_size: 757198 dataset_size: 1137306 - config_name: afr-nbl features: - name: afr dtype: string - name: nbl dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 281328 num_examples: 723 - name: test num_bytes: 57947 num_examples: 155 - name: eval num_bytes: 59996 num_examples: 155 download_size: 279950 dataset_size: 399271 - config_name: afr-nso features: - name: afr dtype: string - name: nso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 980475 num_examples: 2937 - name: test num_bytes: 203451 num_examples: 630 - name: eval num_bytes: 214623 num_examples: 630 download_size: 892392 dataset_size: 1398549 - config_name: afr-sot features: - name: afr dtype: string - name: sot dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 971841 num_examples: 2968 - name: test num_bytes: 211374 num_examples: 636 - name: eval num_bytes: 209697 num_examples: 636 download_size: 901006 dataset_size: 1392912 - config_name: afr-ssw features: - name: afr dtype: string - name: ssw dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 975744 num_examples: 3042 - name: test num_bytes: 209151 num_examples: 652 - name: eval num_bytes: 208877 num_examples: 653 download_size: 927666 dataset_size: 1393772 - config_name: afr-tsn features: - name: afr dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1010506 num_examples: 2830 - name: test num_bytes: 218153 num_examples: 607 - name: eval num_bytes: 214373 num_examples: 607 download_size: 913596 dataset_size: 1443032 - config_name: afr-tso features: - name: afr dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 980025 num_examples: 2952 - name: test num_bytes: 213355 num_examples: 633 - name: eval num_bytes: 211642 num_examples: 633 download_size: 902666 dataset_size: 1405022 - config_name: afr-ven features: - name: afr dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 352031 num_examples: 830 - name: test num_bytes: 72702 num_examples: 178 - name: eval num_bytes: 75243 num_examples: 178 download_size: 323825 dataset_size: 499976 - config_name: afr-xho features: - name: afr dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 986062 num_examples: 3098 - name: test num_bytes: 205229 num_examples: 664 - name: eval num_bytes: 210379 num_examples: 665 download_size: 944334 dataset_size: 1401670 - config_name: afr-zul features: - name: afr dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 982102 num_examples: 3078 - name: test num_bytes: 208473 num_examples: 660 - name: eval num_bytes: 201824 num_examples: 660 download_size: 932565 dataset_size: 1392399 - config_name: default features: - name: nbl dtype: string - name: nso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 128131 num_examples: 315 - name: test num_bytes: 31826 num_examples: 79 download_size: 113394 dataset_size: 159957 - config_name: eng-nbl features: - name: eng dtype: string - name: nbl dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 78419 num_examples: 207 - name: test num_bytes: 16930 num_examples: 45 - name: eval num_bytes: 15202 num_examples: 45 download_size: 89654 dataset_size: 110551 - config_name: eng-nso features: - name: eng dtype: string - name: nso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 848347 num_examples: 2616 - name: test num_bytes: 183267 num_examples: 561 - name: eval num_bytes: 181802 num_examples: 561 download_size: 770909 dataset_size: 1213416 - config_name: eng-sot features: - name: eng dtype: string - name: sot dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 843173 num_examples: 2671 - name: test num_bytes: 181709 num_examples: 573 - name: eval num_bytes: 180602 num_examples: 573 download_size: 776145 dataset_size: 1205484 - config_name: eng-ssw features: - name: eng dtype: string - name: ssw dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 830354 num_examples: 2662 - name: test num_bytes: 175688 num_examples: 571 - name: eval num_bytes: 176734 num_examples: 571 download_size: 777951 dataset_size: 1182776 - config_name: eng-tsn features: - name: eng dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 880306 num_examples: 2517 - name: test num_bytes: 190843 num_examples: 539 - name: eval num_bytes: 187728 num_examples: 540 download_size: 786563 dataset_size: 1258877 - config_name: eng-tso features: - name: eng dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 849914 num_examples: 2623 - name: test num_bytes: 181181 num_examples: 562 - name: eval num_bytes: 176362 num_examples: 563 download_size: 773662 dataset_size: 1207457 - config_name: eng-ven features: - name: eng dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 113647 num_examples: 279 - name: test num_bytes: 26195 num_examples: 60 - name: eval num_bytes: 26121 num_examples: 60 download_size: 119271 dataset_size: 165963 - config_name: eng-xho features: - name: eng dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 827201 num_examples: 2662 - name: test num_bytes: 175023 num_examples: 571 - name: eval num_bytes: 176047 num_examples: 571 download_size: 784961 dataset_size: 1178271 - config_name: eng-zul features: - name: eng dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 815837 num_examples: 2646 - name: test num_bytes: 168769 num_examples: 567 - name: eval num_bytes: 177547 num_examples: 567 download_size: 767836 dataset_size: 1162153 - config_name: nbl-nso features: - name: nbl dtype: string - name: nso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 109438 num_examples: 275 - name: test num_bytes: 24000 num_examples: 59 - name: eval num_bytes: 26519 num_examples: 60 download_size: 118816 dataset_size: 159957 - config_name: nbl-sot features: - name: nbl dtype: string - name: sot dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 149593 num_examples: 365 - name: test num_bytes: 30656 num_examples: 78 - name: eval num_bytes: 32211 num_examples: 79 download_size: 152576 dataset_size: 212460 - config_name: nbl-ssw features: - name: nbl dtype: string - name: ssw dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 146544 num_examples: 387 - name: test num_bytes: 33410 num_examples: 83 - name: eval num_bytes: 32858 num_examples: 84 download_size: 157314 dataset_size: 212812 - config_name: nbl-tsn features: - name: nbl dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 131856 num_examples: 302 - name: test num_bytes: 31961 num_examples: 65 - name: eval num_bytes: 29676 num_examples: 65 download_size: 139315 dataset_size: 193493 - config_name: nbl-tso features: - name: nbl dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 127433 num_examples: 296 - name: test num_bytes: 24654 num_examples: 63 - name: eval num_bytes: 23290 num_examples: 64 download_size: 127532 dataset_size: 175377 - config_name: nbl-ven features: - name: nbl dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 976911 num_examples: 2660 - name: test num_bytes: 211536 num_examples: 570 - name: eval num_bytes: 207694 num_examples: 570 download_size: 885066 dataset_size: 1396141 - config_name: nbl-xho features: - name: nbl dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 149020 num_examples: 403 - name: test num_bytes: 33319 num_examples: 87 - name: eval num_bytes: 31809 num_examples: 87 download_size: 160427 dataset_size: 214148 - config_name: nbl-zul features: - name: nbl dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 111905 num_examples: 289 - name: test num_bytes: 25799 num_examples: 62 - name: eval num_bytes: 22660 num_examples: 63 download_size: 124588 dataset_size: 160364 - config_name: nso-sot features: - name: nso dtype: string - name: sot dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1057851 num_examples: 3052 - name: test num_bytes: 226420 num_examples: 654 - name: eval num_bytes: 232934 num_examples: 655 download_size: 945243 dataset_size: 1517205 - config_name: nso-ssw features: - name: nso dtype: string - name: ssw dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1020738 num_examples: 2968 - name: test num_bytes: 219932 num_examples: 636 - name: eval num_bytes: 218161 num_examples: 637 download_size: 922981 dataset_size: 1458831 - config_name: nso-tsn features: - name: nso dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1092885 num_examples: 2918 - name: test num_bytes: 238439 num_examples: 625 - name: eval num_bytes: 234644 num_examples: 626 download_size: 952272 dataset_size: 1565968 - config_name: nso-tso features: - name: nso dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1045959 num_examples: 2956 - name: test num_bytes: 228677 num_examples: 634 - name: eval num_bytes: 226626 num_examples: 634 download_size: 925262 dataset_size: 1501262 - config_name: nso-ven features: - name: nso dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 155499 num_examples: 343 - name: test num_bytes: 35576 num_examples: 73 - name: eval num_bytes: 31381 num_examples: 74 download_size: 152424 dataset_size: 222456 - config_name: nso-xho features: - name: nso dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1022670 num_examples: 2959 - name: test num_bytes: 214850 num_examples: 634 - name: eval num_bytes: 212932 num_examples: 635 download_size: 929486 dataset_size: 1450452 - config_name: nso-zul features: - name: nso dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1014985 num_examples: 2998 - name: test num_bytes: 223825 num_examples: 643 - name: eval num_bytes: 219173 num_examples: 643 download_size: 926742 dataset_size: 1457983 - config_name: sot-ssw features: - name: sot dtype: string - name: ssw dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1036642 num_examples: 3075 - name: test num_bytes: 217328 num_examples: 659 - name: eval num_bytes: 222863 num_examples: 660 download_size: 950426 dataset_size: 1476833 - config_name: sot-tsn features: - name: sot dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1118346 num_examples: 3019 - name: test num_bytes: 237826 num_examples: 647 - name: eval num_bytes: 235279 num_examples: 647 download_size: 981019 dataset_size: 1591451 - config_name: sot-tso features: - name: sot dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1057631 num_examples: 3027 - name: test num_bytes: 226229 num_examples: 649 - name: eval num_bytes: 222671 num_examples: 649 download_size: 943068 dataset_size: 1506531 - config_name: sot-ven features: - name: sot dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 201166 num_examples: 461 - name: test num_bytes: 44845 num_examples: 99 - name: eval num_bytes: 42607 num_examples: 99 download_size: 191947 dataset_size: 288618 - config_name: sot-xho features: - name: sot dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1042930 num_examples: 3098 - name: test num_bytes: 217327 num_examples: 664 - name: eval num_bytes: 223313 num_examples: 665 download_size: 964792 dataset_size: 1483570 - config_name: sot-zul features: - name: sot dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1017097 num_examples: 3079 - name: test num_bytes: 223761 num_examples: 660 - name: eval num_bytes: 227514 num_examples: 660 download_size: 949761 dataset_size: 1468372 - config_name: ssw-tsn features: - name: ssw dtype: string - name: tsn dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1124400 num_examples: 3110 - name: test num_bytes: 238160 num_examples: 666 - name: eval num_bytes: 246176 num_examples: 667 download_size: 1012570 dataset_size: 1608736 - config_name: ssw-tso features: - name: ssw dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1069540 num_examples: 3142 - name: test num_bytes: 237608 num_examples: 673 - name: eval num_bytes: 231657 num_examples: 674 download_size: 980833 dataset_size: 1538805 - config_name: ssw-ven features: - name: ssw dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 170825 num_examples: 401 - name: test num_bytes: 34774 num_examples: 86 - name: eval num_bytes: 39434 num_examples: 87 download_size: 170522 dataset_size: 245033 - config_name: ssw-xho features: - name: ssw dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1047037 num_examples: 3193 - name: test num_bytes: 227505 num_examples: 684 - name: eval num_bytes: 219981 num_examples: 685 download_size: 992683 dataset_size: 1494523 - config_name: ssw-zul features: - name: ssw dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1054772 num_examples: 3255 - name: test num_bytes: 231524 num_examples: 698 - name: eval num_bytes: 223701 num_examples: 698 download_size: 997182 dataset_size: 1509997 - config_name: tsn-tso features: - name: tsn dtype: string - name: tso dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1141163 num_examples: 3023 - name: test num_bytes: 244100 num_examples: 648 - name: eval num_bytes: 242886 num_examples: 648 download_size: 998631 dataset_size: 1628149 - config_name: tsn-ven features: - name: tsn dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 175353 num_examples: 361 - name: test num_bytes: 39141 num_examples: 77 - name: eval num_bytes: 37453 num_examples: 78 download_size: 165408 dataset_size: 251947 - config_name: tsn-xho features: - name: tsn dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1095514 num_examples: 2989 - name: test num_bytes: 231544 num_examples: 640 - name: eval num_bytes: 227856 num_examples: 641 download_size: 986295 dataset_size: 1554914 - config_name: tsn-zul features: - name: tsn dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1090114 num_examples: 3038 - name: test num_bytes: 232488 num_examples: 651 - name: eval num_bytes: 240758 num_examples: 651 download_size: 989654 dataset_size: 1563360 - config_name: tso-ven features: - name: tso dtype: string - name: ven dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 171428 num_examples: 375 - name: test num_bytes: 33029 num_examples: 80 - name: eval num_bytes: 38079 num_examples: 81 download_size: 163896 dataset_size: 242536 - config_name: tso-xho features: - name: tso dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1049926 num_examples: 3066 - name: test num_bytes: 224708 num_examples: 657 - name: eval num_bytes: 221699 num_examples: 657 download_size: 967978 dataset_size: 1496333 - config_name: tso-zul features: - name: tso dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1059314 num_examples: 3106 - name: test num_bytes: 224935 num_examples: 666 - name: eval num_bytes: 225248 num_examples: 666 download_size: 970505 dataset_size: 1509497 - config_name: ven-xho features: - name: ven dtype: string - name: xho dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 164305 num_examples: 401 - name: test num_bytes: 36290 num_examples: 86 - name: eval num_bytes: 35520 num_examples: 87 download_size: 165177 dataset_size: 236115 - config_name: ven-zul features: - name: ven dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 138178 num_examples: 336 - name: test num_bytes: 32949 num_examples: 72 - name: eval num_bytes: 30697 num_examples: 72 download_size: 143542 dataset_size: 201824 - config_name: xho-zul features: - name: xho dtype: string - name: zul dtype: string - name: score dtype: float64 - name: __index_level_0__ dtype: int64 splits: - name: train num_bytes: 1062980 num_examples: 3276 - name: test num_bytes: 226001 num_examples: 702 - name: eval num_bytes: 225893 num_examples: 703 download_size: 1011124 dataset_size: 1514874 --- # The Vuk'uzenzele South African Multilingual Corpus Github: [https://github.com/dsfsi/vukuzenzele-nlp/](https://github.com/dsfsi/vukuzenzele-nlp/) Zenodo: [](https://doi.org/10.5281/zenodo.7598539) Arxiv Preprint: [](https://arxiv.org/abs/2303.03750) Give Feedback 📑: [DSFSI Resource Feedback Form](https://docs.google.com/forms/d/e/1FAIpQLSf7S36dyAUPx2egmXbFpnTBuzoRulhL5Elu-N1eoMhaO7v10w/formResponse) # About The dataset was obtained from the South African government magazine Vuk'uzenzele, created by the [Government Communication and Information System (GCIS)](https://www.gcis.gov.za/). The original raw PDFS were obtatined from the [Vuk'uzenzele website](https://www.vukuzenzele.gov.za/). The datasets contain government magazine editions in 11 languages, namely: | Language | Code | Language | Code | |------------|-------|------------|-------| | English | (eng) | Sepedi | (sep) | | Afrikaans | (afr) | Setswana | (tsn) | | isiNdebele | (nbl) | Siswati | (ssw) | | isiXhosa | (xho) | Tshivenda | (ven) | | isiZulu | (zul) | Xitstonga | (tso) | | Sesotho | (nso) | ## Available pairings The alignment direction is bidrectional, i.e. xho-zul is zul-xho afr-eng; afr-nbl; afr-nso; afr-sot; afr-ssw; afr-tsn; afr-tso; afr-ven; afr-xho; afr-zul eng-nbl; eng-nso; eng-sot ;eng-ssw; eng-tsn; eng-tso; eng-ven; eng-xho; eng-zul nbl-nso; nbl-sot; nbl-ssw; nbl-tsn; nbl-tso; nbl-ven; nbl-xho; nbl-zul nso-sot; nso-ssw; nso-tsn; nso-tso; nso-ven; nso-xho; nso-zul sot-ssw; sot-tsn; sot-tso; sot-ven; sot-xho; sot-zul ssw-tsn; ssw-tso; ssw-ven; ssw-xho; ssw-zul tsn-tso; tsn-ven; tsn-xho; tsn-zul tso-ven; tso-xho; tso-zul ven-xho; ven-zul xho-zul # Disclaimer This dataset contains machine-readable data extracted from PDF documents, from https://www.vukuzenzele.gov.za/, provided by the Government Communication Information System (GCIS). While efforts were made to ensure the accuracy and completeness of this data, there may be errors or discrepancies between the original publications and this dataset. No warranties, guarantees or representations are given in relation to the information contained in the dataset. The members of the Data Science for Societal Impact Research Group bear no responsibility and/or liability for any such errors or discrepancies in this dataset. The Government Communication Information System (GCIS) bears no responsibility and/or liability for any such errors or discrepancies in this dataset. It is recommended that users verify all information contained herein before making decisions based upon this information. # Datasets The datasets consist of pairwise sentence aligned data. There are 55 distinct datasets of paired sentences. The data is obtained by comparing [LASER](https://github.com/facebookresearch/LASER) embeddings of sentence tokens between 2 languages. If the similarity is high, the sentences are deemed semantic equivalents of one another and the observation is outputted. Naming convention: The naming structure of the pairwise_sentence_aligned folder is `aligned-{src_lang_code}-{tgt_lang_code}.csv`. For example, `aligned-afr-zul.csv` is the aligned sentences between Afrikaans and isiZulu. The data is in .csv format and the columns are `src_text`,`tgt_text`,`cosine_score` where: - `src_text` is the source sentence - `tgt_text` is the target sentence - `cosine_score` is the cosine similarity score obtained by comparing the sentence embeddings, it ranges from 0 to 1 **Note:** The notion of source (src) and target (tgt) are only necessary for distinction between the languages used in the aligned pair, as the sentence semantics should be bidirectional. (hallo <-> sawubona) # Citation Vukosi Marivate, Andani Madodonga, Daniel Njini, Richard Lastrucci, Isheanesu Dzingirai, Jenalea Rajab. **The Vuk'uzenzele South African Multilingual Corpus**, 2023 > @dataset{marivate_vukosi_2023_7598540, author = {Marivate, Vukosi and Njini, Daniel and Madodonga, Andani and Lastrucci, Richard and Dzingirai, Isheanesu Rajab, Jenalea}, title = {The Vuk'uzenzele South African Multilingual Corpus}, month = feb, year = 2023, publisher = {Zenodo}, doi = {10.5281/zenodo.7598539}, url = {https://doi.org/10.5281/zenodo.7598539} } ### Licence * Licence for Data - [CC 4.0 BY](LICENSE.md)

lerobot/taco_play

lerobot

--- license: cc-by-4.0 task_categories: - robotics tags: - LeRobot configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** https://www.kaggle.com/datasets/oiermees/taco-robot - **Paper:** https://arxiv.org/abs/2209.08959, https://arxiv.org/abs/2210.01911 - **License:** cc-by-4.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "unknown", "total_episodes": 3603, "total_frames": 237798, "total_tasks": 406, "total_videos": 7206, "total_chunks": 4, "chunks_size": 1000, "fps": 15, "splits": { "train": "0:3603" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "observation.images.rgb_static": { "dtype": "video", "shape": [ 150, 200, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 15.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.rgb_gripper": { "dtype": "video", "shape": [ 84, 84, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 15.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "language_instruction": { "dtype": "string", "shape": [ 1 ], "names": null }, "observation.state": { "dtype": "float32", "shape": [ 7 ], "names": { "motors": [ "motor_0", "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6" ] } }, "action": { "dtype": "float32", "shape": [ 7 ], "names": { "motors": [ "motor_0", "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6" ] } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "next.reward": { "dtype": "float32", "shape": [ 1 ], "names": null }, "next.done": { "dtype": "bool", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex @inproceedings{rosete2022tacorl, author = {Erick Rosete-Beas and Oier Mees and Gabriel Kalweit and Joschka Boedecker and Wolfram Burgard}, title = {Latent Plans for Task Agnostic Offline Reinforcement Learning}, journal = {Proceedings of the 6th Conference on Robot Learning (CoRL)}, year = {2022} } @inproceedings{mees23hulc2, title={Grounding Language with Visual Affordances over Unstructured Data}, author={Oier Mees and Jessica Borja-Diaz and Wolfram Burgard}, booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)}, year={2023}, address = {London, UK} } ```

Helsinki-NLP/euconst

Helsinki-NLP

--- annotations_creators: - found language_creators: - found language: - cs - da - de - el - en - es - et - fi - fr - ga - hu - it - lt - lv - mt - nl - pl - pt - sk - sl - sv license: - unknown multilinguality: - multilingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - translation task_ids: [] pretty_name: OPUS EUconst dataset_info: - config_name: cs-da features: - name: translation dtype: translation: languages: - cs - da splits: - name: train num_bytes: 1855304 num_examples: 10554 download_size: 882168 dataset_size: 1855304 - config_name: cs-de features: - name: translation dtype: translation: languages: - cs - de splits: - name: train num_bytes: 1817177 num_examples: 8844 download_size: 854414 dataset_size: 1817177 - config_name: cs-el features: - name: translation dtype: translation: languages: - cs - el splits: - name: train num_bytes: 2690296 num_examples: 10072 download_size: 1142620 dataset_size: 2690296 - config_name: cs-en features: - name: translation dtype: translation: languages: - cs - en splits: - name: train num_bytes: 1850944 num_examples: 9954 download_size: 867071 dataset_size: 1850944 - config_name: cs-es features: - name: translation dtype: translation: languages: - cs - es splits: - name: train num_bytes: 1945302 num_examples: 10023 download_size: 912130 dataset_size: 1945302 - config_name: cs-et features: - name: translation dtype: translation: languages: - cs - et splits: - name: train num_bytes: 1774469 num_examples: 10037 download_size: 877105 dataset_size: 1774469 - config_name: cs-fi features: - name: translation dtype: translation: languages: - cs - fi splits: - name: train num_bytes: 1849788 num_examples: 9848 download_size: 889621 dataset_size: 1849788 - config_name: cs-fr features: - name: translation dtype: translation: languages: - cs - fr splits: - name: train num_bytes: 1919485 num_examples: 10160 download_size: 908068 dataset_size: 1919485 - config_name: cs-ga features: - name: translation dtype: translation: languages: - cs - ga splits: - name: train num_bytes: 1967620 num_examples: 10126 download_size: 927945 dataset_size: 1967620 - config_name: cs-hu features: - name: translation dtype: translation: languages: - cs - hu splits: - name: train num_bytes: 1852201 num_examples: 8586 download_size: 879670 dataset_size: 1852201 - config_name: cs-it features: - name: translation dtype: translation: languages: - cs - it splits: - name: train num_bytes: 1883757 num_examples: 10081 download_size: 902650 dataset_size: 1883757 - config_name: cs-lt features: - name: translation dtype: translation: languages: - cs - lt splits: - name: train num_bytes: 1789406 num_examples: 10008 download_size: 886454 dataset_size: 1789406 - config_name: cs-lv features: - name: translation dtype: translation: languages: - cs - lv splits: - name: train num_bytes: 1826158 num_examples: 10144 download_size: 891607 dataset_size: 1826158 - config_name: cs-mt features: - name: translation dtype: translation: languages: - cs - mt splits: - name: train num_bytes: 1923005 num_examples: 10122 download_size: 909276 dataset_size: 1923005 - config_name: cs-nl features: - name: translation dtype: translation: languages: - cs - nl splits: - name: train num_bytes: 1928472 num_examples: 10021 download_size: 906311 dataset_size: 1928472 - config_name: cs-pl features: - name: translation dtype: translation: languages: - cs - pl splits: - name: train num_bytes: 1888530 num_examples: 10029 download_size: 917552 dataset_size: 1888530 - config_name: cs-pt features: - name: translation dtype: translation: languages: - cs - pt splits: - name: train num_bytes: 1771483 num_examples: 10970 download_size: 849861 dataset_size: 1771483 - config_name: cs-sk features: - name: translation dtype: translation: languages: - cs - sk splits: - name: train num_bytes: 1875901 num_examples: 10631 download_size: 932830 dataset_size: 1875901 - config_name: cs-sl features: - name: translation dtype: translation: languages: - cs - sl splits: - name: train num_bytes: 1679327 num_examples: 8860 download_size: 839034 dataset_size: 1679327 - config_name: cs-sv features: - name: translation dtype: translation: languages: - cs - sv splits: - name: train num_bytes: 1860695 num_examples: 10003 download_size: 887009 dataset_size: 1860695 - config_name: da-de features: - name: translation dtype: translation: languages: - da - de splits: - name: train num_bytes: 1867118 num_examples: 9001 download_size: 847720 dataset_size: 1867118 - config_name: da-el features: - name: translation dtype: translation: languages: - da - el splits: - name: train num_bytes: 2764595 num_examples: 10317 download_size: 1136083 dataset_size: 2764595 - config_name: da-en features: - name: translation dtype: translation: languages: - da - en splits: - name: train num_bytes: 1865851 num_examples: 10033 download_size: 841670 dataset_size: 1865851 - config_name: da-es features: - name: translation dtype: translation: languages: - da - es splits: - name: train num_bytes: 1979041 num_examples: 10227 download_size: 889140 dataset_size: 1979041 - config_name: da-et features: - name: translation dtype: translation: languages: - da - et splits: - name: train num_bytes: 1802112 num_examples: 10166 download_size: 854688 dataset_size: 1802112 - config_name: da-fi features: - name: translation dtype: translation: languages: - da - fi splits: - name: train num_bytes: 1932682 num_examples: 10176 download_size: 890624 dataset_size: 1932682 - config_name: da-fr features: - name: translation dtype: translation: languages: - da - fr splits: - name: train num_bytes: 1966731 num_examples: 10410 download_size: 894321 dataset_size: 1966731 - config_name: da-ga features: - name: translation dtype: translation: languages: - da - ga splits: - name: train num_bytes: 1996338 num_examples: 10205 download_size: 905528 dataset_size: 1996338 - config_name: da-hu features: - name: translation dtype: translation: languages: - da - hu splits: - name: train num_bytes: 1880269 num_examples: 8702 download_size: 856913 dataset_size: 1880269 - config_name: da-it features: - name: translation dtype: translation: languages: - da - it splits: - name: train num_bytes: 1934964 num_examples: 10309 download_size: 892879 dataset_size: 1934964 - config_name: da-lt features: - name: translation dtype: translation: languages: - da - lt splits: - name: train num_bytes: 1851150 num_examples: 10269 download_size: 876303 dataset_size: 1851150 - config_name: da-lv features: - name: translation dtype: translation: languages: - da - lv splits: - name: train num_bytes: 1865382 num_examples: 10309 download_size: 876109 dataset_size: 1865382 - config_name: da-mt features: - name: translation dtype: translation: languages: - da - mt splits: - name: train num_bytes: 1946743 num_examples: 10231 download_size: 887000 dataset_size: 1946743 - config_name: da-nl features: - name: translation dtype: translation: languages: - da - nl splits: - name: train num_bytes: 1973989 num_examples: 10261 download_size: 890128 dataset_size: 1973989 - config_name: da-pl features: - name: translation dtype: translation: languages: - da - pl splits: - name: train num_bytes: 1926083 num_examples: 10196 download_size: 900203 dataset_size: 1926083 - config_name: da-pt features: - name: translation dtype: translation: languages: - da - pt splits: - name: train num_bytes: 1818077 num_examples: 10910 download_size: 826694 dataset_size: 1818077 - config_name: da-sk features: - name: translation dtype: translation: languages: - da - sk splits: - name: train num_bytes: 1942975 num_examples: 10685 download_size: 917692 dataset_size: 1942975 - config_name: da-sl features: - name: translation dtype: translation: languages: - da - sl splits: - name: train num_bytes: 1686933 num_examples: 8891 download_size: 811534 dataset_size: 1686933 - config_name: da-sv features: - name: translation dtype: translation: languages: - da - sv splits: - name: train num_bytes: 1909105 num_examples: 10238 download_size: 871025 dataset_size: 1909105 - config_name: de-el features: - name: translation dtype: translation: languages: - de - el splits: - name: train num_bytes: 2651154 num_examples: 8865 download_size: 1092934 dataset_size: 2651154 - config_name: de-en features: - name: translation dtype: translation: languages: - de - en splits: - name: train num_bytes: 1898701 num_examples: 8772 download_size: 848142 dataset_size: 1898701 - config_name: de-es features: - name: translation dtype: translation: languages: - de - es splits: - name: train num_bytes: 1980607 num_examples: 8875 download_size: 883078 dataset_size: 1980607 - config_name: de-et features: - name: translation dtype: translation: languages: - de - et splits: - name: train num_bytes: 1809090 num_examples: 8764 download_size: 848477 dataset_size: 1809090 - config_name: de-fi features: - name: translation dtype: translation: languages: - de - fi splits: - name: train num_bytes: 1956115 num_examples: 8894 download_size: 891805 dataset_size: 1956115 - config_name: de-fr features: - name: translation dtype: translation: languages: - de - fr splits: - name: train num_bytes: 2005971 num_examples: 9068 download_size: 901873 dataset_size: 2005971 - config_name: de-ga features: - name: translation dtype: translation: languages: - de - ga splits: - name: train num_bytes: 1974960 num_examples: 8803 download_size: 890588 dataset_size: 1974960 - config_name: de-hu features: - name: translation dtype: translation: languages: - de - hu splits: - name: train num_bytes: 2074603 num_examples: 8651 download_size: 937341 dataset_size: 2074603 - config_name: de-it features: - name: translation dtype: translation: languages: - de - it splits: - name: train num_bytes: 1967678 num_examples: 9044 download_size: 897940 dataset_size: 1967678 - config_name: de-lt features: - name: translation dtype: translation: languages: - de - lt splits: - name: train num_bytes: 1870199 num_examples: 8957 download_size: 866559 dataset_size: 1870199 - config_name: de-lv features: - name: translation dtype: translation: languages: - de - lv splits: - name: train num_bytes: 1858936 num_examples: 8885 download_size: 859599 dataset_size: 1858936 - config_name: de-mt features: - name: translation dtype: translation: languages: - de - mt splits: - name: train num_bytes: 1944727 num_examples: 8882 download_size: 876527 dataset_size: 1944727 - config_name: de-nl features: - name: translation dtype: translation: languages: - de - nl splits: - name: train num_bytes: 1985160 num_examples: 8938 download_size: 885866 dataset_size: 1985160 - config_name: de-pl features: - name: translation dtype: translation: languages: - de - pl splits: - name: train num_bytes: 1926133 num_examples: 8866 download_size: 890832 dataset_size: 1926133 - config_name: de-pt features: - name: translation dtype: translation: languages: - de - pt splits: - name: train num_bytes: 1758873 num_examples: 8963 download_size: 801282 dataset_size: 1758873 - config_name: de-sk features: - name: translation dtype: translation: languages: - de - sk splits: - name: train num_bytes: 1881934 num_examples: 9033 download_size: 885844 dataset_size: 1881934 - config_name: de-sl features: - name: translation dtype: translation: languages: - de - sl splits: - name: train num_bytes: 1857160 num_examples: 8713 download_size: 878808 dataset_size: 1857160 - config_name: de-sv features: - name: translation dtype: translation: languages: - de - sv splits: - name: train num_bytes: 1920137 num_examples: 8860 download_size: 867044 dataset_size: 1920137 - config_name: el-en features: - name: translation dtype: translation: languages: - el - en splits: - name: train num_bytes: 2727011 num_examples: 9991 download_size: 1105803 dataset_size: 2727011 - config_name: el-es features: - name: translation dtype: translation: languages: - el - es splits: - name: train num_bytes: 2908134 num_examples: 10284 download_size: 1184854 dataset_size: 2908134 - config_name: el-et features: - name: translation dtype: translation: languages: - el - et splits: - name: train num_bytes: 2714874 num_examples: 10173 download_size: 1140529 dataset_size: 2714874 - config_name: el-fi features: - name: translation dtype: translation: languages: - el - fi splits: - name: train num_bytes: 2800067 num_examples: 10056 download_size: 1162281 dataset_size: 2800067 - config_name: el-fr features: - name: translation dtype: translation: languages: - el - fr splits: - name: train num_bytes: 2875614 num_examples: 10315 download_size: 1179593 dataset_size: 2875614 - config_name: el-ga features: - name: translation dtype: translation: languages: - el - ga splits: - name: train num_bytes: 2861197 num_examples: 10094 download_size: 1170946 dataset_size: 2861197 - config_name: el-hu features: - name: translation dtype: translation: languages: - el - hu splits: - name: train num_bytes: 2679785 num_examples: 8745 download_size: 1117097 dataset_size: 2679785 - config_name: el-it features: - name: translation dtype: translation: languages: - el - it splits: - name: train num_bytes: 2851750 num_examples: 10303 download_size: 1183614 dataset_size: 2851750 - config_name: el-lt features: - name: translation dtype: translation: languages: - el - lt splits: - name: train num_bytes: 2754237 num_examples: 10208 download_size: 1155961 dataset_size: 2754237 - config_name: el-lv features: - name: translation dtype: translation: languages: - el - lv splits: - 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config_name: es-ga features: - name: translation dtype: translation: languages: - es - ga splits: - name: train num_bytes: 2144551 num_examples: 10147 download_size: 952444 dataset_size: 2144551 - config_name: es-hu features: - name: translation dtype: translation: languages: - es - hu splits: - name: train num_bytes: 2051881 num_examples: 8760 download_size: 919527 dataset_size: 2051881 - config_name: es-it features: - name: translation dtype: translation: languages: - es - it splits: - name: train num_bytes: 2108049 num_examples: 10336 download_size: 953118 dataset_size: 2108049 - config_name: es-lt features: - name: translation dtype: translation: languages: - es - lt splits: - name: train num_bytes: 2020068 num_examples: 10297 download_size: 936379 dataset_size: 2020068 - config_name: es-lv features: - name: translation dtype: translation: languages: - es - lv splits: - name: train num_bytes: 2007742 num_examples: 10218 download_size: 918666 dataset_size: 2007742 - config_name: es-mt features: - 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name: train num_bytes: 1898810 num_examples: 8872 download_size: 889702 dataset_size: 1898810 - config_name: et-it features: - name: translation dtype: translation: languages: - et - it splits: - name: train num_bytes: 1915653 num_examples: 10198 download_size: 910098 dataset_size: 1915653 - config_name: et-lt features: - name: translation dtype: translation: languages: - et - lt splits: - name: train num_bytes: 1777689 num_examples: 10015 download_size: 868261 dataset_size: 1777689 - config_name: et-lv features: - name: translation dtype: translation: languages: - et - lv splits: - name: train num_bytes: 1848520 num_examples: 10379 download_size: 894891 dataset_size: 1848520 - config_name: et-mt features: - name: translation dtype: translation: languages: - et - mt splits: - name: train num_bytes: 1957895 num_examples: 10278 download_size: 919214 dataset_size: 1957895 - config_name: et-nl features: - name: translation dtype: translation: languages: - et - nl splits: - name: train num_bytes: 1967828 num_examples: 10196 download_size: 913705 dataset_size: 1967828 - 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config_name: fr-lt features: - name: translation dtype: translation: languages: - fr - lt splits: - name: train num_bytes: 1964743 num_examples: 10346 download_size: 921306 dataset_size: 1964743 - config_name: fr-lv features: - name: translation dtype: translation: languages: - fr - lv splits: - name: train num_bytes: 1947085 num_examples: 10269 download_size: 903449 dataset_size: 1947085 - config_name: fr-mt features: - name: translation dtype: translation: languages: - fr - mt splits: - name: train num_bytes: 2069116 num_examples: 10333 download_size: 939615 dataset_size: 2069116 - config_name: fr-nl features: - name: translation dtype: translation: languages: - fr - nl splits: - name: train num_bytes: 2119906 num_examples: 10363 download_size: 949772 dataset_size: 2119906 - config_name: fr-pl features: - name: translation dtype: translation: languages: - fr - pl splits: - name: train num_bytes: 2039763 num_examples: 10243 download_size: 945055 dataset_size: 2039763 - config_name: fr-pt features: - 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lv - sl splits: - name: train num_bytes: 1706708 num_examples: 8939 download_size: 836300 dataset_size: 1706708 - config_name: lv-sv features: - name: translation dtype: translation: languages: - lv - sv splits: - name: train num_bytes: 1903467 num_examples: 10083 download_size: 886655 dataset_size: 1903467 - config_name: mt-nl features: - name: translation dtype: translation: languages: - mt - nl splits: - name: train num_bytes: 2113163 num_examples: 10281 download_size: 947706 dataset_size: 2113163 - config_name: mt-pl features: - name: translation dtype: translation: languages: - mt - pl splits: - name: train num_bytes: 2068082 num_examples: 10232 download_size: 959844 dataset_size: 2068082 - config_name: mt-pt features: - name: translation dtype: translation: languages: - mt - pt splits: - name: train num_bytes: 1842898 num_examples: 10278 download_size: 845671 dataset_size: 1842898 - config_name: mt-sk features: - name: translation dtype: translation: languages: - mt - sk splits: - name: train num_bytes: 1997330 num_examples: 10344 download_size: 948776 dataset_size: 1997330 - config_name: mt-sl features: - name: translation dtype: translation: languages: - mt - sl splits: - name: train num_bytes: 1795027 num_examples: 8892 download_size: 856085 dataset_size: 1795027 - config_name: mt-sv features: - name: translation dtype: translation: languages: - mt - sv splits: - name: train num_bytes: 2031237 num_examples: 10211 download_size: 917842 dataset_size: 2031237 - config_name: nl-pl features: - name: translation dtype: translation: languages: - nl - pl splits: - name: train num_bytes: 2090781 num_examples: 10244 download_size: 966420 dataset_size: 2090781 - config_name: nl-pt features: - name: translation dtype: translation: languages: - nl - pt splits: - name: train num_bytes: 1838407 num_examples: 10080 download_size: 832162 dataset_size: 1838407 - config_name: nl-sk features: - name: translation dtype: translation: languages: - nl - sk splits: - name: train num_bytes: 2018759 num_examples: 10333 download_size: 949531 dataset_size: 2018759 - config_name: nl-sl features: - name: translation dtype: translation: languages: - nl - sl splits: - name: train num_bytes: 1831790 num_examples: 8969 download_size: 865166 dataset_size: 1831790 - config_name: nl-sv features: - name: translation dtype: translation: languages: - nl - sv splits: - name: train num_bytes: 2061249 num_examples: 10232 download_size: 923554 dataset_size: 2061249 - config_name: pl-pt features: - name: translation dtype: translation: languages: - pl - pt splits: - name: train num_bytes: 1825006 num_examples: 10157 download_size: 857123 dataset_size: 1825006 - config_name: pl-sk features: - name: translation dtype: translation: languages: - pl - sk splits: - name: train num_bytes: 1974134 num_examples: 10335 download_size: 961962 dataset_size: 1974134 - config_name: pl-sl features: - name: translation dtype: translation: languages: - pl - sl splits: - name: train num_bytes: 1781013 num_examples: 8819 download_size: 869217 dataset_size: 1781013 - config_name: pl-sv features: - name: translation dtype: translation: languages: - pl - sv splits: - name: train num_bytes: 2016862 num_examples: 10147 download_size: 932545 dataset_size: 2016862 - config_name: pt-sk features: - name: translation dtype: translation: languages: - pt - sk splits: - name: train num_bytes: 1782241 num_examples: 10597 download_size: 851561 dataset_size: 1782241 - config_name: pt-sl features: - name: translation dtype: translation: languages: - pt - sl splits: - name: train num_bytes: 1557343 num_examples: 8988 download_size: 756975 dataset_size: 1557343 - config_name: pt-sv features: - name: translation dtype: translation: languages: - pt - sv splits: - name: train num_bytes: 1760626 num_examples: 10026 download_size: 811206 dataset_size: 1760626 - config_name: sk-sl features: - name: translation dtype: translation: languages: - sk - sl splits: - name: train num_bytes: 1712582 num_examples: 9051 download_size: 856239 dataset_size: 1712582 - config_name: sk-sv features: - name: translation dtype: translation: languages: - sk - sv splits: - name: train num_bytes: 1937070 num_examples: 10253 download_size: 918866 dataset_size: 1937070 - config_name: sl-sv features: - name: translation dtype: translation: languages: - sl - sv splits: - name: train num_bytes: 1750290 num_examples: 8816 download_size: 833320 dataset_size: 1750290 configs: - config_name: cs-da data_files: - split: train path: cs-da/train-* - config_name: cs-de data_files: - split: train path: cs-de/train-* - config_name: cs-el data_files: - split: train path: cs-el/train-* - config_name: cs-en data_files: - split: train path: cs-en/train-* - config_name: cs-es data_files: - split: train path: cs-es/train-* - config_name: cs-et data_files: - split: train path: cs-et/train-* - config_name: cs-fi data_files: - split: train path: cs-fi/train-* - config_name: cs-fr data_files: - split: train path: cs-fr/train-* - config_name: cs-ga data_files: - split: train path: cs-ga/train-* - config_name: cs-hu data_files: - split: train path: cs-hu/train-* - config_name: cs-it data_files: - split: train path: cs-it/train-* - config_name: cs-lt data_files: - split: train path: cs-lt/train-* - config_name: cs-lv data_files: - split: train path: cs-lv/train-* - config_name: cs-mt data_files: - split: train path: cs-mt/train-* - config_name: cs-nl data_files: - split: train path: cs-nl/train-* - config_name: cs-pl data_files: - split: train path: cs-pl/train-* - config_name: cs-pt data_files: - split: train path: cs-pt/train-* - config_name: cs-sk data_files: - split: train path: cs-sk/train-* - config_name: cs-sl data_files: - split: train path: cs-sl/train-* - config_name: cs-sv data_files: - split: train path: cs-sv/train-* - config_name: da-de data_files: - split: train path: da-de/train-* - config_name: da-el data_files: - split: train path: da-el/train-* - config_name: da-en data_files: - split: train path: da-en/train-* - config_name: da-es data_files: - split: train path: da-es/train-* - config_name: da-et data_files: - split: train path: da-et/train-* - config_name: da-fi data_files: - split: train path: da-fi/train-* - config_name: da-fr data_files: - split: train path: da-fr/train-* - config_name: da-ga data_files: - split: train path: da-ga/train-* - config_name: da-hu data_files: - split: train path: da-hu/train-* - config_name: da-it data_files: - split: train path: da-it/train-* - config_name: da-lt data_files: - split: train path: da-lt/train-* - config_name: da-lv data_files: - split: train path: da-lv/train-* - config_name: da-mt data_files: - split: train path: da-mt/train-* - config_name: da-nl data_files: - split: train path: da-nl/train-* - config_name: da-pl data_files: - split: train path: da-pl/train-* - config_name: da-pt data_files: - split: train path: da-pt/train-* - config_name: da-sk data_files: - split: train path: da-sk/train-* - config_name: da-sl data_files: - split: train path: da-sl/train-* - config_name: da-sv data_files: - split: train path: da-sv/train-* - config_name: de-el data_files: - split: train path: de-el/train-* - config_name: de-en data_files: - split: train path: de-en/train-* - config_name: de-es data_files: - split: train path: de-es/train-* - config_name: de-et data_files: - split: train path: de-et/train-* - config_name: de-fi data_files: - split: train path: de-fi/train-* - config_name: de-fr data_files: - split: train path: de-fr/train-* - config_name: de-ga data_files: - split: train path: de-ga/train-* - config_name: de-hu data_files: - split: train path: de-hu/train-* - config_name: de-it data_files: - split: train path: de-it/train-* - config_name: de-lt data_files: - split: train path: de-lt/train-* - config_name: de-lv data_files: - split: train path: de-lv/train-* - config_name: de-mt data_files: - split: train path: de-mt/train-* - config_name: de-nl data_files: - split: train path: de-nl/train-* - config_name: de-pl data_files: - split: train path: de-pl/train-* - config_name: de-pt data_files: - split: train path: de-pt/train-* - config_name: de-sk data_files: - split: train path: de-sk/train-* - config_name: de-sl data_files: - split: train path: de-sl/train-* - config_name: de-sv data_files: - split: train path: de-sv/train-* - config_name: el-en data_files: - split: train path: el-en/train-* - config_name: el-es data_files: - split: train path: el-es/train-* - config_name: el-et data_files: - split: train path: el-et/train-* - config_name: el-fi data_files: - split: train path: el-fi/train-* - config_name: el-fr data_files: - split: train path: el-fr/train-* - config_name: el-ga data_files: - split: train path: el-ga/train-* - config_name: el-hu data_files: - split: train path: el-hu/train-* - config_name: el-it data_files: - split: train path: el-it/train-* - config_name: el-lt data_files: - split: train path: el-lt/train-* - config_name: el-lv data_files: - split: train path: el-lv/train-* - config_name: el-mt data_files: - split: train path: el-mt/train-* - config_name: el-nl data_files: - split: train path: el-nl/train-* - config_name: el-pl data_files: - split: train path: el-pl/train-* - config_name: el-pt data_files: - split: train path: el-pt/train-* - config_name: el-sk data_files: - split: train path: el-sk/train-* - config_name: el-sl data_files: - split: train path: el-sl/train-* - config_name: el-sv data_files: - split: train path: el-sv/train-* - config_name: en-es data_files: - split: train path: en-es/train-* - config_name: en-et data_files: - split: train path: en-et/train-* - config_name: en-fi data_files: - split: train path: en-fi/train-* - config_name: en-fr data_files: - split: train path: en-fr/train-* - config_name: en-ga data_files: - split: train path: en-ga/train-* - config_name: en-hu data_files: - split: train path: en-hu/train-* - config_name: en-it data_files: - split: train path: en-it/train-* - config_name: en-lt data_files: - split: train path: en-lt/train-* - config_name: en-lv data_files: - split: train path: en-lv/train-* - config_name: en-mt data_files: - split: train path: en-mt/train-* - config_name: en-nl data_files: - split: train path: en-nl/train-* - config_name: en-pl data_files: - split: train path: en-pl/train-* - config_name: en-pt data_files: - split: train path: en-pt/train-* - config_name: en-sk data_files: - split: train path: en-sk/train-* - config_name: en-sl data_files: - split: train path: en-sl/train-* - config_name: en-sv data_files: - split: train path: en-sv/train-* - config_name: es-et data_files: - split: train path: es-et/train-* - config_name: es-fi data_files: - split: train path: es-fi/train-* - config_name: es-fr data_files: - split: train path: es-fr/train-* - config_name: es-ga data_files: - split: train path: es-ga/train-* - config_name: es-hu data_files: - split: train path: es-hu/train-* - config_name: es-it data_files: - split: train path: es-it/train-* - config_name: es-lt data_files: - split: train path: es-lt/train-* - config_name: es-lv data_files: - split: train path: es-lv/train-* - config_name: es-mt data_files: - split: train path: es-mt/train-* - config_name: es-nl data_files: - split: train path: es-nl/train-* - config_name: es-pl data_files: - split: train path: es-pl/train-* - config_name: es-pt data_files: - split: train path: es-pt/train-* - config_name: es-sk data_files: - split: train path: es-sk/train-* - config_name: es-sl data_files: - split: train path: es-sl/train-* - config_name: es-sv data_files: - split: train path: es-sv/train-* - config_name: et-fi data_files: - split: train path: et-fi/train-* - config_name: et-fr data_files: - split: train path: et-fr/train-* - config_name: et-ga data_files: - split: train path: et-ga/train-* - config_name: et-hu data_files: - split: train path: et-hu/train-* - config_name: et-it data_files: - split: train path: et-it/train-* - config_name: et-lt data_files: - split: train path: et-lt/train-* - config_name: et-lv data_files: - split: train path: et-lv/train-* - config_name: et-mt data_files: - split: train path: et-mt/train-* - config_name: et-nl data_files: - split: train path: et-nl/train-* - config_name: et-pl data_files: - split: train path: et-pl/train-* - config_name: et-pt data_files: - split: train path: et-pt/train-* - config_name: et-sk data_files: - split: train path: et-sk/train-* - config_name: et-sl data_files: - split: train path: et-sl/train-* - config_name: et-sv data_files: - split: train path: et-sv/train-* - config_name: fi-fr data_files: - split: train path: fi-fr/train-* - config_name: fi-ga data_files: - split: train path: fi-ga/train-* - config_name: fi-hu data_files: - split: train path: fi-hu/train-* - config_name: fi-it data_files: - split: train path: fi-it/train-* - config_name: fi-lt data_files: - split: train path: fi-lt/train-* - config_name: fi-lv data_files: - split: train path: fi-lv/train-* - config_name: fi-mt data_files: - split: train path: fi-mt/train-* - config_name: fi-nl data_files: - split: train path: fi-nl/train-* - config_name: fi-pl data_files: - split: train path: fi-pl/train-* - config_name: fi-pt data_files: - split: train path: fi-pt/train-* - config_name: fi-sk data_files: - split: train path: fi-sk/train-* - config_name: fi-sl data_files: - split: train path: fi-sl/train-* - config_name: fi-sv data_files: - split: train path: fi-sv/train-* - config_name: fr-ga data_files: - split: train path: fr-ga/train-* - config_name: fr-hu data_files: - split: train path: fr-hu/train-* - config_name: fr-it data_files: - split: train path: fr-it/train-* - config_name: fr-lt data_files: - split: train path: fr-lt/train-* - config_name: fr-lv data_files: - split: train path: fr-lv/train-* - config_name: fr-mt data_files: - split: train path: fr-mt/train-* - config_name: fr-nl data_files: - split: train path: fr-nl/train-* - config_name: fr-pl data_files: - split: train path: fr-pl/train-* - config_name: fr-pt data_files: - split: train path: fr-pt/train-* - config_name: fr-sk data_files: - split: train path: fr-sk/train-* - config_name: fr-sl data_files: - split: train path: fr-sl/train-* - config_name: fr-sv data_files: - split: train path: fr-sv/train-* - config_name: ga-hu data_files: - split: train path: ga-hu/train-* - config_name: ga-it data_files: - split: train path: ga-it/train-* - config_name: ga-lt data_files: - split: train path: ga-lt/train-* - config_name: ga-lv data_files: - split: train path: ga-lv/train-* - config_name: ga-mt data_files: - split: train path: ga-mt/train-* - config_name: ga-nl data_files: - split: train path: ga-nl/train-* - config_name: ga-pl data_files: - split: train path: ga-pl/train-* - config_name: ga-pt data_files: - split: train path: ga-pt/train-* - config_name: ga-sk data_files: - split: train path: ga-sk/train-* - config_name: ga-sl data_files: - split: train path: ga-sl/train-* - config_name: ga-sv data_files: - split: train path: ga-sv/train-* - config_name: hu-it data_files: - split: train path: hu-it/train-* - config_name: hu-lt data_files: - split: train path: hu-lt/train-* - config_name: hu-lv data_files: - split: train path: hu-lv/train-* - config_name: hu-mt data_files: - split: train path: hu-mt/train-* - config_name: hu-nl data_files: - split: train path: hu-nl/train-* - config_name: hu-pl data_files: - split: train path: hu-pl/train-* - config_name: hu-pt data_files: - split: train path: hu-pt/train-* - config_name: hu-sk data_files: - split: train path: hu-sk/train-* - config_name: hu-sl data_files: - split: train path: hu-sl/train-* - config_name: hu-sv data_files: - split: train path: hu-sv/train-* - config_name: it-lt data_files: - split: train path: it-lt/train-* - config_name: it-lv data_files: - split: train path: it-lv/train-* - config_name: it-mt data_files: - split: train path: it-mt/train-* - config_name: it-nl data_files: - split: train path: it-nl/train-* - config_name: it-pl data_files: - split: train path: it-pl/train-* - config_name: it-pt data_files: - split: train path: it-pt/train-* - config_name: it-sk data_files: - split: train path: it-sk/train-* - config_name: it-sl data_files: - split: train path: it-sl/train-* - config_name: it-sv data_files: - split: train path: it-sv/train-* - config_name: lt-lv data_files: - split: train path: lt-lv/train-* - config_name: lt-mt data_files: - split: train path: lt-mt/train-* - config_name: lt-nl data_files: - split: train path: lt-nl/train-* - config_name: lt-pl data_files: - split: train path: lt-pl/train-* - config_name: lt-pt data_files: - split: train path: lt-pt/train-* - config_name: lt-sk data_files: - split: train path: lt-sk/train-* - config_name: lt-sl data_files: - split: train path: lt-sl/train-* - config_name: lt-sv data_files: - split: train path: lt-sv/train-* - config_name: lv-mt data_files: - split: train path: lv-mt/train-* - config_name: lv-nl data_files: - split: train path: lv-nl/train-* - config_name: lv-pl data_files: - split: train path: lv-pl/train-* - config_name: lv-pt data_files: - split: train path: lv-pt/train-* - config_name: lv-sk data_files: - split: train path: lv-sk/train-* - config_name: lv-sl data_files: - split: train path: lv-sl/train-* - config_name: lv-sv data_files: - split: train path: lv-sv/train-* - config_name: mt-nl data_files: - split: train path: mt-nl/train-* - config_name: mt-pl data_files: - split: train path: mt-pl/train-* - config_name: mt-pt data_files: - split: train path: mt-pt/train-* - config_name: mt-sk data_files: - split: train path: mt-sk/train-* - config_name: mt-sl data_files: - split: train path: mt-sl/train-* - config_name: mt-sv data_files: - split: train path: mt-sv/train-* - config_name: nl-pl data_files: - split: train path: nl-pl/train-* - config_name: nl-pt data_files: - split: train path: nl-pt/train-* - config_name: nl-sk data_files: - split: train path: nl-sk/train-* - config_name: nl-sl data_files: - split: train path: nl-sl/train-* - config_name: nl-sv data_files: - split: train path: nl-sv/train-* - config_name: pl-pt data_files: - split: train path: pl-pt/train-* - config_name: pl-sk data_files: - split: train path: pl-sk/train-* - config_name: pl-sl data_files: - split: train path: pl-sl/train-* - config_name: pl-sv data_files: - split: train path: pl-sv/train-* - config_name: pt-sk data_files: - split: train path: pt-sk/train-* - config_name: pt-sl data_files: - split: train path: pt-sl/train-* - config_name: pt-sv data_files: - split: train path: pt-sv/train-* - config_name: sk-sl data_files: - split: train path: sk-sl/train-* - config_name: sk-sv data_files: - split: train path: sk-sv/train-* - config_name: sl-sv data_files: - split: train path: sl-sv/train-* --- # Dataset Card for OPUS EUconst ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://opus.nlpl.eu/EUconst/corpus/version/EUconst - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Leaderboard:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Dataset Summary A parallel corpus collected from the European Constitution. EUconst's Numbers: - Languages: 21 - Bitexts: 210 - Number of files: 986 - Number of tokens: 3.01M - Sentence fragments: 0.22M ### Supported Tasks and Leaderboards The underlying task is machine translation. ### Languages The languages in the dataset are: - Czech (`cs`) - Danish (`da`) - German (`de`) - Greek (`el`) - English (`en`) - Spanish (`es`) - Estonian (`et`) - Finnish (`fi`) - French (`fr`) - Irish (`ga`) - Hungarian (`hu`) - Italian (`it`) - Lithuanian (`lt`) - Latvian (`lv`) - Maltese (`mt`) - Dutch (`nl`) - Polish (`pl`) - Portuguese (`pt`) - Slovak (`sk`) - Slovenian (`sl`) - Swedish (`sv`) ## Dataset Structure ### Data Instances ``` { "translation": { "cs": "Celex Test ", "da": "Celex Test " } } ``` ### Data Fields - `translation` (`dict`): Parallel sentences for the pair of languages. ### Data Splits The dataset contains a single "train" split for each language pair. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information If you use any part of the corpus in your own work, please cite the following article: ``` @inproceedings{tiedemann-2012-parallel, title = "Parallel Data, Tools and Interfaces in {OPUS}", author = {Tiedemann, J{\"o}rg}, editor = "Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Do{\u{g}}an, Mehmet U{\u{g}}ur and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios", booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)", month = may, year = "2012", address = "Istanbul, Turkey", publisher = "European Language Resources Association (ELRA)", url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/463_Paper.pdf", pages = "2214--2218", abstract = "This paper presents the current status of OPUS, a growing language resource of parallel corpora and related tools. The focus in OPUS is to provide freely available data sets in various formats together with basic annotation to be useful for applications in computational linguistics, translation studies and cross-linguistic corpus studies. In this paper, we report about new data sets and their features, additional annotation tools and models provided from the website and essential interfaces and on-line services included in the project.", } ``` ### Contributions Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.

tiange/Cap3D

tiange

--- license: odc-by viewer: false task_categories: - text-to-3d - image-to-3d --- ## Dataset Description - **Paper:** [Scalable 3D Captioning with Pretrained Models](https://arxiv.org/abs/2306.07279) - **Paper:** [View Selection for 3D Captioning via Diffusion Ranking](https://arxiv.org/abs/2404.07984) - **Repository**: [Github_Cap3D](https://github.com/crockwell/Cap3D) - **Repository**: [Github_DiffuRank](https://github.com/tiangeluo/DiffuRank) - **Project**: [Project](https://cap3d-um.github.io/) This repository hosts data for [Scalable 3D Captioning with Pretrained Models](https://cap3d-um.github.io/) and [View Selection for 3D Captioning via Diffusion Ranking](http://arxiv.org/abs/2404.07984), including descriptive **captions** for 3D objects in [Objaverse](https://arxiv.org/abs/2212.08051), [Objaverse-XL](https://arxiv.org/pdf/2307.05663.pdf), [ABO](https://arxiv.org/abs/2110.06199), and [ShapeNet](https://arxiv.org/abs/1512.03012). This repo also includes **point clouds** and **rendered images with camera, depth, and MatAlpha information** of Objaverse objects, as well as their Shap-E latent codes. All the captions and data provided by our papers are released under ODC-By 1.0 license. ## Usage Please download and unzip files from [**Page**](https://huggingface.co/datasets/tiange/Cap3D/tree/main) according to your usage. Below is a table listing fiels descriptions, followed by example Python scripts for data loading. | Filename | Description | | -------------------------------------- | ------------------------------------------------------------ | | **Cap3D_automated_Objaverse_full.csv** | By integrating text descriptions initially generated by [Cap3D](https://arxiv.org/abs/2306.07279) and subsequently refined by [DiffuRank](https://arxiv.org/abs/2404.07984), we have produced a total of **1,153,779** 3D-caption pairs. Out of the total, **785,150** pairs have been contributed to the whole [Objaverse](https://arxiv.org/abs/2212.08051) dataset, with the balance for the [Objaverse-XL](https://arxiv.org/pdf/2307.05663.pdf) dataset (specifically the highquality subset described in Section 4.1 Alignment Finetuning of [Objaverse-XL](https://proceedings.neurips.cc/paper_files/paper/2023/file/70364304877b5e767de4e9a2a511be0c-Paper-Datasets_and_Benchmarks.pdf)). For the object identifier in the left column, strings with a length of 32 characters are **UIDs** from Objaverse 1.0 (retrieved using `import objaverse; uids = objaverse.load_uids()`). Strings with a length of 64 characters are **SHA256** hashes provided by Objaverse-XL. | | Cap3D_automated_**ABO**.csv | Our captions generated by [Cap3D](https://arxiv.org/abs/2306.07279) and [DiffuRank](https://arxiv.org/abs/2404.07984) for the [ABO dataset](https://arxiv.org/abs/2110.06199), including both general and compositional descriptions. | | Cap3D_automated_**ShapeNet**.csv | Our captions generated by [Cap3D](https://arxiv.org/abs/2306.07279) and [DiffuRank](https://arxiv.org/abs/2404.07984) for the [ShapeNet dataset](https://arxiv.org/abs/1512.03012). | | **PointCloud_zips** | Provided by [Cap3D](https://arxiv.org/abs/2306.07279) and [DiffuRank](https://arxiv.org/abs/2404.07984), **1,006,782** PointClouds (16,384 colorful points) extracted from Objaverse objects. Saved as `.ply` file. | | PointCloud_zips_**ABO** | Provided by [Cap3D](https://arxiv.org/abs/2306.07279) and [DiffuRank](https://arxiv.org/abs/2404.07984), **7,953** PointClouds (16,384 colorful points) extracted from ABO objects. Saved as `.ply` file. | | PointCloud_zips_**ShapeNet** | Provided by [Cap3D](https://arxiv.org/abs/2306.07279) and [DiffuRank](https://arxiv.org/abs/2404.07984), **52,472** PointClouds (16,384 colorful points) extracted from ShapeNet objects. Saved as `.ply` file. | | **RenderedImage_perobj_zips** | Provided by [DiffuRank](https://arxiv.org/abs/2404.07984), Rendered images for **1,006,782** Objaverse objects. Once unzip `compressed_imgs_perobj_xx.zip` will have multiple zip files which consists of **20** rendered images along with camera details (intrinsic & extrinsic), depth data, and masks ([one example](https://huggingface.co/datasets/tiange/Cap3D/tree/main/RenderedImage_perobj_zips/example_zipfile)). Please specify the unzip path, such as `unzip ed51a51909ee46c780db3a85e821feb2.zip -d ed51a51909ee46c780db3a85e821feb2`. More information are in [here](https://huggingface.co/datasets/tiange/Cap3D/blob/main/RenderedImage_perobj_zips/README.md). | | RenderedImage_perobj_zips_**ABO** | Provided by [DiffuRank](https://arxiv.org/abs/2404.07984), Rendered images for **7,953** ABO objects. Details similar to the above. | | RenderedImage_perobj_zips_**ShapeNet** | Provided by [DiffuRank](https://arxiv.org/abs/2404.07984), Rendered images for **52,472** ShapeNet objects. Similar to the above but with 8 rendered images. | | misc | Including miscellaneous files such as human-authored captions, finetuned models, objaverse pointclouds stored as .pt, shapE latent codes, and etc. Please refer to this [README](https://huggingface.co/datasets/tiange/Cap3D/blob/main/misc/README.md) | ``` python # load our captions import pandas as pd captions = pd.read_csv('Cap3D_automated_Objaverse_full.csv', header=None) ## captions: ## 0 1 ## 0 ed51a51909ee46c780db3a85e821feb2 Matte green rifle with a long barrel, stock, a... ## 1 9110b606f6c547b2980fcb3c8c4b6a1c Rustic single-story building with a weathered ... ## 2 80d9caaa1fa04502af666135196456e1 a pair of purple and black swords with white h... ## 3 28d43a218cd8466a8c1f82b29b71e314 3D model of a cluttered outdoor scene with veg... ## 4 75582285fab442a2ba31733f9c8fae66 Floating terrain piece with grassy landscape a... ## ... ... ... ## 1002417 3623e74f34c1c3c523af6b2bb8ffcbe2d2dce897ef61b9... Abstract 3D composition with human figures and... ## 1002418 64e9f7b7a1fc4c4ec56ed8b5917dfd610930043ac5e15f... 3D object with a rough, irregular pink surface... ## 1002419 fcd089d6a237fee21dfd5f0d6d9b74b2fd1150cdc61c7f... Bright pink abstract 3D model of a building wi... ## 1002420 f812dc980050f2d5f4b37df2a8620372f810dd6456a5f2... Monochromatic gray 3D model of a stylized huma... ## 1002421 77c09500b4d8e4b881e1ce6929d56c23658b87173c0996... Modular futuristic spacecraft with red and ora... ## if u want to obtain the caption for specific UID caption = captions[captions[0] == '80d9caaa1fa04502af666135196456e1'][1].values[0] # load point clouds (unzip https://huggingface.co/datasets/tiange/Cap3D/tree/main/PointCloud_pt_zips) import torch pts = torch.load('Cap3D_pcs_pt/80d9caaa1fa04502af666135196456e1.pt') ## pts.shape == torch.Size([6, 16384]) ``` If you have any questions, please contact [Tiange](mailto:[email protected]) or [Chris](mailto:[email protected]). ## Citation Information If you find our data or code useful, please consider citing: ```bibtex @article{luo2023scalable, title={Scalable 3D Captioning with Pretrained Models}, author={Luo, Tiange and Rockwell, Chris and Lee, Honglak and Johnson, Justin}, journal={arXiv preprint arXiv:2306.07279}, year={2023} } @article{luo2024view, title={View Selection for 3D Captioning via Diffusion Ranking}, author={Luo, Tiange and Johnson, Justin and Lee, Honglak}, journal={arXiv preprint arXiv:2404.07984}, year={2024} } ``` Please cite ***Objaverse*** and ***ABO*** paper accordingly, if you use related data. ``` @inproceedings{deitke2023objaverse, title={Objaverse: A universe of annotated 3d objects}, author={Deitke, Matt and Schwenk, Dustin and Salvador, Jordi and Weihs, Luca and Michel, Oscar and VanderBilt, Eli and Schmidt, Ludwig and Ehsani, Kiana and Kembhavi, Aniruddha and Farhadi, Ali}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={13142--13153}, year={2023} } @article{deitke2024objaverse, title={Objaverse-xl: A universe of 10m+ 3d objects}, author={Deitke, Matt and Liu, Ruoshi and Wallingford, Matthew and Ngo, Huong and Michel, Oscar and Kusupati, Aditya and Fan, Alan and Laforte, Christian and Voleti, Vikram and Gadre, Samir Yitzhak and others}, journal={Advances in Neural Information Processing Systems}, volume={36}, year={2024} } @inproceedings{collins2022abo, title={Abo: Dataset and benchmarks for real-world 3d object understanding}, author={Collins, Jasmine and Goel, Shubham and Deng, Kenan and Luthra, Achleshwar and Xu, Leon and Gundogdu, Erhan and Zhang, Xi and Vicente, Tomas F Yago and Dideriksen, Thomas and Arora, Himanshu and others}, booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition}, pages={21126--21136}, year={2022} } ```

omegalabsinc/omega-multimodal

omegalabsinc

--- license: mit task_categories: - video-text-to-text - video-classification - image-classification - image-to-text - image-to-video - image-feature-extraction - visual-question-answering - audio-classification - audio-to-audio - text-to-audio - text-to-image - text-to-speech - text-to-video tags: - multimodal - AGI - video - anytoany --- # OMEGA Labs Bittensor Subnet: Multimodal Dataset for AGI Research [](https://omegatron.ai) ## Introduction The OMEGA Labs Bittensor Subnet Dataset is a groundbreaking resource for accelerating Artificial General Intelligence (AGI) research and development. This dataset, powered by the Bittensor decentralized network, aims to be the world's largest multimodal dataset, capturing the vast landscape of human knowledge and creation. With over 1 million hours of footage and 30 million+ 2-minute video clips, the OMEGA Labs dataset will offer unparalleled scale and diversity, covering 50+ scenarios and 15,000+ action phrases. By leveraging state-of-the-art models to translate video components into a unified latent space, this dataset enables the development of powerful AGI models and has the potential to transform various industries. ## Key Features - 🌍 **Constant Stream of Fresh Data**: The OMEGA dataset is constantly updated with new entries scraped by miners on Bittensor's decentralized AI network. We estimate that within a few weeks, we can get to 5M+ new videos added daily. - 📈 **Rich Data**: In addition to scale, we are focused on scraping relevant, high quality data. Using [ImageBind](https://imagebind.metademolab.com/demo) embeddings of the submitted videos and corresponding captions, miners are rewarded based on three factors: - **Diversity**: The further away each new datapoint is from existing datapoints (judged by embedding cosine similarity), the higher the reward - **Richness**: The more detailed the caption (judged by cosine similarity between video and submitted caption), the higher the reward - **Relevance**: Miners are asked to scrape data pertaining to handpicked categories, pertinent for building video understanding and training world models. - 🧠 **Latent Representations**: ImageBind embeddings for the video, audio, and caption are pre-computed - 🤖 **Empowering Digital Agents**: Enables the development of intelligent agents that can navigate complex workflows and assist users across platforms. - 📊 **Flexible Metadata**: Filter the dataset to find clips relevant to topics you would like to train on or filter by your desired cosine similarities ## Dataset Structure The OMEGA Labs Bittensor Subnet Dataset consists of the following columns: - `video_id`: Unique identifier for each video clip. - `youtube_id`: The original YouTube video ID. - `description`: Description of the video content. - `views`: Number of views the original YouTube video has received. - `start_time`: Start time of the video clip within the original video. - `end_time`: End time of the video clip within the original video. - `video_embed`: Latent representation of the video content. - `audio_embed`: Latent representation of the audio content. - `description_embed`: Latent representation of the video description. - `description_relevance_score`: Relevance score of the video description to the content. - `query_relevance_score`: Relevance score of the video to the search query. - `query`: The search query used to retrieve the video. - `submitted_at`: Timestamp of when the video was added to the dataset. ## Applications The OMEGA Labs Bittensor Subnet Dataset empowers researchers and developers to push the boundaries of AGI by providing a vast and diverse resource for training and testing multimodal models. Some potential applications include: - **Unified Representation Learning**: Train powerful models that can learn unified representations across modalities. - **Any-to-Any Models**: Develop models capable of translating between different modalities, such as generating videos from text descriptions or vice versa. - **Digital Agents**: Create intelligent agents that can navigate complex workflows and assist users across platforms. - **Immersive Gaming**: Build realistic gaming environments with rich physics and interactions. - **Video Understanding**: Advance the state-of-the-art in video processing tasks such as transcription, motion analysis, object detection, and emotion recognition. ## Say hi! If you're interested in getting in touch, reach out to us on [Twitter](https://twitter.com/omegalabsai)! You can also visit our [Github](https://github.com/omegalabsinc/omegalabs-bittensor-subnet/tree/main) to learn more about how our scraping is done! And if you'd like to learn more about Bittensor, join the [Discord](https://discord.gg/6yZpQ9KV)!

common-canvas/commoncatalog-cc-by-nc-nd

common-canvas

--- license: cc-by-nc-nd-4.0 dataset_info: features: - name: jpg dtype: image - name: blip2_caption dtype: string - name: caption dtype: string - name: licensename dtype: string - name: licenseurl dtype: string - name: width dtype: int32 - name: height dtype: int32 - name: original_width dtype: int32 - name: original_height dtype: int32 - name: photoid dtype: int64 - name: uid dtype: string - name: unickname dtype: string - name: datetaken dtype: timestamp[us] - name: dateuploaded dtype: int64 - name: capturedevice dtype: string - name: title dtype: string - name: usertags dtype: string - name: machinetags dtype: string - name: longitude dtype: float64 - name: latitude dtype: float64 - name: accuracy dtype: int64 - name: pageurl dtype: string - name: downloadurl dtype: string - name: serverid dtype: int64 - name: farmid dtype: int64 - name: secret dtype: string - name: secretoriginal dtype: string - name: ext dtype: string - name: url dtype: string - name: key dtype: string - name: status dtype: string - name: error_message dtype: string - name: exif dtype: string - name: sha256 dtype: string - name: description dtype: string task_categories: - text-to-image language: - en --- # Dataset Card for CommonCatalog CC-BY-NC-ND This dataset is a large collection of high-resolution Creative Common images (composed of different licenses, see paper Table 1 in the Appendix) collected in 2014 from users of Yahoo Flickr. The dataset contains images of up to 4k resolution, making this one of the highest resolution captioned image datasets. ## Dataset Details ### Dataset Description We provide captions synthetic captions to approximately 100 million high resolution images collected from Yahoo Flickr Creative Commons (YFCC). - **Curated by:** Aaron Gokaslan - **Language(s) (NLP):** en - **License:** See relevant yaml tag / dataset name. ### Dataset Sources <!-- Provide the basic links for the dataset. --> - **Repository:** https://github.com/mosaicml/diffusion - **Paper:** https://arxiv.org/abs/2310.16825 - **Demo:** See CommonCanvas Gradios ## Uses We use CommonCatalog to train a family latent diffusion models called CommonCanvas. The goal is to produce a model that is competitive with Stable Diffusion 2, but to do so using an easily accessible dataset of known provenance. Doing so makes replicating the model significantly easier, and provides a clearer mechanism for applying training-data attribution techniques. ### Direct Use Training text-to-image models Training image-to-text models ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> * Commercial use * Crafting content that is offensive or injurious towards individuals, including negative portrayals of their living conditions, cultural backgrounds, religious beliefs, etc. * Deliberately creating or spreading content that is discriminatory or reinforces harmful stereotypes. * Falsely representing individuals without their permission. * Generating sexual content that may be seen by individuals without their consent. * Producing or disseminating false or misleading information. * Creating content that depicts extreme violence or bloodshed. * Distributing content that modifies copyrighted or licensed material in a way that breaches its usage terms. ## Dataset Structure The dataset is divided into 10 subsets each containing parquets about 4GB each. Each subfolder within contains a resolution range of the images and their respective aspect ratios. The dataset is also divided along images licensed for commercial use (C) and those that are not (NC). ## Dataset Creation ### Curation Rationale Creating a standardized, accessible dataset with synthetic caption and releasing it so other people can train on a common dataset for open source image generation. ### Source Data Yahoo Flickr Creative Commons 100M Dataset and Synthetically Generated Caption Data. #### Data Collection and Processing All synthetic captions were generated with BLIP2. See paper for more details. #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> Users of Flickr ## Bias, Risks, and Limitations See Yahoo Flickr Creative Commons 100M dataset for more information. The information was collected circa 2014 and known to have a bias towards internet connected Western countries. Some areas such as the global south lack representation. ## Citation **BibTeX:** ``` @article{gokaslan2023commoncanvas, title={CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images}, author={Gokaslan, Aaron and Cooper, A Feder and Collins, Jasmine and Seguin, Landan and Jacobson, Austin and Patel, Mihir and Frankle, Jonathan and Stephenson, Cory and Kuleshov, Volodymyr}, journal={arXiv preprint arXiv:2310.16825}, year={2023} } ``` ## Dataset Card Authors [Aaron Gokaslan](https://huggingface.co/Skylion007) ## Dataset Card Contact [Aaron Gokaslan](https://huggingface.co/Skylion007)

taesiri/arxiv_audio

taesiri

--- license: cc-by-4.0 ---

nyu-mll/blimp

nyu-mll

--- annotations_creators: - crowdsourced language_creators: - machine-generated language: - en license: - cc-by-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: - acceptability-classification paperswithcode_id: blimp pretty_name: BLiMP dataset_info: - config_name: adjunct_island features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 165894 num_examples: 1000 download_size: 62231 dataset_size: 165894 - config_name: anaphor_gender_agreement features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 130918 num_examples: 1000 download_size: 39201 dataset_size: 130918 - config_name: anaphor_number_agreement features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 139879 num_examples: 1000 download_size: 41547 dataset_size: 139879 - config_name: animate_subject_passive features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 144423 num_examples: 1000 download_size: 47282 dataset_size: 144423 - config_name: animate_subject_trans features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 127798 num_examples: 1000 download_size: 49651 dataset_size: 127798 - config_name: causative features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 122772 num_examples: 1000 download_size: 48963 dataset_size: 122772 - config_name: complex_NP_island features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 198972 num_examples: 1000 download_size: 78211 dataset_size: 198972 - config_name: coordinate_structure_constraint_complex_left_branch features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 210912 num_examples: 1000 download_size: 67908 dataset_size: 210912 - config_name: coordinate_structure_constraint_object_extraction features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 171655 num_examples: 1000 download_size: 51584 dataset_size: 171655 - config_name: determiner_noun_agreement_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 156120 num_examples: 1000 download_size: 49893 dataset_size: 156120 - config_name: determiner_noun_agreement_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 156204 num_examples: 1000 download_size: 49527 dataset_size: 156204 - config_name: determiner_noun_agreement_irregular_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 164473 num_examples: 1000 download_size: 47274 dataset_size: 164473 - config_name: determiner_noun_agreement_irregular_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 161074 num_examples: 1000 download_size: 47422 dataset_size: 161074 - config_name: determiner_noun_agreement_with_adj_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 179666 num_examples: 1000 download_size: 56346 dataset_size: 179666 - config_name: determiner_noun_agreement_with_adj_irregular_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 184529 num_examples: 1000 download_size: 54405 dataset_size: 184529 - config_name: determiner_noun_agreement_with_adj_irregular_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 184396 num_examples: 1000 download_size: 54064 dataset_size: 184396 - config_name: determiner_noun_agreement_with_adjective_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 185126 num_examples: 1000 download_size: 55682 dataset_size: 185126 - config_name: distractor_agreement_relational_noun features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 191473 num_examples: 1000 download_size: 59641 dataset_size: 191473 - config_name: distractor_agreement_relative_clause features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 216756 num_examples: 1000 download_size: 77897 dataset_size: 216756 - config_name: drop_argument features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 109806 num_examples: 1000 download_size: 39961 dataset_size: 109806 - config_name: ellipsis_n_bar_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 217590 num_examples: 1000 download_size: 92776 dataset_size: 217590 - config_name: ellipsis_n_bar_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 233161 num_examples: 1000 download_size: 98882 dataset_size: 233161 - config_name: existential_there_object_raising features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 223741 num_examples: 1000 download_size: 76641 dataset_size: 223741 - config_name: existential_there_quantifiers_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 162931 num_examples: 1000 download_size: 51576 dataset_size: 162931 - config_name: existential_there_quantifiers_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 164826 num_examples: 1000 download_size: 52092 dataset_size: 164826 - config_name: existential_there_subject_raising features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 200063 num_examples: 1000 download_size: 59519 dataset_size: 200063 - config_name: expletive_it_object_raising features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 238615 num_examples: 1000 download_size: 88607 dataset_size: 238615 - config_name: inchoative features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 104319 num_examples: 1000 download_size: 39842 dataset_size: 104319 - config_name: intransitive features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 111097 num_examples: 1000 download_size: 42387 dataset_size: 111097 - config_name: irregular_past_participle_adjectives features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 144661 num_examples: 1000 download_size: 36654 dataset_size: 144661 - config_name: irregular_past_participle_verbs features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 125692 num_examples: 1000 download_size: 37297 dataset_size: 125692 - config_name: irregular_plural_subject_verb_agreement_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 165584 num_examples: 1000 download_size: 50725 dataset_size: 165584 - config_name: irregular_plural_subject_verb_agreement_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 153843 num_examples: 1000 download_size: 42707 dataset_size: 153843 - config_name: left_branch_island_echo_question features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 147840 num_examples: 1000 download_size: 50481 dataset_size: 147840 - config_name: left_branch_island_simple_question features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 150060 num_examples: 1000 download_size: 50293 dataset_size: 150060 - config_name: matrix_question_npi_licensor_present features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 153262 num_examples: 1000 download_size: 51899 dataset_size: 153262 - config_name: npi_present_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 138465 num_examples: 1000 download_size: 51981 dataset_size: 138465 - config_name: npi_present_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 127636 num_examples: 1000 download_size: 51661 dataset_size: 127636 - config_name: only_npi_licensor_present features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 148516 num_examples: 1000 download_size: 51361 dataset_size: 148516 - config_name: only_npi_scope features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 208902 num_examples: 1000 download_size: 84970 dataset_size: 208902 - config_name: passive_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 145882 num_examples: 1000 download_size: 53931 dataset_size: 145882 - config_name: passive_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 113960 num_examples: 1000 download_size: 40499 dataset_size: 113960 - config_name: principle_A_c_command features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 188490 num_examples: 1000 download_size: 67867 dataset_size: 188490 - config_name: principle_A_case_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 170398 num_examples: 1000 download_size: 61092 dataset_size: 170398 - config_name: principle_A_case_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 170412 num_examples: 1000 download_size: 56430 dataset_size: 170412 - config_name: principle_A_domain_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 171170 num_examples: 1000 download_size: 59120 dataset_size: 171170 - config_name: principle_A_domain_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 165333 num_examples: 1000 download_size: 58464 dataset_size: 165333 - config_name: principle_A_domain_3 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 158998 num_examples: 1000 download_size: 52859 dataset_size: 158998 - config_name: principle_A_reconstruction features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 152104 num_examples: 1000 download_size: 44480 dataset_size: 152104 - config_name: regular_plural_subject_verb_agreement_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 158819 num_examples: 1000 download_size: 49466 dataset_size: 158819 - config_name: regular_plural_subject_verb_agreement_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 153609 num_examples: 1000 download_size: 43365 dataset_size: 153609 - config_name: sentential_negation_npi_licensor_present features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 171864 num_examples: 1000 download_size: 54830 dataset_size: 171864 - config_name: sentential_negation_npi_scope features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 232098 num_examples: 1000 download_size: 90157 dataset_size: 232098 - config_name: sentential_subject_island features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 172432 num_examples: 1000 download_size: 56666 dataset_size: 172432 - config_name: superlative_quantifiers_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 159290 num_examples: 1000 download_size: 48453 dataset_size: 159290 - config_name: superlative_quantifiers_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 159340 num_examples: 1000 download_size: 50480 dataset_size: 159340 - config_name: tough_vs_raising_1 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 148636 num_examples: 1000 download_size: 44779 dataset_size: 148636 - config_name: tough_vs_raising_2 features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 169684 num_examples: 1000 download_size: 61465 dataset_size: 169684 - config_name: transitive features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 133104 num_examples: 1000 download_size: 55090 dataset_size: 133104 - config_name: wh_island features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 142340 num_examples: 1000 download_size: 52808 dataset_size: 142340 - config_name: wh_questions_object_gap features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 193045 num_examples: 1000 download_size: 70049 dataset_size: 193045 - config_name: wh_questions_subject_gap features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 195593 num_examples: 1000 download_size: 71632 dataset_size: 195593 - config_name: wh_questions_subject_gap_long_distance features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 268270 num_examples: 1000 download_size: 98913 dataset_size: 268270 - config_name: wh_vs_that_no_gap features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 188872 num_examples: 1000 download_size: 71710 dataset_size: 188872 - config_name: wh_vs_that_no_gap_long_distance features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 247039 num_examples: 1000 download_size: 95504 dataset_size: 247039 - config_name: wh_vs_that_with_gap features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 173386 num_examples: 1000 download_size: 60291 dataset_size: 173386 - config_name: wh_vs_that_with_gap_long_distance features: - name: sentence_good dtype: string - name: sentence_bad dtype: string - name: field dtype: string - name: linguistics_term dtype: string - name: UID dtype: string - name: simple_LM_method dtype: bool - name: one_prefix_method dtype: bool - name: two_prefix_method dtype: bool - name: lexically_identical dtype: bool - name: pair_id dtype: int32 splits: - name: train num_bytes: 231595 num_examples: 1000 download_size: 84147 dataset_size: 231595 configs: - config_name: adjunct_island data_files: - split: train path: adjunct_island/train-* - config_name: anaphor_gender_agreement data_files: - split: train path: anaphor_gender_agreement/train-* - config_name: anaphor_number_agreement data_files: - split: train path: anaphor_number_agreement/train-* - config_name: animate_subject_passive data_files: - split: train path: animate_subject_passive/train-* - config_name: animate_subject_trans data_files: - split: train path: animate_subject_trans/train-* - config_name: causative data_files: - split: train path: causative/train-* - config_name: complex_NP_island data_files: - split: train path: complex_NP_island/train-* - config_name: coordinate_structure_constraint_complex_left_branch data_files: - split: train path: coordinate_structure_constraint_complex_left_branch/train-* - config_name: coordinate_structure_constraint_object_extraction data_files: - split: train path: coordinate_structure_constraint_object_extraction/train-* - config_name: determiner_noun_agreement_1 data_files: - split: train path: determiner_noun_agreement_1/train-* - config_name: determiner_noun_agreement_2 data_files: - split: train path: determiner_noun_agreement_2/train-* - config_name: determiner_noun_agreement_irregular_1 data_files: - split: train path: determiner_noun_agreement_irregular_1/train-* - config_name: determiner_noun_agreement_irregular_2 data_files: - split: train path: determiner_noun_agreement_irregular_2/train-* - config_name: determiner_noun_agreement_with_adj_2 data_files: - split: train path: determiner_noun_agreement_with_adj_2/train-* - config_name: determiner_noun_agreement_with_adj_irregular_1 data_files: - split: train path: determiner_noun_agreement_with_adj_irregular_1/train-* - config_name: determiner_noun_agreement_with_adj_irregular_2 data_files: - split: train path: determiner_noun_agreement_with_adj_irregular_2/train-* - config_name: determiner_noun_agreement_with_adjective_1 data_files: - split: train path: determiner_noun_agreement_with_adjective_1/train-* - config_name: distractor_agreement_relational_noun data_files: - split: train path: distractor_agreement_relational_noun/train-* - config_name: distractor_agreement_relative_clause data_files: - split: train path: distractor_agreement_relative_clause/train-* - config_name: drop_argument data_files: - split: train path: drop_argument/train-* - config_name: ellipsis_n_bar_1 data_files: - split: train path: ellipsis_n_bar_1/train-* - config_name: ellipsis_n_bar_2 data_files: - split: train path: ellipsis_n_bar_2/train-* - config_name: existential_there_object_raising data_files: - split: train path: existential_there_object_raising/train-* - config_name: existential_there_quantifiers_1 data_files: - split: train path: existential_there_quantifiers_1/train-* - config_name: existential_there_quantifiers_2 data_files: - split: train path: existential_there_quantifiers_2/train-* - config_name: existential_there_subject_raising data_files: - split: train path: existential_there_subject_raising/train-* - config_name: expletive_it_object_raising data_files: - split: train path: expletive_it_object_raising/train-* - config_name: inchoative data_files: - split: train path: inchoative/train-* - config_name: intransitive data_files: - split: train path: intransitive/train-* - config_name: irregular_past_participle_adjectives data_files: - split: train path: irregular_past_participle_adjectives/train-* - config_name: irregular_past_participle_verbs data_files: - split: train path: irregular_past_participle_verbs/train-* - config_name: irregular_plural_subject_verb_agreement_1 data_files: - split: train path: irregular_plural_subject_verb_agreement_1/train-* - config_name: irregular_plural_subject_verb_agreement_2 data_files: - split: train path: irregular_plural_subject_verb_agreement_2/train-* - config_name: left_branch_island_echo_question data_files: - split: train path: left_branch_island_echo_question/train-* - config_name: left_branch_island_simple_question data_files: - split: train path: left_branch_island_simple_question/train-* - config_name: matrix_question_npi_licensor_present data_files: - split: train path: matrix_question_npi_licensor_present/train-* - config_name: npi_present_1 data_files: - split: train path: npi_present_1/train-* - config_name: npi_present_2 data_files: - split: train path: npi_present_2/train-* - config_name: only_npi_licensor_present data_files: - split: train path: only_npi_licensor_present/train-* - config_name: only_npi_scope data_files: - split: train path: only_npi_scope/train-* - config_name: passive_1 data_files: - split: train path: passive_1/train-* - config_name: passive_2 data_files: - split: train path: passive_2/train-* - config_name: principle_A_c_command data_files: - split: train path: principle_A_c_command/train-* - config_name: principle_A_case_1 data_files: - split: train path: principle_A_case_1/train-* - config_name: principle_A_case_2 data_files: - split: train path: principle_A_case_2/train-* - config_name: principle_A_domain_1 data_files: - split: train path: principle_A_domain_1/train-* - config_name: principle_A_domain_2 data_files: - split: train path: principle_A_domain_2/train-* - config_name: principle_A_domain_3 data_files: - split: train path: principle_A_domain_3/train-* - config_name: principle_A_reconstruction data_files: - split: train path: principle_A_reconstruction/train-* - config_name: regular_plural_subject_verb_agreement_1 data_files: - split: train path: regular_plural_subject_verb_agreement_1/train-* - config_name: regular_plural_subject_verb_agreement_2 data_files: - split: train path: regular_plural_subject_verb_agreement_2/train-* - config_name: sentential_negation_npi_licensor_present data_files: - split: train path: sentential_negation_npi_licensor_present/train-* - config_name: sentential_negation_npi_scope data_files: - split: train path: sentential_negation_npi_scope/train-* - config_name: sentential_subject_island data_files: - split: train path: sentential_subject_island/train-* - config_name: superlative_quantifiers_1 data_files: - split: train path: superlative_quantifiers_1/train-* - config_name: superlative_quantifiers_2 data_files: - split: train path: superlative_quantifiers_2/train-* - config_name: tough_vs_raising_1 data_files: - split: train path: tough_vs_raising_1/train-* - config_name: tough_vs_raising_2 data_files: - split: train path: tough_vs_raising_2/train-* - config_name: transitive data_files: - split: train path: transitive/train-* - config_name: wh_island data_files: - split: train path: wh_island/train-* - config_name: wh_questions_object_gap data_files: - split: train path: wh_questions_object_gap/train-* - config_name: wh_questions_subject_gap data_files: - split: train path: wh_questions_subject_gap/train-* - config_name: wh_questions_subject_gap_long_distance data_files: - split: train path: wh_questions_subject_gap_long_distance/train-* - config_name: wh_vs_that_no_gap data_files: - split: train path: wh_vs_that_no_gap/train-* - config_name: wh_vs_that_no_gap_long_distance data_files: - split: train path: wh_vs_that_no_gap_long_distance/train-* - config_name: wh_vs_that_with_gap data_files: - split: train path: wh_vs_that_with_gap/train-* - config_name: wh_vs_that_with_gap_long_distance data_files: - split: train path: wh_vs_that_with_gap_long_distance/train-* --- # Dataset Card for "blimp" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** https://github.com/alexwarstadt/blimp - **Paper:** [BLiMP: The Benchmark of Linguistic Minimal Pairs for English](https://doi.org/10.1162/tacl_a_00321) - **Paper:** https://arxiv.org/abs/1912.00582 - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of downloaded dataset files:** 29.58 MB - **Size of the generated dataset:** 11.45 MB - **Total amount of disk used:** 41.03 MB ### Dataset Summary BLiMP is a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English. BLiMP consists of 67 sub-datasets, each containing 1000 minimal pairs isolating specific contrasts in syntax, morphology, or semantics. The data is automatically generated according to expert-crafted grammars. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### adjunct_island - **Size of downloaded dataset files:** 0.36 MB - **Size of the generated dataset:** 0.17 MB - **Total amount of disk used:** 0.52 MB An example of 'train' looks as follows. ``` { "UID": "tough_vs_raising_1", "field": "syntax_semantics", "lexically_identical": false, "linguistics_term": "control_raising", "one_prefix_method": false, "pair_id": 2, "sentence_bad": "Benjamin's tutor was certain to boast about.", "sentence_good": "Benjamin's tutor was easy to boast about.", "simple_LM_method": true, "two_prefix_method": false } ``` #### anaphor_gender_agreement - **Size of downloaded dataset files:** 0.44 MB - **Size of the generated dataset:** 0.14 MB - **Total amount of disk used:** 0.57 MB An example of 'train' looks as follows. ``` { "UID": "tough_vs_raising_1", "field": "syntax_semantics", "lexically_identical": false, "linguistics_term": "control_raising", "one_prefix_method": false, "pair_id": 2, "sentence_bad": "Benjamin's tutor was certain to boast about.", "sentence_good": "Benjamin's tutor was easy to boast about.", "simple_LM_method": true, "two_prefix_method": false } ``` #### anaphor_number_agreement - **Size of downloaded dataset files:** 0.45 MB - **Size of the generated dataset:** 0.14 MB - **Total amount of disk used:** 0.59 MB An example of 'train' looks as follows. ``` { "UID": "tough_vs_raising_1", "field": "syntax_semantics", "lexically_identical": false, "linguistics_term": "control_raising", "one_prefix_method": false, "pair_id": 2, "sentence_bad": "Benjamin's tutor was certain to boast about.", "sentence_good": "Benjamin's tutor was easy to boast about.", "simple_LM_method": true, "two_prefix_method": false } ``` #### animate_subject_passive - **Size of downloaded dataset files:** 0.46 MB - **Size of the generated dataset:** 0.15 MB - **Total amount of disk used:** 0.61 MB An example of 'train' looks as follows. ``` { "UID": "tough_vs_raising_1", "field": "syntax_semantics", "lexically_identical": false, "linguistics_term": "control_raising", "one_prefix_method": false, "pair_id": 2, "sentence_bad": "Benjamin's tutor was certain to boast about.", "sentence_good": "Benjamin's tutor was easy to boast about.", "simple_LM_method": true, "two_prefix_method": false } ``` #### animate_subject_trans - **Size of downloaded dataset files:** 0.43 MB - **Size of the generated dataset:** 0.13 MB - **Total amount of disk used:** 0.57 MB An example of 'train' looks as follows. ``` { "UID": "tough_vs_raising_1", "field": "syntax_semantics", "lexically_identical": false, "linguistics_term": "control_raising", "one_prefix_method": false, "pair_id": 2, "sentence_bad": "Benjamin's tutor was certain to boast about.", "sentence_good": "Benjamin's tutor was easy to boast about.", "simple_LM_method": true, "two_prefix_method": false } ``` ### Data Fields The data fields are the same among all splits. #### adjunct_island - `sentence_good`: a `string` feature. - `sentence_bad`: a `string` feature. - `field`: a `string` feature. - `linguistics_term`: a `string` feature. - `UID`: a `string` feature. - `simple_LM_method`: a `bool` feature. - `one_prefix_method`: a `bool` feature. - `two_prefix_method`: a `bool` feature. - `lexically_identical`: a `bool` feature. - `pair_id`: a `int32` feature. #### anaphor_gender_agreement - `sentence_good`: a `string` feature. - `sentence_bad`: a `string` feature. - `field`: a `string` feature. - `linguistics_term`: a `string` feature. - `UID`: a `string` feature. - `simple_LM_method`: a `bool` feature. - `one_prefix_method`: a `bool` feature. - `two_prefix_method`: a `bool` feature. - `lexically_identical`: a `bool` feature. - `pair_id`: a `int32` feature. #### anaphor_number_agreement - `sentence_good`: a `string` feature. - `sentence_bad`: a `string` feature. - `field`: a `string` feature. - `linguistics_term`: a `string` feature. - `UID`: a `string` feature. - `simple_LM_method`: a `bool` feature. - `one_prefix_method`: a `bool` feature. - `two_prefix_method`: a `bool` feature. - `lexically_identical`: a `bool` feature. - `pair_id`: a `int32` feature. #### animate_subject_passive - `sentence_good`: a `string` feature. - `sentence_bad`: a `string` feature. - `field`: a `string` feature. - `linguistics_term`: a `string` feature. - `UID`: a `string` feature. - `simple_LM_method`: a `bool` feature. - `one_prefix_method`: a `bool` feature. - `two_prefix_method`: a `bool` feature. - `lexically_identical`: a `bool` feature. - `pair_id`: a `int32` feature. #### animate_subject_trans - `sentence_good`: a `string` feature. - `sentence_bad`: a `string` feature. - `field`: a `string` feature. - `linguistics_term`: a `string` feature. - `UID`: a `string` feature. - `simple_LM_method`: a `bool` feature. - `one_prefix_method`: a `bool` feature. - `two_prefix_method`: a `bool` feature. - `lexically_identical`: a `bool` feature. - `pair_id`: a `int32` feature. ### Data Splits | name |train| |------------------------|----:| |adjunct_island | 1000| |anaphor_gender_agreement| 1000| |anaphor_number_agreement| 1000| |animate_subject_passive | 1000| |animate_subject_trans | 1000| ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information BLiMP is distributed under a [CC-BY](https://creativecommons.org/licenses/by/4.0/) license. Source: https://github.com/alexwarstadt/blimp#license ### Citation Information ``` @article{warstadt2020blimp, author = {Warstadt, Alex and Parrish, Alicia and Liu, Haokun and Mohananey, Anhad and Peng, Wei and Wang, Sheng-Fu and Bowman, Samuel R.}, title = {BLiMP: The Benchmark of Linguistic Minimal Pairs for English}, journal = {Transactions of the Association for Computational Linguistics}, volume = {8}, number = {}, pages = {377-392}, year = {2020}, doi = {10.1162/tacl\_a\_00321}, URL = {https://doi.org/10.1162/tacl_a_00321}, eprint = {https://doi.org/10.1162/tacl_a_00321}, abstract = { We introduce The Benchmark of Linguistic Minimal Pairs (BLiMP),1 a challenge set for evaluating the linguistic knowledge of language models (LMs) on major grammatical phenomena in English. BLiMP consists of 67 individual datasets, each containing 1,000 minimal pairs—that is, pairs of minimally different sentences that contrast in grammatical acceptability and isolate specific phenomenon in syntax, morphology, or semantics. We generate the data according to linguist-crafted grammar templates, and human aggregate agreement with the labels is 96.4\%. We evaluate n-gram, LSTM, and Transformer (GPT-2 and Transformer-XL) LMs by observing whether they assign a higher probability to the acceptable sentence in each minimal pair. We find that state-of-the-art models identify morphological contrasts related to agreement reliably, but they struggle with some subtle semantic and syntactic phenomena, such as negative polarity items and extraction islands. } } ``` #### Errata Some results were misreported in the published TACL version. Please refer to the corrected version on arXiv: https://arxiv.org/abs/1912.00582 ### Contributions Thanks to [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

mikeboss/FIP1

mikeboss

--- license: cc-by-4.0 size_categories: - 1K<n<10K dataset_info: features: - name: plot_uid dtype: string - name: yearsite_uid dtype: string - name: crop_type dtype: string - name: experiment_number dtype: uint8 - name: plot_number dtype: int16 - name: range dtype: uint8 - name: row dtype: uint8 - name: lot dtype: uint8 - name: latitude dtype: float64 - name: longitude dtype: float64 - name: spatial_check dtype: int32 - name: sowing_date dtype: date32 - name: harvest_date dtype: date32 - name: harvest_year dtype: uint16 - name: images sequence: string - name: image_dates sequence: date32 - name: image_times sequence: time32[s] - name: alignment_plot_soil_polygons sequence: sequence: sequence: float16 - name: alignment_num_steps sequence: uint8 - name: alignment_dates sequence: date32 - name: alignment_times sequence: time32[s] - name: alignment_initial_date dtype: date32 - name: alignment_inner_plot_transform sequence: sequence: float16 - name: inner_plot_images sequence: string - name: image_inner_plot_transforms sequence: sequence: sequence: float16 - name: genotype_id dtype: string - name: marker_biallelic_codes sequence: uint8 - name: marker_metadata_strings sequence: string - name: canopy_cover_values sequence: float16 - name: canopy_cover_dates sequence: date32 - name: canopy_cover_trait_id dtype: uint8 - name: canopy_cover_trait_name dtype: string - name: canopy_cover_method_id dtype: uint16 - name: canopy_cover_method_name dtype: string - name: canopy_cover_si_unit dtype: string - name: canopy_cover_responsible dtype: string - name: height_values sequence: float16 - name: height_dates sequence: date32 - name: height_trait_id dtype: uint8 - name: height_trait_name dtype: string - name: height_method_id dtype: uint16 - name: height_method_name dtype: string - name: height_si_unit dtype: string - name: height_responsible dtype: string - name: spike_count_values sequence: float16 - name: spike_count_dates sequence: date32 - name: spike_count_trait_id dtype: uint8 - name: spike_count_trait_name dtype: string - name: spike_count_method_id dtype: uint16 - name: spike_count_method_name dtype: string - name: spike_count_si_unit dtype: string - name: spike_count_responsible dtype: string - name: senescence_values sequence: float16 - name: senescence_dates sequence: date32 - name: senescence_trait_id dtype: uint8 - name: senescence_trait_name dtype: string - name: senescence_method_id dtype: uint16 - name: senescence_method_name dtype: string - name: senescence_si_unit dtype: string - name: senescence_responsible dtype: string - name: heading_value dtype: float16 - name: heading_date dtype: date32 - name: heading_blue dtype: float16 - name: heading_heritability dtype: float16 - name: heading_trait_id dtype: uint8 - name: heading_trait_name dtype: string - name: heading_method_id dtype: uint16 - name: heading_method_name dtype: string - name: heading_si_unit dtype: string - name: heading_responsible dtype: string - name: height_final_value dtype: float16 - name: height_final_date dtype: date32 - name: height_final_blue dtype: float16 - name: height_final_heritability dtype: float16 - name: height_final_trait_id dtype: uint8 - name: height_final_trait_name dtype: string - name: height_final_method_id dtype: uint16 - name: height_final_method_name dtype: string - name: height_final_si_unit dtype: string - name: height_final_responsible dtype: string - name: yield_value dtype: float16 - name: yield_date dtype: date32 - name: yield_blue dtype: float16 - name: yield_heritability dtype: float16 - name: yield_trait_id dtype: uint8 - name: yield_trait_name dtype: string - name: yield_method_id dtype: uint16 - name: yield_method_name dtype: string - name: yield_si_unit dtype: string - name: yield_responsible dtype: string - name: yield_adjusted_value dtype: float16 - name: yield_adjusted_date dtype: date32 - name: yield_adjusted_blue dtype: float16 - name: yield_adjusted_heritability dtype: float16 - name: yield_adjusted_trait_id dtype: uint8 - name: yield_adjusted_trait_name dtype: string - name: yield_adjusted_method_id dtype: uint16 - name: yield_adjusted_method_name dtype: string - name: yield_adjusted_si_unit dtype: string - name: yield_adjusted_responsible dtype: string - name: protein_value dtype: float16 - name: protein_date dtype: date32 - name: protein_blue dtype: float16 - name: protein_heritability dtype: float16 - name: protein_trait_id dtype: uint8 - name: protein_trait_name dtype: string - name: protein_method_id dtype: uint16 - name: protein_method_name dtype: string - name: protein_si_unit dtype: string - name: protein_responsible dtype: string - name: temperature_air_10cm_values sequence: float16 - name: temperature_air_10cm_dates sequence: date32 - name: temperature_air_10cm_times sequence: time32[s] - name: temperature_air_200cm_values sequence: float16 - name: temperature_air_200cm_dates sequence: date32 - name: temperature_air_200cm_times sequence: time32[s] - name: temperature_soil_5cm_values sequence: float16 - name: temperature_soil_5cm_dates sequence: date32 - name: temperature_soil_5cm_times sequence: time32[s] - name: humidity_air_10cm_values sequence: float16 - name: humidity_air_10cm_dates sequence: date32 - name: humidity_air_10cm_times sequence: time32[s] - name: humidity_air_200cm_values sequence: float16 - name: humidity_air_200cm_dates sequence: date32 - name: humidity_air_200cm_times sequence: time32[s] - name: precipitation_200cm_values sequence: float16 - name: precipitation_200cm_dates sequence: date32 - name: precipitation_200cm_times sequence: time32[s] - name: irradiance_solar_200cm_values sequence: float16 - name: irradiance_solar_200cm_dates sequence: date32 - name: irradiance_solar_200cm_times sequence: time32[s] splits: - name: train num_bytes: 3196147599 num_examples: 2930 - name: validation num_bytes: 673564266 num_examples: 380 - name: test_plot num_bytes: 443112041 num_examples: 250 - name: test_genotype num_bytes: 436276173 num_examples: 246 - name: test_environment num_bytes: 161988616 num_examples: 190 - name: test_genotype_environment num_bytes: 109816338 num_examples: 62 download_size: 1375752424 dataset_size: 5020905033 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test_plot path: data/test_plot-* - split: test_genotype path: data/test_genotype-* - split: test_environment path: data/test_environment-* - split: test_genotype_environment path: data/test_genotype_environment-* tags: - phenotyping - wheat - plant - regression - trait - pheno task_categories: - time-series-forecasting - feature-extraction - tabular-regression ---  # The FIP 1.0 Data Set: Highly Resolved Annotated Image Time Series of 4,000 Wheat Plots Grown in Six Years ## Dataset Details ### Dataset Description We provide time series data for more than 4,000 wheat plots, including aligned high-resolution image sequences totaling more than 151,000 aligned images across six years. Measurement data for eight key wheat traits is included, namely canopy cover values, plant heights, wheat head counts, senescence ratings, heading date, final plant height, grain yield, and protein content. Genetic marker information and environmental data complement the time series. Data quality is demonstrated through heritability analyses and genomic prediction models, achieving accuracies aligned with previous research. - **Curated by:** Mike Boss, Lukas Roth, Norbert Kirchgessner - **License:** CC-BY ### Dataset Sources <!-- Provide the basic links for the dataset. --> - **Data:** [https://doi.org/20.500.11850/697773](https://doi.org/20.500.11850/697773) > Note that only the aligned inner plot images are contained in this repo, the original image paths point to */data/image* and have to be downloaded separately from the [ETH research collection](https://doi.org/10.3929/ethz-b-000697773). - **Paper:** [https://doi.org/10.1101/2024.10.04.616624](https://doi.org/10.1101/2024.10.04.616624) ## Uses We see the largest re-use potential of the presented data set for the development and evaluation of new modelling and prediction approaches in crop genomics and phenomics. The multi-faceted data set allows modelling approaches on various levels: - Genomic prediction approaches that include genotype-environment interactions: The presented data enhance the data by Gogna et al. by 6 environments, totalling to 14 environments that are characterized by environmental covariates. The presented benchmark of a genomic prediction with random regressions to environmental covariates provides a baseline that novel approaches can challenge. - Modelling plant growth and development with longitudinal modelling approaches: The four low-level traits canopy cover, plant height, wheat head count and senescence cover the full growing season of winter wheat in 6 environments that are characterized by environmental covariates. Baseline approaches for plant height growth modelling, canopy cover growth modelling and senescence dynamics modelling for subsets of the presented data exist. - Image-based phenomic predictions and combined phenomic and genomic prediction approaches: The dense time series of images allow training and analysing end-to-end modelling approaches (e.g., deep learning based) that predict target traits such as yield based on images. ## Dataset Structure The data is structured such that each row contains all data for a plot in a given year. The plot can be identified by it's *plot_uid* which is also available in parts as *yearsite_uid*, *crop_type*, etc. If data does not exist for a certain plot it is *None*, while if time series data does not exist for a certain date it is simply not present. The image data is in the *images* and *inner_plot_images* colums. *images* are the original images while *inner_plot_images* are aligned cutouts of the inner wheat plot. Trait data is included as the values in *trait_value(s)* and the dates *trait_date(s)*. Marker data includes an anyomized *genotype_id* string, biallelic codes and corresponding metadata strings. Enviroment variables are also included as *_value(s)*, *_date(s)* and in addition *_time(s)*. The sowing date, harvest date and harvest_year are included. The data set includes additional data used for the creation of the data set itself such as the alignments. ## Dataset Creation ### Curation Rationale Winter wheat provides a crucial share of calories for human nutrition, with global demand steadily increasing. However, crop production faces challenges due to limited resources like water, agrochemicals, and land. Climate change further threatens crop yields, necessitating responsible and efficient resource use. Crop yields are substantially driven by complex interactions between plant genetics and environmental factors. For instance, genes involved in fruit formation interact with temperatures at flowering, influencing growth and yield potential. Limited phenotyping data is seen as the major reason for the incomplete understanding of such genotype-environment interactions. HTFP was developed to address this data gap. Imaging HTFP platforms allow researchers to monitor crop canopy development over time, generating dense time series data of plant growth. There are many approaches to process such data ranging from extracting traits at critical time points to modeling growth dynamics and finally using end-to-end methods that directly analyze image time series. This data set aims to provide a comprehensive foundation for these diverse approaches. Our goal is to foster collaboration between plant physiology, biometrics, and computer vision research, ultimately improving the ability to predict genotype-environment interactions for current and future climates. ### Source Data The FIP at ETH was established in 2015 to collect image time series of crops growing under realistic field conditions. The FIP's cable carrying system is capable of carrying a 90 kg sensor head. The original sensor head, hereafter referred to as the FIP 1.0 head, was equipped with a red, green, and blue (RGB) camera and a TLS, among other sensors. Wheat field experiments were observed using FIP 1.0 over an eight-year period from 2015 to 2022, yielding six years of data collection, with 2015 and 2020 excluded due to incomplete measuring seasons . Up to three times a week, RGB images of all experimental units (so-called `plots') were collected, and plant heights were measured simultaneously using either the TLS (2016, 2017) or drones (2018--2022) . In 2023, the FIP 1.0 sensor head was replaced with a new, multi-view RGB sensor head. The described data set includes all RGB and height data collected in winter wheat experiments up to this replacement. The area of approximately one ha that the FIP can monitor is divided into six smaller parts (so-called `lots') that are integrated into a crop rotation. The two FIP lots dedicated to winter wheat provide space for ~350 genotypes, replicated once per lot. For the first three years (2016--2018), the GABI-WHEAT panel was grown as the genotype set. From 2019--2022, a subset of the GABI-WHEAT panel was grown in addition to other genotypes . The GABI-WHEAT panel consists of registered genotypes from different climatic regions of Europe . Genetic marker data and MET data from eight year-locations for GABI-WHEAT are publicly available. The GABI-WHEAT panel was largely superseded by the Swiss breeding set in 2021 . This new set primarily consists of eighth-generation (F8) breeding genotypes. For the Swiss breeding set, genetic marker data exists but remains confidential. The remaining genotypes, linked to specific projects such as INVITE, were present throughout all years but were generally only grown in a single year each . These genotypes currently lack available marker data. Regular measurements with the FIP 1.0 head were accompanied by reference measurement campaigns as part of several projects. The heading date and senescence ratings were performed to investigate the relationships of senescence dynamics and diseases . Yield measurements taken on the FIP field were combined with data from other locations to train phenomic prediction models . The plant height measurements served as a basis to quantify the temperature response of wheat genotypes in the stem elongation phase . The extracted plant height values demonstrated their usefulness in improving trait extraction methods from longitudinal data . The images collected were used to quantify canopy covers and examine their relationship to frost damage events using CNNs. Using a combination of drone data and the high-resolution images the rows in the individual plots were identified . In a small subset (375 images), the wheat heads were annotated and the data was integrated into the public global wheat head detection data set . The image-based canopy cover values served as a test data set to evaluate the cultivar-specific extensions of the thermal time concept . <!-- ### Annotations [optional] #### Annotation process [More Information Needed] [More Information Needed] ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] --> ## Dataset Card Authors Mike Boss, Lukas Roth, Norbert Kirchgessner ## Dataset Card Contact Mike Boss ([email protected])

WebOrganizer/Corpus-200B

WebOrganizer

--- language: - en size_categories: - 100B<n<1T --- # WebOrganizer/Corpus-200B [[Paper](https://arxiv.org/abs/2502.10341)] [[Website](https://weborganizer.allenai.org)] [[GitHub](https://github.com/CodeCreator/WebOrganizer)] This dataset is a pre-processed version of the `1b-1x` CommonCrawl pool from DataComps-LM cleaned with (1) [RefinedWeb filters](https://github.com/mlfoundations/dclm/blob/main/baselines/baselines_configs/dclm_baseline_refinedweb.yaml) and (2) [BFF deduplication](https://github.com/mlfoundations/dclm/tree/main/dedup/bff). We provide the resulting 200B token corpus annotated with two quality scores, WebOrganizer domains, and k-means scores. __Download the dataset by cloning the repository with Git LFS instead of HuggingFace's `load_dataset()`.__ The dataset has the following folder structure: ```bash Corpus-200B/ documents/ # Pre-processed web documents - CC_shard_00000000_processed.jsonl.zst - CC_shard_00000001_processed.jsonl.zst - ... tokens/ # number of tokens per document (GPT-NeoX tokenizer) - CC_shard_00000000_processed.npy - CC_shard_00000001_processed.npy - ... scores_dclm-fasttext/ # DCLM-fasttext score - CC_shard_00000000_processed.npy - ... scores_fineweb-edu/ # FineWeb-Edu score - CC_shard_00000000_processed.npy - ... scores_fineweb-edu__rounded/ # Rounded FineWeb-Edu score - CC_shard_00000000_processed__rounded.npy - ... domains_topics/ # TopicClassifier annotations - CC_shard_00000000_processed__choice.npy # index of top choice - ... domain_topics__logits/ - CC_shard_00000000_processed__logits.npy # logits for each topic - ... domains_formats/ # FormatClassifier annotations - CC_shard_00000000_processed__choice.npy # index of top choice - ... domains_formats/ # FormatClassifier annotations - CC_shard_00000000_processed__logits.npy # logits for each format - ... domains_clusters-k24/ # K-means clusters - CC_shard_00000000_processed.npy # cluster assignment for each document - ... ``` We also include statistics about the presence and co-occurence of domains in the `domain_statistics/` folder, computed with the `domain_statistics.py` script. ## Citation If you make use of this pre-processed corpus in your work, please cite: ```bibtex @article{wettig2025organize, title={Organize the Web: Constructing Domains Enhances Pre-Training Data Curation}, author={Alexander Wettig and Kyle Lo and Sewon Min and Hannaneh Hajishirzi and Danqi Chen and Luca Soldaini}, journal={arXiv preprint arXiv:2502.10341}, year={2025} } ```

MMMU/MMMU

MMMU

--- language: - en license: apache-2.0 size_categories: - 10K<n<100K task_categories: - question-answering - visual-question-answering - multiple-choice pretty_name: mmmu dataset_info: - config_name: Accounting features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 262599.0 num_examples: 5 - name: validation num_bytes: 1598285.0 num_examples: 30 - name: test num_bytes: 22135625.0 num_examples: 380 download_size: 37363379 dataset_size: 23996509.0 - config_name: Agriculture features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 22082656.0 num_examples: 5 - name: validation num_bytes: 119217558.0 num_examples: 30 - name: test num_bytes: 993664077.0 num_examples: 287 download_size: 1158036990 dataset_size: 1134964291.0 - config_name: Architecture_and_Engineering features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 137750.0 num_examples: 5 - name: validation num_bytes: 721378.0 num_examples: 30 - name: test num_bytes: 16054607.0 num_examples: 551 download_size: 48763955 dataset_size: 16913735.0 - config_name: Art features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 6241184.0 num_examples: 5 - name: validation num_bytes: 29934534.0 num_examples: 30 - name: test num_bytes: 237801390.0 num_examples: 231 download_size: 585798641 dataset_size: 273977108.0 - config_name: Art_Theory features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 7435106.0 num_examples: 5 - name: validation num_bytes: 33481558.0 num_examples: 30 - name: test num_bytes: 553174647.0 num_examples: 429 download_size: 930525695 dataset_size: 594091311.0 - config_name: Basic_Medical_Science features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 814310.0 num_examples: 5 - name: validation num_bytes: 4125930.0 num_examples: 30 - name: test num_bytes: 48125891.0 num_examples: 326 download_size: 84666454 dataset_size: 53066131.0 - config_name: Biology features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 574342.0 num_examples: 5 - name: validation num_bytes: 8491863.0 num_examples: 30 - name: test num_bytes: 132966151.0 num_examples: 345 download_size: 410242502 dataset_size: 142032356.0 - config_name: Chemistry features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 262397.0 num_examples: 5 - name: validation num_bytes: 1518573.0 num_examples: 30 - name: test num_bytes: 37219529.0 num_examples: 603 download_size: 108345562 dataset_size: 39000499.0 - config_name: Clinical_Medicine features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 1467945.0 num_examples: 5 - name: validation num_bytes: 10882484.0 num_examples: 30 - name: test num_bytes: 98201863.0 num_examples: 325 download_size: 160611488 dataset_size: 110552292.0 - config_name: Computer_Science features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 440523.0 num_examples: 5 - name: validation num_bytes: 2072018.0 num_examples: 30 - name: test num_bytes: 32047381.0 num_examples: 371 download_size: 55640991 dataset_size: 34559922.0 - config_name: Design features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 2259873.0 num_examples: 5 - name: validation num_bytes: 17923120.0 num_examples: 30 - name: test num_bytes: 77676331.0 num_examples: 169 download_size: 142866617 dataset_size: 97859324.0 - config_name: Diagnostics_and_Laboratory_Medicine features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 2056117.0 num_examples: 5 - name: validation num_bytes: 37106233.0 num_examples: 30 - name: test num_bytes: 157003069.0 num_examples: 162 download_size: 603957093 dataset_size: 196165419.0 - config_name: Economics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 171434.0 num_examples: 5 - name: validation num_bytes: 1487048.0 num_examples: 30 - name: test num_bytes: 11852300.0 num_examples: 267 download_size: 20777635 dataset_size: 13510782.0 - config_name: Electronics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 123632.0 num_examples: 5 - name: validation num_bytes: 641377.0 num_examples: 30 - name: test num_bytes: 5717686.0 num_examples: 256 download_size: 11602832 dataset_size: 6482695.0 - config_name: Energy_and_Power features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 105006.0 num_examples: 5 - name: validation num_bytes: 1641935.0 num_examples: 30 - name: test num_bytes: 14748428.0 num_examples: 432 download_size: 35246567 dataset_size: 16495369.0 - config_name: Finance features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 296124.0 num_examples: 5 - name: validation num_bytes: 1071060.0 num_examples: 30 - name: test num_bytes: 12065803.0 num_examples: 355 download_size: 29551521 dataset_size: 13432987.0 - config_name: Geography features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 1494060.0 num_examples: 5 - name: validation num_bytes: 6671316.0 num_examples: 30 - name: test num_bytes: 137218400.0 num_examples: 565 download_size: 374766631 dataset_size: 145383776.0 - config_name: History features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 1444231.0 num_examples: 5 - name: validation num_bytes: 8819857.0 num_examples: 30 - name: test num_bytes: 115228815.0 num_examples: 278 download_size: 232549641 dataset_size: 125492903.0 - config_name: Literature features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 2451201.0 num_examples: 5 - name: validation num_bytes: 14241046.0 num_examples: 30 - name: test num_bytes: 50301541.0 num_examples: 112 download_size: 132145895 dataset_size: 66993788.0 - config_name: Manage features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 449514.0 num_examples: 5 - name: validation num_bytes: 3277436.0 num_examples: 30 - name: test num_bytes: 29963963.0 num_examples: 245 download_size: 51186888 dataset_size: 33690913.0 - config_name: Marketing features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 116960.0 num_examples: 5 - name: validation num_bytes: 1472981.0 num_examples: 30 - name: test num_bytes: 7732976.0 num_examples: 181 download_size: 13146078 dataset_size: 9322917.0 - config_name: Materials features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 239632.0 num_examples: 5 - name: validation num_bytes: 2305223.0 num_examples: 30 - name: test num_bytes: 25256854.0 num_examples: 458 download_size: 105773156 dataset_size: 27801709.0 - config_name: Math features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 175839.0 num_examples: 5 - name: validation num_bytes: 1444496.0 num_examples: 30 - name: test num_bytes: 27701845.0 num_examples: 505 download_size: 174098418 dataset_size: 29322180.0 - config_name: Mechanical_Engineering features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 152542.0 num_examples: 5 - name: validation num_bytes: 874988.0 num_examples: 30 - name: test num_bytes: 15093746.0 num_examples: 429 download_size: 30450114 dataset_size: 16121276.0 - config_name: Music features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 1417615.0 num_examples: 5 - name: validation num_bytes: 9359372.0 num_examples: 30 - name: test num_bytes: 134096770.0 num_examples: 334 download_size: 174725052 dataset_size: 144873757.0 - config_name: Pharmacy features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 207924.0 num_examples: 5 - name: validation num_bytes: 1656342.0 num_examples: 30 - name: test num_bytes: 31866248.0 num_examples: 430 download_size: 62721263 dataset_size: 33730514.0 - config_name: Physics features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 233734.0 num_examples: 5 - name: validation num_bytes: 1114130.0 num_examples: 30 - name: test num_bytes: 15905705.0 num_examples: 408 download_size: 35238571 dataset_size: 17253569.0 - config_name: Psychology features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 600864.0 num_examples: 5 - name: validation num_bytes: 4403886.0 num_examples: 30 - name: test num_bytes: 53813915.0 num_examples: 305 download_size: 102466671 dataset_size: 58818665.0 - config_name: Public_Health features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 234781.0 num_examples: 5 - name: validation num_bytes: 1508761.0 num_examples: 30 - name: test num_bytes: 32150088.0 num_examples: 509 download_size: 48231609 dataset_size: 33893630.0 - config_name: Sociology features: - name: id dtype: string - name: question dtype: string - name: options dtype: string - name: explanation dtype: string - name: image_1 dtype: image - name: image_2 dtype: image - name: image_3 dtype: image - name: image_4 dtype: image - name: image_5 dtype: image - name: image_6 dtype: image - name: image_7 dtype: image - name: img_type dtype: string - name: answer dtype: string - name: topic_difficulty dtype: string - name: question_type dtype: string - name: subfield dtype: string splits: - name: dev num_bytes: 3769220.0 num_examples: 5 - name: validation num_bytes: 18455336.0 num_examples: 30 - name: test num_bytes: 144301123.0 num_examples: 252 download_size: 310313826 dataset_size: 166525679.0 configs: - config_name: Accounting data_files: - split: dev path: Accounting/dev-* - split: validation path: Accounting/validation-* - split: test path: Accounting/test-* - config_name: Agriculture data_files: - split: dev path: Agriculture/dev-* - split: validation path: Agriculture/validation-* - split: test path: Agriculture/test-* - config_name: Architecture_and_Engineering data_files: - split: dev path: Architecture_and_Engineering/dev-* - split: validation path: Architecture_and_Engineering/validation-* - split: test path: Architecture_and_Engineering/test-* - config_name: Art data_files: - split: dev path: Art/dev-* - split: validation path: Art/validation-* - split: test path: Art/test-* - config_name: Art_Theory data_files: - split: dev path: Art_Theory/dev-* - split: validation path: Art_Theory/validation-* - split: test path: Art_Theory/test-* - config_name: Basic_Medical_Science data_files: - split: dev path: Basic_Medical_Science/dev-* - split: validation path: Basic_Medical_Science/validation-* - split: test path: Basic_Medical_Science/test-* - config_name: Biology data_files: - split: dev path: Biology/dev-* - split: validation path: Biology/validation-* - split: test path: Biology/test-* - config_name: Chemistry data_files: - split: dev path: Chemistry/dev-* - split: validation path: Chemistry/validation-* - split: test path: Chemistry/test-* - config_name: Clinical_Medicine data_files: - split: dev path: Clinical_Medicine/dev-* - split: validation path: Clinical_Medicine/validation-* - split: test path: Clinical_Medicine/test-* - config_name: Computer_Science data_files: - split: dev path: Computer_Science/dev-* - split: validation path: Computer_Science/validation-* - split: test path: Computer_Science/test-* - config_name: Design data_files: - split: dev path: Design/dev-* - split: validation path: Design/validation-* - split: test path: Design/test-* - config_name: Diagnostics_and_Laboratory_Medicine data_files: - split: dev path: Diagnostics_and_Laboratory_Medicine/dev-* - split: validation path: Diagnostics_and_Laboratory_Medicine/validation-* - split: test path: Diagnostics_and_Laboratory_Medicine/test-* - config_name: Economics data_files: - split: dev path: Economics/dev-* - split: validation path: Economics/validation-* - split: test path: Economics/test-* - config_name: Electronics data_files: - split: dev path: Electronics/dev-* - split: validation path: Electronics/validation-* - split: test path: Electronics/test-* - config_name: Energy_and_Power data_files: - split: dev path: Energy_and_Power/dev-* - split: validation path: Energy_and_Power/validation-* - split: test path: Energy_and_Power/test-* - config_name: Finance data_files: - split: dev path: Finance/dev-* - split: validation path: Finance/validation-* - split: test path: Finance/test-* - config_name: Geography data_files: - split: dev path: Geography/dev-* - split: validation path: Geography/validation-* - split: test path: Geography/test-* - config_name: History data_files: - split: dev path: History/dev-* - split: validation path: History/validation-* - split: test path: History/test-* - config_name: Literature data_files: - split: dev path: Literature/dev-* - split: validation path: Literature/validation-* - split: test path: Literature/test-* - config_name: Manage data_files: - split: dev path: Manage/dev-* - split: validation path: Manage/validation-* - split: test path: Manage/test-* - config_name: Marketing data_files: - split: dev path: Marketing/dev-* - split: validation path: Marketing/validation-* - split: test path: Marketing/test-* - config_name: Materials data_files: - split: dev path: Materials/dev-* - split: validation path: Materials/validation-* - split: test path: Materials/test-* - config_name: Math data_files: - split: dev path: Math/dev-* - split: validation path: Math/validation-* - split: test path: Math/test-* - config_name: Mechanical_Engineering data_files: - split: dev path: Mechanical_Engineering/dev-* - split: validation path: Mechanical_Engineering/validation-* - split: test path: Mechanical_Engineering/test-* - config_name: Music data_files: - split: dev path: Music/dev-* - split: validation path: Music/validation-* - split: test path: Music/test-* - config_name: Pharmacy data_files: - split: dev path: Pharmacy/dev-* - split: validation path: Pharmacy/validation-* - split: test path: Pharmacy/test-* - config_name: Physics data_files: - split: dev path: Physics/dev-* - split: validation path: Physics/validation-* - split: test path: Physics/test-* - config_name: Psychology data_files: - split: dev path: Psychology/dev-* - split: validation path: Psychology/validation-* - split: test path: Psychology/test-* - config_name: Public_Health data_files: - split: dev path: Public_Health/dev-* - split: validation path: Public_Health/validation-* - split: test path: Public_Health/test-* - config_name: Sociology data_files: - split: dev path: Sociology/dev-* - split: validation path: Sociology/validation-* - split: test path: Sociology/test-* tags: - biology - medical - finance - chemistry - music - art - art_theory - design - music - business - accounting - economics - finance - manage - marketing - health - medicine - basic_medical_science - clinical - pharmacy - public_health - humanities - social_science - history - literature - sociology - psychology - science - biology - chemistry - geography - math - physics - engineering - agriculture - architecture - computer_science - electronics - energy_and_power - materials - mechanical_engineering --- # MMMU (A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI) [**🌐 Homepage**](https://mmmu-benchmark.github.io/) | [**🏆 Leaderboard**](https://mmmu-benchmark.github.io/#leaderboard) | [**🤗 Dataset**](https://huggingface.co/datasets/MMMU/MMMU/) | [**🤗 Paper**](https://huggingface.co/papers/2311.16502) | [**📖 arXiv**](https://arxiv.org/abs/2311.16502) | [**GitHub**](https://github.com/MMMU-Benchmark/MMMU) ## 🔔News - **🛠️[2024-05-30]: Fixed duplicate option issues in Materials dataset items (validation_Materials_25; test_Materials_17, 242) and content error in validation_Materials_25.** - **🛠️[2024-04-30]: Fixed missing "-" or "^" signs in Math dataset items (dev_Math_2, validation_Math_11, 12, 16; test_Math_8, 23, 43, 113, 164, 223, 236, 287, 329, 402, 498) and corrected option errors in validation_Math_2. If you encounter any issues with the dataset, please contact us promptly!** - **🚀[2024-01-31]: We added Human Expert performance on the [Leaderboard](https://mmmu-benchmark.github.io/#leaderboard)!🌟** - **🔥[2023-12-04]: Our evaluation server for test set is now availble on [EvalAI](https://eval.ai/web/challenges/challenge-page/2179/overview). We welcome all submissions and look forward to your participation! 😆** ## Dataset Details ### Dataset Description We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning. MMMU includes **11.5K meticulously collected multimodal questions** from college exams, quizzes, and textbooks, covering six core disciplines: Art & Design, Business, Science, Health & Medicine, Humanities & Social Science, and Tech & Engineering. These questions span **30 subjects** and **183 subfields**, comprising **30 highly heterogeneous image types**, such as charts, diagrams, maps, tables, music sheets, and chemical structures. We believe MMMU will stimulate the community to build next-generation multimodal foundation models towards expert artificial general intelligence (AGI). 🎯 **We have released a full set comprising 150 development samples and 900 validation samples. We have released 10,500 test questions without their answers.** The development set is used for few-shot/in-context learning, and the validation set is used for debugging models, selecting hyperparameters, or quick evaluations. The answers and explanations for the test set questions are withheld. You can submit your model's predictions for the **test set** on **[EvalAI](https://eval.ai/web/challenges/challenge-page/2179/overview)**.  ### Dataset Creation MMMU was created to challenge multimodal models with tasks that demand college-level subject knowledge and deliberate reasoning, pushing the boundaries of what these models can achieve in terms of expert-level perception and reasoning. The data for the MMMU dataset was manually collected by a team of college students from various disciplines, using online sources, textbooks, and lecture materials. - **Content:** The dataset contains 11.5K college-level problems across six broad disciplines (Art & Design, Business, Science, Health & Medicine, Humanities & Social Science, Tech & Engineering) and 30 college subjects. - **Image Types:** The dataset includes 30 highly heterogeneous image types, such as charts, diagrams, maps, tables, music sheets, and chemical structures, interleaved with text.  ## 🏆 Mini-Leaderboard We show a mini-leaderboard here and please find more information in our paper or [**homepage**](https://mmmu-benchmark.github.io/). | Model | Val (900) | Test (10.5K) | |--------------------------------|:---------:|:------------:| | Expert (Best) | 88.6 | - | | Expert (Medium) | 82.6 | - | | Expert (Worst) | 76.2 | - | | GPT-4o* | **69.1** | - | | Gemini 1.5 Pro* | 62.2 | - | | InternVL2-Pro* | 62.0 | **55.7** | | Gemini 1.0 Ultra* | 59.4 | - | | Claude 3 Opus* | 59.4 | - | | GPT-4V(ision) (Playground) | 56.8 | **55.7** | | Reka Core* | 56.3 | - | | Gemini 1.5 Flash* | 56.1 | - | | SenseChat-Vision-0423-Preview* | 54.6 | 50.3 | | Reka Flash* | 53.3 | - | | Claude 3 Sonnet* | 53.1 | - | | HPT Pro* | 52.0 | - | | VILA1.5* | 51.9 | 46.9 | | Qwen-VL-MAX* | 51.4 | 46.8 | | InternVL-Chat-V1.2* | 51.6 | 46.2 | | Skywork-VL* | 51.4 | 46.2 | | LLaVA-1.6-34B* | 51.1 | 44.7 | | Claude 3 Haiku* | 50.2 | - | | Adept Fuyu-Heavy* | 48.3 | - | | Gemini 1.0 Pro* | 47.9 | - | | Marco-VL-Plus* | 46.2 | 44.3 | | Yi-VL-34B* | 45.9 | 41.6 | | Qwen-VL-PLUS* | 45.2 | 40.8 | | HPT Air* | 44.0 | - | | Reka Edge* | 42.8 | - | | Marco-VL* | 41.2 | 40.4 | | OmniLMM-12B* | 41.1 | 40.4 | | Bunny-8B* | 43.3 | 39.0 | | Bunny-4B* | 41.4 | 38.4 | | Weitu-VL-1.0-15B* | - | 38.4 | | InternLM-XComposer2-VL* | 43.0 | 38.2 | | Yi-VL-6B* | 39.1 | 37.8 | | InfiMM-Zephyr-7B* | 39.4 | 35.5 | | InternVL-Chat-V1.1* | 39.1 | 35.3 | | Math-LLaVA-13B* | 38.3 | 34.6 | | SVIT* | 38.0 | 34.1 | | MiniCPM-V* | 37.2 | 34.1 | | MiniCPM-V-2* | 37.1 | - | | Emu2-Chat* | 36.3 | 34.1 | | BLIP-2 FLAN-T5-XXL | 35.4 | 34.0 | | InstructBLIP-T5-XXL | 35.7 | 33.8 | | LLaVA-1.5-13B | 36.4 | 33.6 | | Bunny-3B* | 38.2 | 33.0 | | Qwen-VL-7B-Chat | 35.9 | 32.9 | | SPHINX* | 32.9 | 32.9 | | mPLUG-OWL2* | 32.7 | 32.1 | | BLIP-2 FLAN-T5-XL | 34.4 | 31.0 | | InstructBLIP-T5-XL | 32.9 | 30.6 | | Gemini Nano2* | 32.6 | - | | CogVLM | 32.1 | 30.1 | | Otter | 32.2 | 29.1 | | LLaMA-Adapter2-7B | 29.8 | 27.7 | | MiniGPT4-Vicuna-13B | 26.8 | 27.6 | | Adept Fuyu-8B | 27.9 | 27.4 | | Kosmos2 | 24.4 | 26.6 | | OpenFlamingo2-9B | 28.7 | 26.3 | | Frequent Choice | 22.1 | 23.9 | | Random Choice | 26.8 | 25.8 | *: results provided by the authors. ## Limitations Despite its comprehensive nature, MMMU, like any benchmark, is not without limitations. The manual curation process, albeit thorough, may carry biases. And the focus on college-level subjects might not fully be a sufficient test for Expert AGI. However, we believe it should be necessary for an Expert AGI to achieve strong performance on MMMU to demonstrate their broad and deep subject knowledge as well as expert-level understanding and reasoning capabilities. In future work, we plan to incorporate human evaluations into MMMU. This will provide a more grounded comparison between model capabilities and expert performance, shedding light on the proximity of current AI systems to achieving Expert AGI. ## Disclaimers The guidelines for the annotators emphasized strict compliance with copyright and licensing rules from the initial data source, specifically avoiding materials from websites that forbid copying and redistribution. Should you encounter any data samples potentially breaching the copyright or licensing regulations of any site, we encourage you to notify us. Upon verification, such samples will be promptly removed. ## Contact - Xiang Yue: [email protected] - Yu Su: [email protected] - Wenhu Chen: [email protected] ## Citation **BibTeX:** ```bibtex @inproceedings{yue2023mmmu, title={MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI}, author={Xiang Yue and Yuansheng Ni and Kai Zhang and Tianyu Zheng and Ruoqi Liu and Ge Zhang and Samuel Stevens and Dongfu Jiang and Weiming Ren and Yuxuan Sun and Cong Wei and Botao Yu and Ruibin Yuan and Renliang Sun and Ming Yin and Boyuan Zheng and Zhenzhu Yang and Yibo Liu and Wenhao Huang and Huan Sun and Yu Su and Wenhu Chen}, booktitle={Proceedings of CVPR}, year={2024}, } ```

QingyiSi/Alpaca-CoT

QingyiSi

--- language: - en - zh - ml tags: - Instruction - Cot license: apache-2.0 datasets: - dataset1 - dataset2 --- # Instruction-Finetuning Dataset Collection (Alpaca-CoT) This repository will continuously collect various instruction tuning datasets. And we standardize different datasets into the same format, which can be directly loaded by the [code](https://github.com/PhoebusSi/alpaca-CoT) of Alpaca model. We also have conducted empirical study on various instruction-tuning datasets based on the Alpaca model, as shown in [https://github.com/PhoebusSi/alpaca-CoT](https://github.com/PhoebusSi/alpaca-CoT). If you think this dataset collection is helpful to you, please `like` this dataset and `star` our [github project](https://github.com/PhoebusSi/alpaca-CoT)! You are in a warm welcome to provide us with any non-collected instruction-tuning datasets (or their sources). We will uniformly format them, train Alpaca model with these datasets and open source the model checkpoints. # Contribute Welcome to join us and become a contributor to this project! If you want to share some datasets, adjust the data in the following format: ``` example.json [ {"instruction": instruction string, "input": input string, # (may be empty) "output": output string} ] ``` Folder should be like this: ``` Alpaca-CoT | |----example | | | |----example.json | | | ----example_context.json ... ``` Create a new pull request in [Community ](https://huggingface.co/datasets/QingyiSi/Alpaca-CoT/discussions) and publish your branch when you are ready. We will merge it as soon as we can. # Data Usage and Resources ## Data Format All data in this folder is formatted into the same templates, where each sample is as follows: ``` [ {"instruction": instruction string, "input": input string, # (may be empty) "output": output string} ] ``` ## alpaca #### alpaca_data.json > This dataset is published by [Stanford Alpaca](https://github.com/tatsu-lab/stanford_alpaca). It contains 52K English instruction-following samples obtained by [Self-Instruction](https://github.com/yizhongw/self-instruct) techniques. #### alpaca_data_cleaned.json > This dataset is obtained [here](https://github.com/tloen/alpaca-lora). It is a revised version of `alpaca_data.json` by stripping of various tokenization artifacts. ## alpacaGPT4 #### alpaca_gpt4_data.json > This dataset is published by [Instruction-Tuning-with-GPT-4](https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM). It contains 52K English instruction-following samples generated by GPT-4 using Alpaca prompts for fine-tuning LLMs. #### alpaca_gpt4_data_zh.json > This dataset is generated by GPT-4 using Chinese prompts translated from Alpaca by ChatGPT. <!-- ## belle_cn #### belle_data_cn.json This dataset is published by [BELLE](https://github.com/LianjiaTech/BELLE). It contains 0.5M Chinese instruction-following samples, which is also generated by [Self-Instruction](https://github.com/yizhongw/self-instruct) techniques. #### belle_data1M_cn.json This dataset is published by [BELLE](https://github.com/LianjiaTech/BELLE). It contains 1M Chinese instruction-following samples. The data of `belle_data_cn.json` and `belle_data1M_cn.json` are not duplicated. --> ## Chain-of-Thought #### CoT_data.json > This dataset is obtained by formatting the combination of 9 CoT datasets published by [FLAN](https://github.com/google-research/FLAN). It contains 9 CoT tasks involving 74771 samples. #### CoT_CN_data.json > This dataset is obtained by tranlating `CoT_data.json` into Chinese, using Google Translate(en2cn). #### formatted_cot_data folder > This folder contains the formatted English data for each CoT dataset. #### formatted_cot_data folder > This folder contains the formatted Chinese data for each CoT dataset. ## CodeAlpaca #### code_alpaca.json > This dataset is published by [codealpaca](https://github.com/sahil280114/codealpaca). It contains code generation task involving 20022 samples. ## finance #### finance_en.json > This dataset is collected from [here](https://huggingface.co/datasets/gbharti/finance-alpaca). It contains 68912 financial related instructions in English. ## firefly #### firefly.json > his dataset is collected from [here](https://github.com/yangjianxin1/Firefly). It contains 1649398 chinese instructions in 23 nlp tasks. ## GPT4all #### gpt4all.json > This dataset is collected from [here](https://github.com/nomic-ai/gpt4all). It contains 806199 en instructions in code, storys and dialogs tasks. #### gpt4all_without_p3.json > gpt4all without Bigscience/P3, contains 437605 samples. ## GPTeacher #### GPTeacher.json > This dataset is collected from [here](https://github.com/teknium1/GPTeacher). It contains 29013 en instructions generated by GPT-4, General-Instruct - Roleplay-Instruct - Code-Instruct - and Toolformer. ## Guanaco #### GuanacoDataset.json > This dataset is collected from [here](https://huggingface.co/datasets/JosephusCheung/GuanacoDataset). It contains 534610 en instructions generated by text-davinci-003 upon 175 tasks from the Alpaca model by providing rewrites of seed tasks in different languages and adding new tasks specifically designed for English grammar analysis, natural language understanding, cross-lingual self-awareness, and explicit content recognition. #### Guanaco_additional_Dataset.json > A new additional larger dataset for different languages. ## HC3 #### HC3_ChatGPT.json/HC3_Human.json > This dataset is collected from [here](https://huggingface.co/datasets/Hello-SimpleAI/HC3). It contains 37175 en/zh instructions generated by ChatGPT and human. #### HC3_ChatGPT_deduplication.json/HC3_Human_deduplication.json > HC3 dataset without deduplication instructions. ## instinwild #### instinwild_en.json & instinwild_cn.json > The two datasets are obtained [here](https://github.com/XueFuzhao/InstructionWild). It contains 52191 English and 51504 Chinese instructions, which are collected from Twitter, where users tend to share their interesting prompts of mostly generation, open QA, and mind-storm types. (Colossal AI used these datasets to train the ColossalChat model.) ## instruct #### instruct.json > The two datasets are obtained [here](https://huggingface.co/datasets/swype/instruct). It contains 888969 English instructions, which are caugmentation performed using the advanced NLP tools provided by AllenAI. ## Natural Instructions #### natural-instructions-1700tasks.zip > This dataset is obtained [here](https://github.com/allenai/natural-instructions). It contains 5040134 instructions, which are collected from diverse nlp tasks ## prosocial dialog #### natural-instructions-1700tasks.zip > This dataset is obtained [here](https://huggingface.co/datasets/allenai/prosocial-dialog). It contains 165681 English instructions, which are produuced by GPT-3 rewrites questions and humans feedback ## xP3 #### natural-instructions-1700tasks.zip > This dataset is obtained [here](https://huggingface.co/datasets/bigscience/xP3). It contains 78883588 instructions, which are collected by prompts & datasets across 46 of languages & 16 NLP tasks ## Chinese-instruction-collection > all datasets of Chinese instruction collection ## combination #### alcapa_plus_belle_data.json > This dataset is the combination of English `alpaca_data.json` and Chinese `belle_data_cn.json`. #### alcapa_plus_cot_data.json > This dataset is the combination of English `alpaca_data.json` and CoT `CoT_data.json`. #### alcapa_plus_belle_cot_data.json > This dataset is the combination of English `alpaca_data.json`, Chinese `belle_data_cn.json` and CoT `CoT_data.json`. ## Citation Please cite the repo if you use the data collection, code, and experimental findings in this repo. ``` @misc{alpaca-cot, author = {Qingyi Si, Zheng Lin }, school = {Institute of Information Engineering, Chinese Academy of Sciences, Beijing, China}, title = {Alpaca-CoT: An Instruction Fine-Tuning Platform with Instruction Data Collection and Unified Large Language Models Interface}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/PhoebusSi/alpaca-CoT}}, } ``` Cite the original Stanford Alpaca, BELLE and FLAN papers as well, please.

universal-dependencies/universal_dependencies

universal-dependencies

--- annotations_creators: - expert-generated language_creators: - crowdsourced language: - af - aii - ajp - akk - am - apu - aqz - ar - be - bg - bho - bm - br - bxr - ca - ckt - cop - cs - cu - cy - da - de - el - en - es - et - eu - fa - fi - fo - fr - fro - ga - gd - gl - got - grc - gsw - gun - gv - he - hi - hr - hsb - hu - hy - id - is - it - ja - kfm - kk - kmr - ko - koi - kpv - krl - la - lt - lv - lzh - mdf - mr - mt - myu - myv - nl - 'no' - nyq - olo - orv - otk - pcm - pl - pt - ro - ru - sa - sk - sl - sme - sms - soj - sq - sr - sv - swl - ta - te - th - tl - tpn - tr - ug - uk - ur - vi - wbp - wo - yo - yue - zh license: - unknown multilinguality: - multilingual size_categories: - 1K<n<10K source_datasets: - original task_categories: - token-classification task_ids: - parsing paperswithcode_id: universal-dependencies pretty_name: Universal Dependencies Treebank tags: - constituency-parsing - dependency-parsing dataset_info: - config_name: af_afribooms features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 3523113 num_examples: 1315 - name: validation num_bytes: 547285 num_examples: 194 - name: test num_bytes: 1050299 num_examples: 425 download_size: 3088237 dataset_size: 5120697 - config_name: akk_pisandub features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 153470 num_examples: 101 download_size: 101789 dataset_size: 153470 - config_name: akk_riao features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 3374577 num_examples: 1804 download_size: 2022357 dataset_size: 3374577 - config_name: aqz_tudet features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 8286 num_examples: 24 download_size: 5683 dataset_size: 8286 - config_name: sq_tsa features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 116034 num_examples: 60 download_size: 68875 dataset_size: 116034 - config_name: am_att features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1554859 num_examples: 1074 download_size: 1019607 dataset_size: 1554859 - config_name: grc_perseus features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 22611612 num_examples: 11476 - name: validation num_bytes: 3152233 num_examples: 1137 - name: test num_bytes: 3004502 num_examples: 1306 download_size: 18898313 dataset_size: 28768347 - config_name: grc_proiel features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 30938089 num_examples: 15014 - name: validation num_bytes: 2264551 num_examples: 1019 - name: test num_bytes: 2192289 num_examples: 1047 download_size: 23715831 dataset_size: 35394929 - config_name: apu_ufpa features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 75578 num_examples: 76 download_size: 69565 dataset_size: 75578 - config_name: ar_nyuad features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 79064476 num_examples: 15789 - name: validation num_bytes: 9859912 num_examples: 1986 - name: test num_bytes: 9880240 num_examples: 1963 download_size: 58583673 dataset_size: 98804628 - config_name: ar_padt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 58537298 num_examples: 6075 - name: validation num_bytes: 7787253 num_examples: 909 - name: test num_bytes: 7428063 num_examples: 680 download_size: 51208169 dataset_size: 73752614 - config_name: ar_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2816625 num_examples: 1000 download_size: 2084082 dataset_size: 2816625 - config_name: hy_armtdp features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 7697891 num_examples: 1975 - name: validation num_bytes: 988849 num_examples: 249 - name: test num_bytes: 947287 num_examples: 278 download_size: 6886567 dataset_size: 9634027 - config_name: aii_as features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 52540 num_examples: 57 download_size: 32639 dataset_size: 52540 - config_name: bm_crb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1502886 num_examples: 1026 download_size: 892924 dataset_size: 1502886 - config_name: eu_bdt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 8199861 num_examples: 5396 - name: validation num_bytes: 2701073 num_examples: 1798 - name: test num_bytes: 2734601 num_examples: 1799 download_size: 8213576 dataset_size: 13635535 - config_name: be_hse features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 34880663 num_examples: 21555 - name: validation num_bytes: 1745668 num_examples: 1090 - name: test num_bytes: 1818113 num_examples: 889 download_size: 26433402 dataset_size: 38444444 - config_name: bho_bhtb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 947740 num_examples: 357 download_size: 614159 dataset_size: 947740 - config_name: br_keb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1026257 num_examples: 888 download_size: 679680 dataset_size: 1026257 - config_name: bg_btb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 18545312 num_examples: 8907 - name: validation num_bytes: 2393174 num_examples: 1115 - name: test num_bytes: 2344136 num_examples: 1116 download_size: 14910603 dataset_size: 23282622 - config_name: bxr_bdt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 17364 num_examples: 19 - name: test num_bytes: 1116630 num_examples: 908 download_size: 726053 dataset_size: 1133994 - config_name: yue_hk features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1242850 num_examples: 1004 download_size: 710060 dataset_size: 1242850 - config_name: ca_ancora features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 46502842 num_examples: 13123 - name: validation num_bytes: 6282364 num_examples: 1709 - name: test num_bytes: 6441038 num_examples: 1846 download_size: 35924146 dataset_size: 59226244 - config_name: zh_cfl features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 660584 num_examples: 451 download_size: 384725 dataset_size: 660584 - config_name: zh_gsd features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 9268661 num_examples: 3997 - name: validation num_bytes: 1188371 num_examples: 500 - name: test num_bytes: 1130467 num_examples: 500 download_size: 6828367 dataset_size: 11587499 - config_name: zh_gsdsimp features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 9268663 num_examples: 3997 - name: validation num_bytes: 1188383 num_examples: 500 - name: test num_bytes: 1130459 num_examples: 500 download_size: 6828419 dataset_size: 11587505 - config_name: zh_hk features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 880193 num_examples: 1004 download_size: 494447 dataset_size: 880193 - config_name: zh_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2425817 num_examples: 1000 download_size: 1606982 dataset_size: 2425817 - config_name: ckt_hse features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 808669 num_examples: 1004 download_size: 771943 dataset_size: 808669 - config_name: lzh_kyoto features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 26615708 num_examples: 38669 - name: validation num_bytes: 3770507 num_examples: 5296 - name: test num_bytes: 3155207 num_examples: 4469 download_size: 22658287 dataset_size: 33541422 - config_name: cop_scriptorium features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 3944468 num_examples: 1089 - name: validation num_bytes: 1566786 num_examples: 381 - name: test num_bytes: 1487709 num_examples: 403 download_size: 4502996 dataset_size: 6998963 - config_name: hr_set features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 19104315 num_examples: 6914 - name: validation num_bytes: 2787184 num_examples: 960 - name: test num_bytes: 3035797 num_examples: 1136 download_size: 15103034 dataset_size: 24927296 - config_name: cs_cac features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 81527862 num_examples: 23478 - name: validation num_bytes: 1898678 num_examples: 603 - name: test num_bytes: 1878841 num_examples: 628 download_size: 55990235 dataset_size: 85305381 - config_name: cs_cltt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 4277239 num_examples: 860 - name: validation num_bytes: 752253 num_examples: 129 - name: test num_bytes: 646103 num_examples: 136 download_size: 3745656 dataset_size: 5675595 - config_name: cs_fictree features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 21490020 num_examples: 10160 - name: validation num_bytes: 2677727 num_examples: 1309 - name: test num_bytes: 2679930 num_examples: 1291 download_size: 17464342 dataset_size: 26847677 - config_name: cs_pdt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 201356662 num_examples: 68495 - name: validation num_bytes: 27366981 num_examples: 9270 - name: test num_bytes: 29817339 num_examples: 10148 download_size: 171506068 dataset_size: 258540982 - config_name: cs_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 3195818 num_examples: 1000 download_size: 2231853 dataset_size: 3195818 - config_name: da_ddt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 8689809 num_examples: 4383 - name: validation num_bytes: 1117939 num_examples: 564 - name: test num_bytes: 1082651 num_examples: 565 download_size: 6425281 dataset_size: 10890399 - config_name: nl_alpino features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 22503950 num_examples: 12264 - name: validation num_bytes: 1411253 num_examples: 718 - name: test num_bytes: 1354908 num_examples: 596 download_size: 16858557 dataset_size: 25270111 - config_name: nl_lassysmall features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 9001614 num_examples: 5787 - name: validation num_bytes: 1361552 num_examples: 676 - name: test num_bytes: 1391136 num_examples: 875 download_size: 8034396 dataset_size: 11754302 - config_name: en_esl features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 5335977 num_examples: 4124 - name: validation num_bytes: 648562 num_examples: 500 - name: test num_bytes: 651829 num_examples: 500 download_size: 3351548 dataset_size: 6636368 - config_name: en_ewt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 22755753 num_examples: 12543 - name: validation num_bytes: 2829889 num_examples: 2002 - name: test num_bytes: 2820398 num_examples: 2077 download_size: 16893922 dataset_size: 28406040 - config_name: en_gum features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 8999554 num_examples: 4287 - name: validation num_bytes: 1704949 num_examples: 784 - name: test num_bytes: 1743317 num_examples: 890 download_size: 7702761 dataset_size: 12447820 - config_name: en_gumreddit features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1365930 num_examples: 587 - name: validation num_bytes: 317546 num_examples: 150 - name: test num_bytes: 374707 num_examples: 158 download_size: 1195979 dataset_size: 2058183 - config_name: en_lines features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 5728898 num_examples: 3176 - name: validation num_bytes: 1911762 num_examples: 1032 - name: test num_bytes: 1766797 num_examples: 1035 download_size: 5522254 dataset_size: 9407457 - config_name: en_partut features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 4133445 num_examples: 1781 - name: validation num_bytes: 265039 num_examples: 156 - name: test num_bytes: 326834 num_examples: 153 download_size: 2720286 dataset_size: 4725318 - config_name: en_pronouns features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 207364 num_examples: 285 download_size: 147181 dataset_size: 207364 - config_name: en_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2282027 num_examples: 1000 download_size: 1340563 dataset_size: 2282027 - config_name: myv_jr features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2763297 num_examples: 1690 download_size: 1945981 dataset_size: 2763297 - config_name: et_edt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 42901059 num_examples: 24633 - name: validation num_bytes: 5551620 num_examples: 3125 - name: test num_bytes: 5994421 num_examples: 3214 download_size: 32393618 dataset_size: 54447100 - config_name: et_ewt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 4199896 num_examples: 2837 - name: validation num_bytes: 1089459 num_examples: 743 - name: test num_bytes: 1600116 num_examples: 913 download_size: 4044147 dataset_size: 6889471 - config_name: fo_farpahc features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 2114958 num_examples: 1020 - name: validation num_bytes: 809707 num_examples: 300 - name: test num_bytes: 798245 num_examples: 301 download_size: 2186706 dataset_size: 3722910 - config_name: fo_oft features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1220792 num_examples: 1208 download_size: 802681 dataset_size: 1220792 - config_name: fi_ftb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - 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name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2086421 num_examples: 1000 download_size: 1411514 dataset_size: 2086421 - config_name: fi_tdt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - 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name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 6322307 num_examples: 1000 download_size: 4661525 dataset_size: 6322307 - config_name: krl_kkpp features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 370378 num_examples: 228 download_size: 226103 dataset_size: 370378 - config_name: kk_ktb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 64737 num_examples: 31 - name: test num_bytes: 1263246 num_examples: 1047 download_size: 849300 dataset_size: 1327983 - config_name: kfm_aha features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 8464 num_examples: 10 download_size: 6290 dataset_size: 8464 - config_name: koi_uh features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 117629 num_examples: 81 download_size: 91509 dataset_size: 117629 - config_name: kpv_ikdp features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 182189 num_examples: 132 download_size: 121684 dataset_size: 182189 - config_name: kpv_lattice features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 685683 num_examples: 435 download_size: 467085 dataset_size: 685683 - config_name: ko_gsd features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 5480313 num_examples: 4400 - name: validation num_bytes: 1156603 num_examples: 950 - name: test num_bytes: 1129555 num_examples: 989 download_size: 4882238 dataset_size: 7766471 - config_name: ko_kaist features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 29037654 num_examples: 23010 - name: validation num_bytes: 2511880 num_examples: 2066 - name: test num_bytes: 2792215 num_examples: 2287 download_size: 21855177 dataset_size: 34341749 - config_name: ko_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2511856 num_examples: 1000 download_size: 2024810 dataset_size: 2511856 - config_name: kmr_mg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 30374 num_examples: 20 - name: test num_bytes: 1248564 num_examples: 734 download_size: 765158 dataset_size: 1278938 - config_name: la_ittb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 54306304 num_examples: 22775 - name: validation num_bytes: 4236222 num_examples: 2101 - name: test num_bytes: 4221459 num_examples: 2101 download_size: 40247546 dataset_size: 62763985 - config_name: la_llct features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 26885433 num_examples: 7289 - name: validation num_bytes: 3363915 num_examples: 850 - name: test num_bytes: 3352500 num_examples: 884 download_size: 21975884 dataset_size: 33601848 - config_name: la_perseus features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 2542043 num_examples: 1334 - name: test num_bytes: 1575350 num_examples: 939 download_size: 2573703 dataset_size: 4117393 - config_name: la_proiel features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 24956038 num_examples: 15917 - name: validation num_bytes: 2020476 num_examples: 1234 - name: test num_bytes: 2029828 num_examples: 1260 download_size: 18434442 dataset_size: 29006342 - config_name: lv_lvtb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 29167529 num_examples: 10156 - name: validation num_bytes: 4501172 num_examples: 1664 - name: test num_bytes: 4565919 num_examples: 1823 download_size: 25227301 dataset_size: 38234620 - config_name: lt_alksnis features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 7272501 num_examples: 2341 - name: validation num_bytes: 1763901 num_examples: 617 - name: test num_bytes: 1648521 num_examples: 684 download_size: 7008248 dataset_size: 10684923 - config_name: lt_hse features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 433214 num_examples: 153 - name: validation num_bytes: 433214 num_examples: 153 - name: test num_bytes: 433214 num_examples: 153 download_size: 265619 dataset_size: 1299642 - config_name: olo_kkpp features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 18096 num_examples: 19 - name: test num_bytes: 175355 num_examples: 106 download_size: 121837 dataset_size: 193451 - config_name: mt_mudt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1858001 num_examples: 1123 - name: validation num_bytes: 826004 num_examples: 433 - name: test num_bytes: 892629 num_examples: 518 download_size: 2011753 dataset_size: 3576634 - config_name: gv_cadhan features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 483042 num_examples: 291 download_size: 287206 dataset_size: 483042 - config_name: mr_ufal features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 420345 num_examples: 373 - name: validation num_bytes: 60791 num_examples: 46 - name: test num_bytes: 56582 num_examples: 47 download_size: 339354 dataset_size: 537718 - config_name: gun_dooley features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 1037858 num_examples: 1046 download_size: 571571 dataset_size: 1037858 - config_name: gun_thomas features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 143111 num_examples: 98 download_size: 92963 dataset_size: 143111 - config_name: mdf_jr features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 234147 num_examples: 167 download_size: 162330 dataset_size: 234147 - config_name: myu_tudet features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 26202 num_examples: 62 download_size: 20315 dataset_size: 26202 - config_name: pcm_nsc features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 16079391 num_examples: 7279 - name: validation num_bytes: 2099571 num_examples: 991 - name: test num_bytes: 2063685 num_examples: 972 download_size: 14907410 dataset_size: 20242647 - config_name: nyq_aha features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 8723 num_examples: 10 download_size: 6387 dataset_size: 8723 - config_name: sme_giella features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - 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name: test num_bytes: 3151638 num_examples: 1939 download_size: 19177350 dataset_size: 32627595 - config_name: no_nynorsk features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 25630539 num_examples: 14174 - name: validation num_bytes: 3277649 num_examples: 1890 - name: test num_bytes: 2601676 num_examples: 1511 download_size: 18532495 dataset_size: 31509864 - config_name: no_nynorsklia features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - 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name: test num_bytes: 1535923 num_examples: 1927 download_size: 9043098 dataset_size: 15022356 - config_name: orv_rnc features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1527306 num_examples: 320 - name: test num_bytes: 2552216 num_examples: 637 download_size: 2627398 dataset_size: 4079522 - config_name: orv_torot features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - 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config_name: fa_perdt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 48654947 num_examples: 26196 - name: validation num_bytes: 2687750 num_examples: 1456 - name: test num_bytes: 2600303 num_examples: 1455 download_size: 33606395 dataset_size: 53943000 - config_name: fa_seraji features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 12627691 num_examples: 4798 - name: validation num_bytes: 1634327 num_examples: 599 - name: test num_bytes: 1675134 num_examples: 600 download_size: 9890107 dataset_size: 15937152 - config_name: pl_lfg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 16810910 num_examples: 13774 - name: validation num_bytes: 2093712 num_examples: 1745 - name: test num_bytes: 2100915 num_examples: 1727 download_size: 14865541 dataset_size: 21005537 - config_name: pl_pdb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 44652289 num_examples: 17722 - name: validation num_bytes: 5494883 num_examples: 2215 - name: test num_bytes: 5322608 num_examples: 2215 download_size: 36340919 dataset_size: 55469780 - config_name: pl_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2943603 num_examples: 1000 download_size: 1943983 dataset_size: 2943603 - config_name: pt_bosque features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 22808617 num_examples: 8328 - name: validation num_bytes: 1201577 num_examples: 560 - name: test num_bytes: 1131511 num_examples: 476 download_size: 15201503 dataset_size: 25141705 - config_name: pt_gsd features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 22208385 num_examples: 9664 - name: validation num_bytes: 2805628 num_examples: 1210 - name: test num_bytes: 2732063 num_examples: 1204 download_size: 15300844 dataset_size: 27746076 - config_name: pt_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2431942 num_examples: 1000 download_size: 1516883 dataset_size: 2431942 - config_name: ro_nonstandard features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 74489083 num_examples: 24121 - name: validation num_bytes: 2663152 num_examples: 1052 - name: test num_bytes: 3017162 num_examples: 1052 download_size: 50345748 dataset_size: 80169397 - config_name: ro_rrt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 23695399 num_examples: 8043 - name: validation num_bytes: 2190973 num_examples: 752 - name: test num_bytes: 2092520 num_examples: 729 download_size: 17187956 dataset_size: 27978892 - config_name: ro_simonero features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 15390734 num_examples: 3747 - name: validation num_bytes: 1926639 num_examples: 443 - name: test num_bytes: 1940787 num_examples: 491 download_size: 11409378 dataset_size: 19258160 - config_name: ru_gsd features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 10504099 num_examples: 3850 - name: validation num_bytes: 1635884 num_examples: 579 - name: test num_bytes: 1597603 num_examples: 601 download_size: 8830986 dataset_size: 13737586 - config_name: ru_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2695958 num_examples: 1000 download_size: 1869304 dataset_size: 2695958 - config_name: ru_syntagrus features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 126305584 num_examples: 48814 - name: validation num_bytes: 17043673 num_examples: 6584 - name: test num_bytes: 16880203 num_examples: 6491 download_size: 102745164 dataset_size: 160229460 - config_name: ru_taiga features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 5802733 num_examples: 3138 - name: validation num_bytes: 1382140 num_examples: 945 - name: test num_bytes: 1314084 num_examples: 881 download_size: 5491427 dataset_size: 8498957 - config_name: sa_ufal features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 431697 num_examples: 230 download_size: 424675 dataset_size: 431697 - config_name: sa_vedic features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 2179608 num_examples: 2524 - name: test num_bytes: 1209605 num_examples: 1473 download_size: 2041583 dataset_size: 3389213 - config_name: gd_arcosg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 3952356 num_examples: 1990 - name: validation num_bytes: 1038211 num_examples: 645 - name: test num_bytes: 1034788 num_examples: 538 download_size: 3474087 dataset_size: 6025355 - config_name: sr_set features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 9309552 num_examples: 3328 - name: validation num_bytes: 1503953 num_examples: 536 - name: test num_bytes: 1432672 num_examples: 520 download_size: 7414381 dataset_size: 12246177 - config_name: sms_giellagas features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 174744 num_examples: 104 download_size: 116491 dataset_size: 174744 - config_name: sk_snk features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 12017312 num_examples: 8483 - name: validation num_bytes: 1863926 num_examples: 1060 - name: test num_bytes: 1943012 num_examples: 1061 download_size: 10013420 dataset_size: 15824250 - config_name: sl_ssj features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - 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name: test num_bytes: 1493885 num_examples: 1110 download_size: 2655777 dataset_size: 4397560 - config_name: soj_aha features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 6218 num_examples: 8 download_size: 4577 dataset_size: 6218 - config_name: ajp_madar features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 71956 num_examples: 100 download_size: 43174 dataset_size: 71956 - config_name: es_ancora features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 50101327 num_examples: 14305 - name: validation num_bytes: 5883940 num_examples: 1654 - name: test num_bytes: 5928986 num_examples: 1721 download_size: 37668083 dataset_size: 61914253 - config_name: es_gsd features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 39582074 num_examples: 14187 - name: validation num_bytes: 3834443 num_examples: 1400 - name: test num_bytes: 1253720 num_examples: 426 download_size: 26073760 dataset_size: 44670237 - config_name: es_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2595946 num_examples: 1000 download_size: 1628475 dataset_size: 2595946 - config_name: swl_sslc features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 57443 num_examples: 87 - name: validation num_bytes: 59002 num_examples: 82 - name: test num_bytes: 24542 num_examples: 34 download_size: 81699 dataset_size: 140987 - config_name: sv_lines features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 6731662 num_examples: 3176 - name: validation num_bytes: 2239951 num_examples: 1032 - name: test num_bytes: 2070626 num_examples: 1035 download_size: 7245283 dataset_size: 11042239 - config_name: sv_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2554725 num_examples: 1000 download_size: 1722516 dataset_size: 2554725 - config_name: sv_talbanken features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 9287256 num_examples: 4303 - name: validation num_bytes: 1361535 num_examples: 504 - name: test num_bytes: 2835742 num_examples: 1219 download_size: 8476012 dataset_size: 13484533 - config_name: gsw_uzh features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 111357 num_examples: 100 download_size: 59675 dataset_size: 111357 - config_name: tl_trg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 86696 num_examples: 128 download_size: 61344 dataset_size: 86696 - config_name: tl_ugnayan features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 90863 num_examples: 94 download_size: 55207 dataset_size: 90863 - config_name: ta_mwtt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 522349 num_examples: 534 download_size: 414263 dataset_size: 522349 - config_name: ta_ttb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1538780 num_examples: 400 - name: validation num_bytes: 305206 num_examples: 80 - name: test num_bytes: 478941 num_examples: 120 download_size: 1753448 dataset_size: 2322927 - config_name: te_mtg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 703512 num_examples: 1051 - name: validation num_bytes: 91547 num_examples: 131 - name: test num_bytes: 99757 num_examples: 146 download_size: 643764 dataset_size: 894816 - config_name: th_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2341697 num_examples: 1000 download_size: 1606517 dataset_size: 2341697 - config_name: tpn_tudet features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 8089 num_examples: 8 download_size: 5447 dataset_size: 8089 - config_name: qtd_sagt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 583697 num_examples: 285 - name: validation num_bytes: 1564765 num_examples: 801 - name: test num_bytes: 1710777 num_examples: 805 download_size: 2299611 dataset_size: 3859239 - config_name: tr_boun features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 12827173 num_examples: 7803 - name: validation num_bytes: 1577760 num_examples: 979 - name: test num_bytes: 1580727 num_examples: 979 download_size: 9742035 dataset_size: 15985660 - config_name: tr_gb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2146729 num_examples: 2880 download_size: 1474083 dataset_size: 2146729 - config_name: tr_imst features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 5063905 num_examples: 3664 - name: validation num_bytes: 1342351 num_examples: 988 - name: test num_bytes: 1347524 num_examples: 983 download_size: 4711018 dataset_size: 7753780 - config_name: tr_pud features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 2021772 num_examples: 1000 download_size: 1359487 dataset_size: 2021772 - config_name: uk_iu features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 18886802 num_examples: 5496 - name: validation num_bytes: 2592721 num_examples: 672 - name: test num_bytes: 3561164 num_examples: 892 download_size: 17344586 dataset_size: 25040687 - config_name: hsb_ufal features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 54257 num_examples: 23 - name: test num_bytes: 1246592 num_examples: 623 download_size: 781067 dataset_size: 1300849 - config_name: ur_udtb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 19808745 num_examples: 4043 - name: validation num_bytes: 2652349 num_examples: 552 - name: test num_bytes: 2702596 num_examples: 535 download_size: 15901007 dataset_size: 25163690 - config_name: ug_udt features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 2570856 num_examples: 1656 - name: validation num_bytes: 1406032 num_examples: 900 - name: test num_bytes: 1371993 num_examples: 900 download_size: 3455092 dataset_size: 5348881 - config_name: vi_vtb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1689772 num_examples: 1400 - name: validation num_bytes: 948019 num_examples: 800 - name: test num_bytes: 987207 num_examples: 800 download_size: 2055529 dataset_size: 3624998 - config_name: wbp_ufal features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 48533 num_examples: 55 download_size: 38326 dataset_size: 48533 - config_name: cy_ccg features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 1629465 num_examples: 704 - name: test num_bytes: 1779002 num_examples: 953 download_size: 1984759 dataset_size: 3408467 - config_name: wo_wtb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: train num_bytes: 2781883 num_examples: 1188 - name: validation num_bytes: 1204839 num_examples: 449 - name: test num_bytes: 1227124 num_examples: 470 download_size: 3042699 dataset_size: 5213846 - config_name: yo_ytb features: - name: idx dtype: string - name: text dtype: string - name: tokens sequence: string - name: lemmas sequence: string - name: upos sequence: class_label: names: '0': NOUN '1': PUNCT '2': ADP '3': NUM '4': SYM '5': SCONJ '6': ADJ '7': PART '8': DET '9': CCONJ '10': PROPN '11': PRON '12': X '13': _ '14': ADV '15': INTJ '16': VERB '17': AUX - name: xpos sequence: string - name: feats sequence: string - name: head sequence: string - name: deprel sequence: string - name: deps sequence: string - name: misc sequence: string splits: - name: test num_bytes: 905766 num_examples: 318 download_size: 567955 dataset_size: 905766 config_names: - af_afribooms - aii_as - ajp_madar - akk_pisandub - akk_riao - am_att - apu_ufpa - aqz_tudet - ar_nyuad - ar_padt - ar_pud - be_hse - bg_btb - bho_bhtb - bm_crb - br_keb - bxr_bdt - ca_ancora - ckt_hse - cop_scriptorium - cs_cac - cs_cltt - cs_fictree - cs_pdt - cs_pud - cu_proiel - cy_ccg - da_ddt - de_gsd - de_hdt - de_lit - de_pud - el_gdt - en_esl - en_ewt - en_gum - en_gumreddit - en_lines - en_partut - en_pronouns - en_pud - es_ancora - es_gsd - es_pud - et_edt - et_ewt - eu_bdt - fa_perdt - fa_seraji - fi_ftb - fi_ood - fi_pud - fi_tdt - fo_farpahc - fo_oft - fr_fqb - fr_ftb - fr_gsd - fr_partut - fr_pud - fr_sequoia - fr_spoken - fro_srcmf - ga_idt - gd_arcosg - gl_ctg - gl_treegal - got_proiel - grc_perseus - grc_proiel - gsw_uzh - gun_dooley - gun_thomas - gv_cadhan - he_htb - hi_hdtb - hi_pud - hr_set - hsb_ufal - hu_szeged - hy_armtdp - id_csui - id_gsd - id_pud - is_icepahc - is_pud - it_isdt - it_partut - it_postwita - it_pud - it_twittiro - it_vit - ja_bccwj - ja_gsd - ja_modern - ja_pud - kfm_aha - kk_ktb - kmr_mg - ko_gsd - ko_kaist - ko_pud - koi_uh - kpv_ikdp - kpv_lattice - krl_kkpp - la_ittb - la_llct - la_perseus - la_proiel - lt_alksnis - lt_hse - lv_lvtb - lzh_kyoto - mdf_jr - mr_ufal - mt_mudt - myu_tudet - myv_jr - nl_alpino - nl_lassysmall - no_bokmaal - no_nynorsk - no_nynorsklia - nyq_aha - olo_kkpp - orv_rnc - orv_torot - otk_tonqq - pcm_nsc - pl_lfg - pl_pdb - pl_pud - pt_bosque - pt_gsd - pt_pud - qhe_hiencs - qtd_sagt - ro_nonstandard - ro_rrt - ro_simonero - ru_gsd - ru_pud - ru_syntagrus - ru_taiga - sa_ufal - sa_vedic - sk_snk - sl_ssj - sl_sst - sme_giella - sms_giellagas - soj_aha - sq_tsa - sr_set - sv_lines - sv_pud - sv_talbanken - swl_sslc - ta_mwtt - ta_ttb - te_mtg - th_pud - tl_trg - tl_ugnayan - tpn_tudet - tr_boun - tr_gb - tr_imst - tr_pud - ug_udt - uk_iu - ur_udtb - vi_vtb - wbp_ufal - wo_wtb - yo_ytb - yue_hk - zh_cfl - zh_gsd - zh_gsdsimp - zh_hk - zh_pud --- # Dataset Card for Universal Dependencies Treebank ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [Universal Dependencies](https://universaldependencies.org/) - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@jplu](https://github.com/jplu) for adding this dataset.

luulinh90s/chm-corr-prj-giang

luulinh90s

--- license: mit ---

Helsinki-NLP/news_commentary

Helsinki-NLP

--- annotations_creators: - found language_creators: - found language: - ar - cs - de - en - es - fr - it - ja - nl - pt - ru - zh license: - unknown multilinguality: - multilingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - translation task_ids: [] pretty_name: News-Commentary dataset_info: - config_name: ar-cs features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - cs splits: - name: train num_bytes: 51546388 num_examples: 52128 download_size: 28342257 dataset_size: 51546388 - config_name: ar-de features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - de splits: - name: train num_bytes: 69681335 num_examples: 68916 download_size: 37202855 dataset_size: 69681335 - config_name: ar-en features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - en splits: - name: train num_bytes: 80655165 num_examples: 83187 download_size: 42807620 dataset_size: 80655165 - config_name: ar-es features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - es splits: - name: train num_bytes: 79255889 num_examples: 78074 download_size: 42005622 dataset_size: 79255889 - config_name: ar-fr features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - fr splits: - name: train num_bytes: 71034977 num_examples: 69157 download_size: 37543169 dataset_size: 71034977 - config_name: ar-it features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - it splits: - name: train num_bytes: 17413426 num_examples: 17227 download_size: 9186088 dataset_size: 17413426 - config_name: ar-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - ja splits: - name: train num_bytes: 661980 num_examples: 569 download_size: 354690 dataset_size: 661980 - config_name: ar-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - nl splits: - name: train num_bytes: 9054122 num_examples: 9047 download_size: 4808380 dataset_size: 9054122 - config_name: ar-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - pt splits: - name: train num_bytes: 11340050 num_examples: 11433 download_size: 6098489 dataset_size: 11340050 - config_name: ar-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - ru splits: - name: train num_bytes: 105804195 num_examples: 84455 download_size: 52467607 dataset_size: 105804195 - config_name: ar-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - ar - zh splits: - name: train num_bytes: 65483120 num_examples: 66021 download_size: 36527030 dataset_size: 65483120 - config_name: cs-de features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - de splits: - name: train num_bytes: 57470583 num_examples: 172706 download_size: 37013107 dataset_size: 57470583 - config_name: cs-en features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - en splits: - name: train num_bytes: 54487658 num_examples: 177278 download_size: 35385370 dataset_size: 54487658 - config_name: cs-es features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - es splits: - name: train num_bytes: 56794609 num_examples: 170489 download_size: 36325813 dataset_size: 56794609 - config_name: cs-fr features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - fr splits: - name: train num_bytes: 50364657 num_examples: 148578 download_size: 31970167 dataset_size: 50364657 - config_name: cs-it features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - it splits: - name: train num_bytes: 10441797 num_examples: 30547 download_size: 6651753 dataset_size: 10441797 - config_name: cs-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - ja splits: - name: train num_bytes: 487890 num_examples: 622 download_size: 304917 dataset_size: 487890 - config_name: cs-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - nl splits: - name: train num_bytes: 5860952 num_examples: 17358 download_size: 3727739 dataset_size: 5860952 - config_name: cs-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - pt splits: - name: train num_bytes: 6183701 num_examples: 18356 download_size: 3984228 dataset_size: 6183701 - config_name: cs-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - ru splits: - name: train num_bytes: 71185491 num_examples: 161133 download_size: 40217853 dataset_size: 71185491 - config_name: cs-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - cs - zh splits: - name: train num_bytes: 29971132 num_examples: 45424 download_size: 20270691 dataset_size: 29971132 - config_name: de-en features: - name: id dtype: string - name: translation dtype: translation: languages: - de - en splits: - name: train num_bytes: 73085175 num_examples: 223153 download_size: 45240694 dataset_size: 73085175 - config_name: de-es features: - name: id dtype: string - name: translation dtype: translation: languages: - de - es splits: - name: train num_bytes: 74708488 num_examples: 209839 download_size: 45574007 dataset_size: 74708488 - config_name: de-fr features: - name: id dtype: string - name: translation dtype: translation: languages: - de - fr splits: - name: train num_bytes: 67083671 num_examples: 185442 download_size: 40685965 dataset_size: 67083671 - config_name: de-it features: - name: id dtype: string - name: translation dtype: translation: languages: - de - it splits: - name: train num_bytes: 13993406 num_examples: 38961 download_size: 8509324 dataset_size: 13993406 - config_name: de-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - de - ja splits: - name: train num_bytes: 465563 num_examples: 582 download_size: 281101 dataset_size: 465563 - config_name: de-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - de - nl splits: - name: train num_bytes: 7645529 num_examples: 21439 download_size: 4664824 dataset_size: 7645529 - config_name: de-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - de - pt splits: - name: train num_bytes: 7699047 num_examples: 21884 download_size: 4755247 dataset_size: 7699047 - config_name: de-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - de - ru splits: - name: train num_bytes: 81811798 num_examples: 175905 download_size: 44732705 dataset_size: 81811798 - config_name: de-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - de - zh splits: - name: train num_bytes: 39044632 num_examples: 59020 download_size: 25362199 dataset_size: 39044632 - config_name: en-es features: - name: id dtype: string - name: translation dtype: translation: languages: - en - es splits: - name: train num_bytes: 78600501 num_examples: 238872 download_size: 48099801 dataset_size: 78600501 - config_name: en-fr features: - name: id dtype: string - name: translation dtype: translation: languages: - en - fr splits: - name: train num_bytes: 70339762 num_examples: 209479 download_size: 42791798 dataset_size: 70339762 - config_name: en-it features: - name: id dtype: string - name: translation dtype: translation: languages: - en - it splits: - name: train num_bytes: 14213912 num_examples: 40009 download_size: 8519809 dataset_size: 14213912 - config_name: en-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - en - ja splits: - name: train num_bytes: 485472 num_examples: 637 download_size: 292084 dataset_size: 485472 - config_name: en-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - en - nl splits: - name: train num_bytes: 7316575 num_examples: 19399 download_size: 4313377 dataset_size: 7316575 - config_name: en-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - en - pt splits: - name: train num_bytes: 9238783 num_examples: 25929 download_size: 5612678 dataset_size: 9238783 - config_name: en-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - en - ru splits: - name: train num_bytes: 83282240 num_examples: 190104 download_size: 45349681 dataset_size: 83282240 - config_name: en-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - en - zh splits: - name: train num_bytes: 44596003 num_examples: 69206 download_size: 28997427 dataset_size: 44596003 - config_name: es-fr features: - name: id dtype: string - name: translation dtype: translation: languages: - es - fr splits: - name: train num_bytes: 71025693 num_examples: 195241 download_size: 42650193 dataset_size: 71025693 - config_name: es-it features: - name: id dtype: string - name: translation dtype: translation: languages: - es - it splits: - name: train num_bytes: 15139576 num_examples: 41497 download_size: 9097532 dataset_size: 15139576 - config_name: es-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - es - ja splits: - name: train num_bytes: 484451 num_examples: 602 download_size: 289298 dataset_size: 484451 - config_name: es-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - es - nl splits: - name: train num_bytes: 7560087 num_examples: 21012 download_size: 4572049 dataset_size: 7560087 - config_name: es-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - es - pt splits: - name: train num_bytes: 9195649 num_examples: 25551 download_size: 5633226 dataset_size: 9195649 - config_name: es-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - es - ru splits: - name: train num_bytes: 84345622 num_examples: 180217 download_size: 45710609 dataset_size: 84345622 - config_name: es-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - es - zh splits: - name: train num_bytes: 43939929 num_examples: 65424 download_size: 28264415 dataset_size: 43939929 - config_name: fr-it features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - it splits: - name: train num_bytes: 14216031 num_examples: 38485 download_size: 8499047 dataset_size: 14216031 - config_name: fr-ja features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - ja splits: - name: train num_bytes: 418176 num_examples: 519 download_size: 251240 dataset_size: 418176 - config_name: fr-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - nl splits: - name: train num_bytes: 7603467 num_examples: 20898 download_size: 4553502 dataset_size: 7603467 - config_name: fr-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - pt splits: - name: train num_bytes: 9261133 num_examples: 25642 download_size: 5614816 dataset_size: 9261133 - config_name: fr-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - ru splits: - name: train num_bytes: 75967049 num_examples: 160740 download_size: 41078195 dataset_size: 75967049 - config_name: fr-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - fr - zh splits: - name: train num_bytes: 40143999 num_examples: 59060 download_size: 25753128 dataset_size: 40143999 - config_name: it-nl features: - name: id dtype: string - name: translation dtype: translation: languages: - it - nl splits: - name: train num_bytes: 5380888 num_examples: 15428 download_size: 3279009 dataset_size: 5380888 - config_name: it-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - it - pt splits: - name: train num_bytes: 3988546 num_examples: 11407 download_size: 2432377 dataset_size: 3988546 - config_name: it-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - it - ru splits: - name: train num_bytes: 12915037 num_examples: 27267 download_size: 7009784 dataset_size: 12915037 - config_name: it-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - it - zh splits: - name: train num_bytes: 9676732 num_examples: 14652 download_size: 6219158 dataset_size: 9676732 - config_name: ja-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - ja - ru splits: - name: train num_bytes: 596154 num_examples: 586 download_size: 324916 dataset_size: 596154 - config_name: ja-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - ja - zh splits: - name: train num_bytes: 462673 num_examples: 570 download_size: 290801 dataset_size: 462673 - config_name: nl-pt features: - name: id dtype: string - name: translation dtype: translation: languages: - nl - pt splits: - name: train num_bytes: 3612315 num_examples: 10598 download_size: 2204974 dataset_size: 3612315 - config_name: nl-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - nl - ru splits: - name: train num_bytes: 8933781 num_examples: 19112 download_size: 4857132 dataset_size: 8933781 - config_name: nl-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - nl - zh splits: - name: train num_bytes: 5509058 num_examples: 8433 download_size: 3573395 dataset_size: 5509058 - config_name: pt-ru features: - name: id dtype: string - name: translation dtype: translation: languages: - pt - ru splits: - name: train num_bytes: 8645451 num_examples: 18458 download_size: 4739066 dataset_size: 8645451 - config_name: pt-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - pt - zh splits: - name: train num_bytes: 7152750 num_examples: 10873 download_size: 4668616 dataset_size: 7152750 - config_name: ru-zh features: - name: id dtype: string - name: translation dtype: translation: languages: - ru - zh splits: - name: train num_bytes: 43112764 num_examples: 47687 download_size: 24587160 dataset_size: 43112764 configs: - config_name: ar-cs data_files: - split: train path: ar-cs/train-* - config_name: ar-de data_files: - split: train path: ar-de/train-* - config_name: ar-en data_files: - split: train path: ar-en/train-* - config_name: ar-es data_files: - split: train path: ar-es/train-* - config_name: ar-fr data_files: - split: train path: ar-fr/train-* - config_name: ar-it data_files: - split: train path: ar-it/train-* - config_name: ar-ja data_files: - split: train path: ar-ja/train-* - config_name: ar-nl data_files: - split: train path: ar-nl/train-* - config_name: ar-pt data_files: - split: train path: ar-pt/train-* - config_name: ar-ru data_files: - split: train path: ar-ru/train-* - config_name: ar-zh data_files: - split: train path: ar-zh/train-* - config_name: cs-de data_files: - split: train path: cs-de/train-* - config_name: cs-en data_files: - split: train path: cs-en/train-* - config_name: cs-es data_files: - split: train path: cs-es/train-* - config_name: cs-fr data_files: - split: train path: cs-fr/train-* - config_name: cs-it data_files: - split: train path: cs-it/train-* - config_name: cs-ja data_files: - split: train path: cs-ja/train-* - config_name: cs-nl data_files: - split: train path: cs-nl/train-* - config_name: cs-pt data_files: - split: train path: cs-pt/train-* - config_name: cs-ru data_files: - split: train path: cs-ru/train-* - config_name: cs-zh data_files: - split: train path: cs-zh/train-* - config_name: de-en data_files: - split: train path: de-en/train-* - config_name: de-es data_files: - split: train path: de-es/train-* - config_name: de-fr data_files: - split: train path: de-fr/train-* - config_name: de-it data_files: - split: train path: de-it/train-* - config_name: de-ja data_files: - split: train path: de-ja/train-* - config_name: de-nl data_files: - split: train path: de-nl/train-* - config_name: de-pt data_files: - split: train path: de-pt/train-* - config_name: de-ru data_files: - split: train path: de-ru/train-* - config_name: de-zh data_files: - split: train path: de-zh/train-* - config_name: en-es data_files: - split: train path: en-es/train-* - config_name: en-fr data_files: - split: train path: en-fr/train-* - config_name: en-it data_files: - split: train path: en-it/train-* - config_name: en-ja data_files: - split: train path: en-ja/train-* - config_name: en-nl data_files: - split: train path: en-nl/train-* - config_name: en-pt data_files: - split: train path: en-pt/train-* - config_name: en-ru data_files: - split: train path: en-ru/train-* - config_name: en-zh data_files: - split: train path: en-zh/train-* - config_name: es-fr data_files: - split: train path: es-fr/train-* - config_name: es-it data_files: - split: train path: es-it/train-* - config_name: es-ja data_files: - split: train path: es-ja/train-* - config_name: es-nl data_files: - split: train path: es-nl/train-* - config_name: es-pt data_files: - split: train path: es-pt/train-* - config_name: es-ru data_files: - split: train path: es-ru/train-* - config_name: es-zh data_files: - split: train path: es-zh/train-* - config_name: fr-it data_files: - split: train path: fr-it/train-* - config_name: fr-ja data_files: - split: train path: fr-ja/train-* - config_name: fr-nl data_files: - split: train path: fr-nl/train-* - config_name: fr-pt data_files: - split: train path: fr-pt/train-* - config_name: fr-ru data_files: - split: train path: fr-ru/train-* - config_name: fr-zh data_files: - split: train path: fr-zh/train-* - config_name: it-nl data_files: - split: train path: it-nl/train-* - config_name: it-pt data_files: - split: train path: it-pt/train-* - config_name: it-ru data_files: - split: train path: it-ru/train-* - config_name: it-zh data_files: - split: train path: it-zh/train-* - config_name: ja-ru data_files: - split: train path: ja-ru/train-* - config_name: ja-zh data_files: - split: train path: ja-zh/train-* - config_name: nl-pt data_files: - split: train path: nl-pt/train-* - config_name: nl-ru data_files: - split: train path: nl-ru/train-* - config_name: nl-zh data_files: - split: train path: nl-zh/train-* - config_name: pt-ru data_files: - split: train path: pt-ru/train-* - config_name: pt-zh data_files: - split: train path: pt-zh/train-* - config_name: ru-zh data_files: - split: train path: ru-zh/train-* --- # Dataset Card for OPUS News-Commentary ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://opus.nlpl.eu/News-Commentary/corpus/version/News-Commentary - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** https://aclanthology.org/L12-1246/ - **Leaderboard:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Dataset Summary [More Information Needed] ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data [More Information Needed] #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations [More Information Needed] #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information Please cite the following article if you use any part of the OPUS corpus in your own work: ```bibtex @inproceedings{tiedemann-2012-parallel, title = "Parallel Data, Tools and Interfaces in {OPUS}", author = {Tiedemann, J{\"o}rg}, editor = "Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Do{\u{g}}an, Mehmet U{\u{g}}ur and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios", booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)", month = may, year = "2012", address = "Istanbul, Turkey", publisher = "European Language Resources Association (ELRA)", url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/463_Paper.pdf", pages = "2214--2218", } ``` ### Contributions Thanks to [@abhishekkrthakur](https://github.com/abhishekkrthakur) for adding this dataset.

SLPL/naab

SLPL

--- language: - fa license: - mit multilinguality: - monolingual size_categories: - 100M<n<1B task_categories: - fill-mask - text-generation task_ids: - language-modeling - masked-language-modeling pretty_name: naab (A ready-to-use plug-and-play corpus in Farsi) --- # naab: A ready-to-use plug-and-play corpus in Farsi _[If you want to join our community to keep up with news, models and datasets from naab, click on [this](https://docs.google.com/forms/d/e/1FAIpQLSe8kevFl_ODCx-zapAuOIAQYr8IvkVVaVHOuhRL9Ha0RVJ6kg/viewform) link.]_ ## Table of Contents - [Dataset Card Creation Guide](#dataset-card-creation-guide) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [Sharif Speech and Language Processing Lab](https://huggingface.co/SLPL) - **Paper:** [naab: A ready-to-use plug-and-play corpus for Farsi](https://arxiv.org/abs/2208.13486) - **Point of Contact:** [Sadra Sabouri](mailto:[email protected]) ### Dataset Summary naab is the biggest cleaned and ready-to-use open-source textual corpus in Farsi. It contains about 130GB of data, 250 million paragraphs, and 15 billion words. The project name is derived from the Farsi word ناب which means pure and high-grade. We also provide the raw version of the corpus called naab-raw and an easy-to-use pre-processor that can be employed by those who wanted to make a customized corpus. You can use this corpus by the commands below: ```python from datasets import load_dataset dataset = load_dataset("SLPL/naab") ``` You may need to download parts/splits of this corpus too, if so use the command below (You can find more ways to use it [here](https://huggingface.co/docs/datasets/loading#slice-splits)): ```python from datasets import load_dataset dataset = load_dataset("SLPL/naab", split="train[:10%]") ``` **Note: be sure that your machine has at least 130 GB free space, also it may take a while to download. If you are facing disk or internet shortage, you can use below code snippet helping you download your costume sections of the naab:** ```python from datasets import load_dataset # ========================================================== # You should just change this part in order to download your # parts of corpus. indices = { "train": [5, 1, 2], "test": [0, 2] } # ========================================================== N_FILES = { "train": 126, "test": 3 } _BASE_URL = "https://huggingface.co/datasets/SLPL/naab/resolve/main/data/" data_url = { "train": [_BASE_URL + "train-{:05d}-of-{:05d}.txt".format(x, N_FILES["train"]) for x in range(N_FILES["train"])], "test": [_BASE_URL + "test-{:05d}-of-{:05d}.txt".format(x, N_FILES["test"]) for x in range(N_FILES["test"])], } for index in indices['train']: assert index < N_FILES['train'] for index in indices['test']: assert index < N_FILES['test'] data_files = { "train": [data_url['train'][i] for i in indices['train']], "test": [data_url['test'][i] for i in indices['test']] } print(data_files) dataset = load_dataset('text', data_files=data_files, use_auth_token=True) ``` ### Supported Tasks and Leaderboards This corpus can be used for training all language models which can be trained by Masked Language Modeling (MLM) or any other self-supervised objective. - `language-modeling` - `masked-language-modeling` ## Dataset Structure Each row of the dataset will look like something like the below: ```json { 'text': "این یک تست برای نمایش یک پاراگراف در پیکره متنی ناب است.", } ``` + `text` : the textual paragraph. ### Data Splits This dataset includes two splits (`train` and `test`). We split these two by dividing the randomly permuted version of the corpus into (95%, 5%) division respected to (`train`, `test`). Since `validation` is usually occurring during training with the `train` dataset we avoid proposing another split for it. | | train | test | |-------------------------|------:|-----:| | Input Sentences | 225892925 | 11083849 | | Average Sentence Length | 61 | 25 | Below you can see the log-based histogram of word/paragraph over the two splits of the dataset. <div align="center"> <img src="https://huggingface.co/datasets/SLPL/naab/resolve/main/naab-hist.png"> </div> ## Dataset Creation ### Curation Rationale Due to the lack of a huge amount of text data in lower resource languages - like Farsi - researchers working on these languages were always finding it hard to start to fine-tune such models. This phenomenon can lead to a situation in which the golden opportunity for fine-tuning models is just in hands of a few companies or countries which contributes to the weakening the open science. The last biggest cleaned merged textual corpus in Farsi is a 70GB cleaned text corpus from a compilation of 8 big data sets that have been cleaned and can be downloaded directly. Our solution to the discussed issues is called naab. It provides **126GB** (including more than **224 million** sequences and nearly **15 billion** words) as the training corpus and **2.3GB** (including nearly **11 million** sequences and nearly **300 million** words) as the test corpus. ### Source Data The textual corpora that we used as our source data are illustrated in the figure below. It contains 5 corpora which are linked in the coming sections. <div align="center"> <img src="https://huggingface.co/datasets/SLPL/naab/resolve/main/naab-pie.png"> </div> #### Persian NLP [This](https://github.com/persiannlp/persian-raw-text) corpus includes eight corpora that are sorted based on their volume as below: - [Common Crawl](https://commoncrawl.org/): 65GB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/commoncrawl_fa_merged.txt)) - [MirasText](https://github.com/miras-tech/MirasText): 12G - [W2C – Web to Corpus](https://lindat.mff.cuni.cz/repository/xmlui/handle/11858/00-097C-0000-0022-6133-9): 1GB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/w2c_merged.txt)) - Persian Wikipedia (March 2020 dump): 787MB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/fawiki_merged.txt)) - [Leipzig Corpora](https://corpora.uni-leipzig.de/): 424M ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/LeipzigCorpus.txt)) - [VOA corpus](https://jon.dehdari.org/corpora/): 66MB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/voa_persian_2003_2008_cleaned.txt)) - [Persian poems corpus](https://github.com/amnghd/Persian_poems_corpus): 61MB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/poems_merged.txt)) - [TEP: Tehran English-Persian parallel corpus](http://opus.nlpl.eu/TEP.php): 33MB ([link](https://storage.googleapis.com/danielk-files/farsi-text/merged_files/TEP_fa.txt)) #### AGP This corpus was a formerly private corpus for ASR Gooyesh Pardaz which is now published for all users by this project. This corpus contains more than 140 million paragraphs summed up in 23GB (after cleaning). This corpus is a mixture of both formal and informal paragraphs that are crawled from different websites and/or social media. #### OSCAR-fa [OSCAR](https://oscar-corpus.com/) or Open Super-large Crawled ALMAnaCH coRpus is a huge multilingual corpus obtained by language classification and filtering of the Common Crawl corpus using the go classy architecture. Data is distributed by language in both original and deduplicated form. We used the unshuffled-deduplicated-fa from this corpus, after cleaning there were about 36GB remaining. #### Telegram Telegram, a cloud-based instant messaging service, is a widely used application in Iran. Following this hypothesis, we prepared a list of Telegram channels in Farsi covering various topics including sports, daily news, jokes, movies and entertainment, etc. The text data extracted from mentioned channels mainly contains informal data. #### LSCP [The Large Scale Colloquial Persian Language Understanding dataset](https://iasbs.ac.ir/~ansari/lscp/) has 120M sentences from 27M casual Persian sentences with its derivation tree, part-of-speech tags, sentiment polarity, and translations in English, German, Czech, Italian, and Hindi. However, we just used the Farsi part of it and after cleaning we had 2.3GB of it remaining. Since the dataset is casual, it may help our corpus have more informal sentences although its proportion to formal paragraphs is not comparable. #### Initial Data Collection and Normalization The data collection process was separated into two parts. In the first part, we searched for existing corpora. After downloading these corpora we started to crawl data from some social networks. Then thanks to [ASR Gooyesh Pardaz](https://asr-gooyesh.com/en/) we were provided with enough textual data to start the naab journey. We used a preprocessor based on some stream-based Linux kernel commands so that this process can be less time/memory-consuming. The code is provided [here](https://github.com/Sharif-SLPL/t5-fa/tree/main/preprocess). ### Personal and Sensitive Information Since this corpus is briefly a compilation of some former corpora we take no responsibility for personal information included in this corpus. If you detect any of these violations please let us know, we try our best to remove them from the corpus ASAP. We tried our best to provide anonymity while keeping the crucial information. We shuffled some parts of the corpus so the information passing through possible conversations wouldn't be harmful. ## Additional Information ### Dataset Curators + Sadra Sabouri (Sharif University of Technology) + Elnaz Rahmati (Sharif University of Technology) ### Licensing Information mit? ### Citation Information ``` @article{sabouri2022naab, title={naab: A ready-to-use plug-and-play corpus for Farsi}, author={Sabouri, Sadra and Rahmati, Elnaz and Gooran, Soroush and Sameti, Hossein}, journal={arXiv preprint arXiv:2208.13486}, year={2022} } ``` DOI: [https://doi.org/10.48550/arXiv.2208.13486](https://doi.org/10.48550/arXiv.2208.13486) ### Contributions Thanks to [@sadrasabouri](https://github.com/sadrasabouri) and [@elnazrahmati](https://github.com/elnazrahmati) for adding this dataset. ### Keywords + Farsi + Persian + raw text + پیکره فارسی + پیکره متنی + آموزش مدل زبانی

aklein4/OpenHermes-Llama-3.2-Instruct-Shuffled

aklein4

--- dataset_info: features: - name: __key__ dtype: string - name: __url__ dtype: string - name: gen_mask.npy sequence: bool - name: input_ids.npy sequence: uint32 - name: pad_mask.npy sequence: bool - name: segment_ids.npy sequence: uint32 - name: text.txt dtype: string splits: - name: train num_bytes: 4970493095.0 num_examples: 374215 download_size: 1516295098 dataset_size: 4970493095.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

HuggingFaceM4/WebSight

HuggingFaceM4

--- language: - en license: cc-by-4.0 size_categories: - 1M<n<10M pretty_name: WebSight dataset_info: - config_name: v0.2 features: - name: image dtype: image - name: text dtype: string - name: llm_generated_idea dtype: string splits: - name: train num_bytes: 368943620718.125 num_examples: 1922671 download_size: 144861710051 dataset_size: 368943620718.125 - config_name: v0.1 features: - name: image dtype: image - name: text dtype: string splits: - name: train num_bytes: 35386660486.65 num_examples: 822987 download_size: 31394170440 dataset_size: 35386660486.65 configs: - config_name: v0.2 default: true data_files: - split: train path: v0.2/train-* - config_name: v0.1 data_files: - split: train path: data/train-* tags: - code - synthetic --- # Dataset Card for WebSight ## Dataset Description WebSight is a large synthetic dataset containing HTML/CSS codes representing synthetically generated English websites, each accompanied by a corresponding screenshot. This dataset serves as a valuable resource for tasks such as generating UI codes from a screenshot. It comes in two versions: - v0.1: Websites are coded with HTML + CSS. They do not include real images. - v0.2: Websites are coded with HTML + Tailwind CSS. They do include real images. Essentially, here are the improvements in version v0.2, compared to version v0.1: - Websites include real images (related to the context of the website!!) - Usage of Tailwind CSS instead of traditional CSS - Contains 2x more examples - Contains more tables - Better resolution for the screenshots - Presence of a column indicating the LLM-generated idea to create the websites <details> <summary>Details for WebSight-v0.1 (HTML + CSS)</summary> ## Data Fields An example of a sample appears as follows: ``` { 'images': PIL.Image, 'text': '<html>\n<style>\n{css}</style>\n{body}\n</html>', } ``` where `css` is the CSS code, and `body` is the body of the HTML code. In other words, the CSS code is embedded directly within the HTML code, facilitating the straightforward training of a model. ## Data Splits There is only one split, `train`, that contains 822,987 images and codes. ## Dataset Creation This dataset was created using [Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) to generate random website ideas with the prompt ``` Generate diverse website layout ideas for different companies, each with a unique design element. Examples include: a car company site with a left column, a webpage footer with a centered logo. Explore variations in colors, positions, and company fields. Don't give any explanations or recognition that you have understood the request, just give the list of 10 ideas, with a line break between each. ``` which were then passed to [Deepseek-Coder-33b-Instruct](https://huggingface.co/deepseek-ai/deepseek-coder-33b-instruct) with the prompt ``` Create a very SIMPLE and SHORT website with the following elements: {idea} Be creative with the design, size, position of the elements, columns, etc... Don't give any explanation, just the content of the HTML code `index.html` starting with `<!DOCTYPE html>`, followed by the CSS code `styles.css` starting with `/* Global Styles */`. Write real and short sentences for the paragraphs, don't use Lorem ipsum. When you want to display an image, don't use <img> in the HTML, always display a colored rectangle instead. ``` Following these steps, the HTML and CSS codes were extracted from the outputs of Deepseek-Coder and formatted into the structure `'<html>\n<style>\n{css}</style>\n{body}\n</html>'`. </details> <details> <summary>Details for WebSight-v0.2 (HTML + Tailwind CSS)</summary> ## Data Fields An example of a sample appears as follows: ``` { 'images': PIL.Image, 'text': '<html>\n<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/tailwind.min.css" rel="stylesheet">\n{body}\n</html>', } ``` where `body` is the body of the HTML code, containing directly the Tailwind CSS code and facilitating the straightforward training of a model. ## Data Splits There is only one split, `train`, that contains TO DO images and codes. ## Dataset Creation TO DO. For now, the creation of the dataset is documented in the technical report. </details> ## Terms of Use By using the dataset, you agree to comply with the original licenses of the source content as well as the dataset license (CC-BY-4.0). Additionally, if you use this dataset to train a Machine Learning model, you agree to disclose your use of the dataset when releasing the model or an ML application using the model. ### Licensing Information License CC-BY-4.0. ### Citation Information If you are using this dataset, please cite our [technical report](https://arxiv.org/abs/2403.09029) ``` @misc{laurençon2024unlocking, title={Unlocking the conversion of Web Screenshots into HTML Code with the WebSight Dataset}, author={Hugo Laurençon and Léo Tronchon and Victor Sanh}, year={2024}, eprint={2403.09029}, archivePrefix={arXiv}, primaryClass={cs.HC} } ```

fsicoli/common_voice_15_0

fsicoli

--- license: cc language: - ab - af - am - ar - as - ast - az - ba - bas - be - bg - bn - br - ca - ckb - cnh - cs - cv - cy - da - de - dv - dyu - el - en - eo - es - et - eu - fa - fi - fr - gl - gn - ha - he - hi - hsb - hu - ia - id - ig - is - it - ja - ka - kab - kk - kmr - ko - ky - lg - lo - lt - lv - mdf - mhr - mk - ml - mn - mr - mrj - mt - myv - nl - oc - or - pl - ps - pt - quy - ro - ru - rw - sah - sat - sc - sk - skr - sl - sq - sr - sw - ta - th - ti - tig - tk - tok - tr - tt - tw - ug - uk - ur - uz - vi - vot - yue - zgh - zh - yo task_categories: - automatic-speech-recognition pretty_name: Common Voice Corpus 15.0 size_categories: - 100B<n<1T tags: - mozilla - foundation --- # Dataset Card for Common Voice Corpus 15.0 <!-- Provide a quick summary of the dataset. --> This dataset is an unofficial version of the Mozilla Common Voice Corpus 15. It was downloaded and converted from the project's website https://commonvoice.mozilla.org/. ## Languages ``` Abkhaz, Albanian, Amharic, Arabic, Armenian, Assamese, Asturian, Azerbaijani, Basaa, Bashkir, Basque, Belarusian, Bengali, Breton, Bulgarian, Cantonese, Catalan, Central Kurdish, Chinese (China), Chinese (Hong Kong), Chinese (Taiwan), Chuvash, Czech, Danish, Dhivehi, Dioula, Dutch, English, Erzya, Esperanto, Estonian, Finnish, French, Frisian, Galician, Georgian, German, Greek, Guarani, Hakha Chin, Hausa, Hill Mari, Hindi, Hungarian, Icelandic, Igbo, Indonesian, Interlingua, Irish, Italian, Japanese, Kabyle, Kazakh, Kinyarwanda, Korean, Kurmanji Kurdish, Kyrgyz, Lao, Latvian, Lithuanian, Luganda, Macedonian, Malayalam, Maltese, Marathi, Meadow Mari, Moksha, Mongolian, Nepali, Norwegian Nynorsk, Occitan, Odia, Pashto, Persian, Polish, Portuguese, Punjabi, Quechua Chanka, Romanian, Romansh Sursilvan, Romansh Vallader, Russian, Sakha, Santali (Ol Chiki), Saraiki, Sardinian, Serbian, Slovak, Slovenian, Sorbian, Upper, Spanish, Swahili, Swedish, Taiwanese (Minnan), Tamazight, Tamil, Tatar, Thai, Tigre, Tigrinya, Toki Pona, Turkish, Turkmen, Twi, Ukrainian, Urdu, Uyghur, Uzbek, Vietnamese, Votic, Welsh, Yoruba ``` ## How to use The datasets library allows you to load and pre-process your dataset in pure Python, at scale. The dataset can be downloaded and prepared in one call to your local drive by using the load_dataset function. For example, to download the Portuguese config, simply specify the corresponding language config name (i.e., "pt" for Portuguese): ``` from datasets import load_dataset cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") ``` Using the datasets library, you can also stream the dataset on-the-fly by adding a streaming=True argument to the load_dataset function call. Loading a dataset in streaming mode loads individual samples of the dataset at a time, rather than downloading the entire dataset to disk. ``` from datasets import load_dataset cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train", streaming=True) print(next(iter(cv_15))) ``` Bonus: create a PyTorch dataloader directly with your own datasets (local/streamed). ### Local ``` from datasets import load_dataset from torch.utils.data.sampler import BatchSampler, RandomSampler cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") batch_sampler = BatchSampler(RandomSampler(cv_15), batch_size=32, drop_last=False) dataloader = DataLoader(cv_15, batch_sampler=batch_sampler) ``` ### Streaming ``` from datasets import load_dataset from torch.utils.data import DataLoader cv_15 = load_dataset("fsicoli/common_voice_15_0", "pt", split="train") dataloader = DataLoader(cv_15, batch_size=32) ``` To find out more about loading and preparing audio datasets, head over to hf.co/blog/audio-datasets. ### Dataset Structure Data Instances A typical data point comprises the path to the audio file and its sentence. Additional fields include accent, age, client_id, up_votes, down_votes, gender, locale and segment. ### Licensing Information Public Domain, CC-0 ### Citation Information ``` @inproceedings{commonvoice:2020, author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.}, title = {Common Voice: A Massively-Multilingual Speech Corpus}, booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)}, pages = {4211--4215}, year = 2020 } ```

asahi417/seamless-align-enA-zhA.speaker-embedding.xlsr-2b

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 14209259131 num_examples: 1962 download_size: 14256120203 dataset_size: 14209259131 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13574781625 num_examples: 2031 download_size: 13621966757 dataset_size: 13574781625 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13223964877 num_examples: 1891 download_size: 13269307182 dataset_size: 13223964877 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13038203739 num_examples: 1885 download_size: 13083404216 dataset_size: 13038203739 - config_name: subset_102 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12731679458 num_examples: 1863 download_size: 12775688644 dataset_size: 12731679458 - config_name: subset_103 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12967209285 num_examples: 1861 download_size: 13011071076 dataset_size: 12967209285 - config_name: subset_104 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12798692606 num_examples: 1875 download_size: 12842795816 dataset_size: 12798692606 - config_name: subset_105 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13127114114 num_examples: 1871 download_size: 13172271401 dataset_size: 13127114114 - config_name: subset_106 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12426801586 num_examples: 1865 download_size: 12469421998 dataset_size: 12426801586 - config_name: subset_107 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12484775174 num_examples: 1838 download_size: 12527398592 dataset_size: 12484775174 - config_name: subset_108 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13018346253 num_examples: 1860 download_size: 13063301347 dataset_size: 13018346253 - config_name: subset_109 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12986696298 num_examples: 1866 download_size: 13030608940 dataset_size: 12986696298 - config_name: subset_11 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 13038519979 num_examples: 1994 download_size: 13084550040 dataset_size: 13038519979 - config_name: subset_110 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12537003686 num_examples: 1843 download_size: 12580875152 dataset_size: 12537003686 - config_name: subset_111 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - 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config_name: subset_119 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 12663849536 num_examples: 1823 download_size: 12706307005 dataset_size: 12663849536 - config_name: subset_12 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - 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split: train path: subset_207/train-* - config_name: subset_208 data_files: - split: train path: subset_208/train-* - config_name: subset_209 data_files: - split: train path: subset_209/train-* - config_name: subset_21 data_files: - split: train path: subset_21/train-* - config_name: subset_210 data_files: - split: train path: subset_210/train-* - config_name: subset_211 data_files: - split: train path: subset_211/train-* - config_name: subset_212 data_files: - split: train path: subset_212/train-* - config_name: subset_213 data_files: - split: train path: subset_213/train-* - config_name: subset_214 data_files: - split: train path: subset_214/train-* - config_name: subset_215 data_files: - split: train path: subset_215/train-* - config_name: subset_216 data_files: - split: train path: subset_216/train-* - config_name: subset_217 data_files: - split: train path: subset_217/train-* - config_name: subset_218 data_files: - split: train path: subset_218/train-* - config_name: subset_219 data_files: - split: train path: subset_219/train-* - config_name: subset_22 data_files: - split: train path: subset_22/train-* - config_name: subset_220 data_files: - split: train path: subset_220/train-* - config_name: subset_221 data_files: - split: train path: subset_221/train-* - config_name: subset_222 data_files: - split: train path: subset_222/train-* - config_name: subset_223 data_files: - split: train path: subset_223/train-* - config_name: subset_224 data_files: - split: train path: subset_224/train-* - config_name: subset_225 data_files: - split: train path: subset_225/train-* - config_name: subset_226 data_files: - split: train path: subset_226/train-* - config_name: subset_227 data_files: - split: train path: subset_227/train-* - config_name: subset_228 data_files: - split: train path: subset_228/train-* - config_name: subset_229 data_files: - split: train path: subset_229/train-* - config_name: subset_23 data_files: - split: train path: subset_23/train-* - config_name: subset_230 data_files: - split: train path: subset_230/train-* - config_name: subset_231 data_files: - split: train path: subset_231/train-* - config_name: subset_232 data_files: - split: train path: subset_232/train-* - config_name: subset_233 data_files: - split: train path: subset_233/train-* - config_name: subset_234 data_files: - split: train path: subset_234/train-* - config_name: subset_235 data_files: - split: train path: subset_235/train-* - config_name: subset_236 data_files: - split: train path: subset_236/train-* - config_name: subset_237 data_files: - split: train path: subset_237/train-* - config_name: subset_238 data_files: - split: train path: subset_238/train-* - config_name: subset_239 data_files: - split: train path: subset_239/train-* - config_name: subset_24 data_files: - split: train path: subset_24/train-* - config_name: subset_240 data_files: - split: train path: subset_240/train-* - config_name: subset_241 data_files: - split: train path: subset_241/train-* - config_name: subset_242 data_files: - split: train path: subset_242/train-* - config_name: subset_243 data_files: - split: train path: subset_243/train-* - config_name: subset_244 data_files: - split: train path: subset_244/train-* - config_name: subset_245 data_files: - split: train path: subset_245/train-* - config_name: subset_246 data_files: - split: train path: subset_246/train-* - config_name: subset_247 data_files: - split: train path: subset_247/train-* - config_name: subset_248 data_files: - split: train path: subset_248/train-* - config_name: subset_249 data_files: - split: train path: subset_249/train-* - config_name: subset_25 data_files: - split: train path: subset_25/train-* - config_name: subset_250 data_files: - split: train path: subset_250/train-* - config_name: subset_251 data_files: - split: train path: subset_251/train-* - config_name: subset_252 data_files: - split: train path: subset_252/train-* - config_name: subset_253 data_files: - split: train path: subset_253/train-* - config_name: subset_254 data_files: - split: train path: subset_254/train-* - config_name: subset_255 data_files: - split: train path: subset_255/train-* - config_name: subset_256 data_files: - split: train path: subset_256/train-* - config_name: subset_257 data_files: - split: train path: subset_257/train-* - config_name: subset_258 data_files: - split: train path: subset_258/train-* - config_name: subset_26 data_files: - split: train path: subset_26/train-* - config_name: subset_27 data_files: - split: train path: subset_27/train-* - config_name: subset_28 data_files: - split: train path: subset_28/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_35 data_files: - split: train path: subset_35/train-* - config_name: subset_36 data_files: - split: train path: subset_36/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_44 data_files: - split: train path: subset_44/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_46 data_files: - split: train path: subset_46/train-* - config_name: subset_47 data_files: - split: train path: subset_47/train-* - config_name: subset_48 data_files: - split: train path: subset_48/train-* - config_name: subset_49 data_files: - split: train path: subset_49/train-* - config_name: subset_5 data_files: - split: train path: subset_5/train-* - config_name: subset_50 data_files: - split: train path: subset_50/train-* - config_name: subset_51 data_files: - split: train path: subset_51/train-* - config_name: subset_52 data_files: - split: train path: subset_52/train-* - config_name: subset_53 data_files: - split: train path: subset_53/train-* - config_name: subset_54 data_files: - split: train path: subset_54/train-* - config_name: subset_55 data_files: - split: train path: subset_55/train-* - config_name: subset_56 data_files: - split: train path: subset_56/train-* - config_name: subset_57 data_files: - split: train path: subset_57/train-* - config_name: subset_58 data_files: - split: train path: subset_58/train-* - config_name: subset_59 data_files: - split: train path: subset_59/train-* - config_name: subset_6 data_files: - split: train path: subset_6/train-* - config_name: subset_60 data_files: - split: train path: subset_60/train-* - config_name: subset_61 data_files: - split: train path: subset_61/train-* - config_name: subset_62 data_files: - split: train path: subset_62/train-* - config_name: subset_63 data_files: - split: train path: subset_63/train-* - config_name: subset_64 data_files: - split: train path: subset_64/train-* - config_name: subset_65 data_files: - split: train path: subset_65/train-* - config_name: subset_66 data_files: - split: train path: subset_66/train-* - config_name: subset_67 data_files: - split: train path: subset_67/train-* - config_name: subset_68 data_files: - split: train path: subset_68/train-* - config_name: subset_69 data_files: - split: train path: subset_69/train-* - config_name: subset_7 data_files: - split: train path: subset_7/train-* - config_name: subset_70 data_files: - split: train path: subset_70/train-* - config_name: subset_71 data_files: - split: train path: subset_71/train-* - config_name: subset_72 data_files: - split: train path: subset_72/train-* - config_name: subset_73 data_files: - split: train path: subset_73/train-* - config_name: subset_74 data_files: - split: train path: subset_74/train-* - config_name: subset_75 data_files: - split: train path: subset_75/train-* - config_name: subset_76 data_files: - split: train path: subset_76/train-* - config_name: subset_77 data_files: - split: train path: subset_77/train-* - config_name: subset_78 data_files: - split: train path: subset_78/train-* - config_name: subset_79 data_files: - split: train path: subset_79/train-* - config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

oscar-corpus/oscar

oscar-corpus

--- pretty_name: OSCAR annotations_creators: - no-annotation language_creators: - found language: - af - als - am - an - ar - arz - as - ast - av - az - azb - ba - bar - bcl - be - bg - bh - bn - bo - bpy - br - bs - bxr - ca - cbk - ce - ceb - ckb - cs - cv - cy - da - de - diq - dsb - dv - el - eml - en - eo - es - et - eu - fa - fi - fr - frr - fy - ga - gd - gl - gn - gom - gu - he - hi - hr - hsb - ht - hu - hy - ia - id - ie - ilo - io - is - it - ja - jbo - jv - ka - kk - km - kn - ko - krc - ku - kv - kw - ky - la - lb - lez - li - lmo - lo - lrc - lt - lv - mai - mg - mhr - min - mk - ml - mn - mr - mrj - ms - mt - mwl - my - myv - mzn - nah - nap - nds - ne - new - nl - nn - 'no' - oc - or - os - pa - pam - pl - pms - pnb - ps - pt - qu - rm - ro - ru - sa - sah - scn - sd - sh - si - sk - sl - so - sq - sr - su - sv - sw - ta - te - tg - th - tk - tl - tr - tt - tyv - ug - uk - ur - uz - vec - vi - vo - wa - war - wuu - xal - xmf - yi - yo - yue - zh license: - cc0-1.0 multilinguality: - multilingual size_categories: - 100K<n<1M - 100M<n<1B - 10K<n<100K - 10M<n<100M - 1K<n<10K - 1M<n<10M - n<1K source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: oscar dataset_info: - config_name: unshuffled_deduplicated_af features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 171320914 num_examples: 130640 download_size: 65989254 dataset_size: 171320914 - config_name: unshuffled_deduplicated_als features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2915912 num_examples: 4518 download_size: 1263294 dataset_size: 2915912 - config_name: unshuffled_deduplicated_arz features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 34893248 num_examples: 79928 download_size: 10027493 dataset_size: 34893248 - config_name: unshuffled_deduplicated_an features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 842246 num_examples: 2025 download_size: 133373 dataset_size: 842246 - config_name: unshuffled_deduplicated_ast features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2150022 num_examples: 5343 download_size: 856177 dataset_size: 2150022 - config_name: unshuffled_deduplicated_ba features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 93623739 num_examples: 27050 download_size: 25983491 dataset_size: 93623739 - config_name: unshuffled_deduplicated_am features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 215618603 num_examples: 43102 download_size: 61347279 dataset_size: 215618603 - config_name: unshuffled_deduplicated_as features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 73989818 num_examples: 9212 download_size: 15513004 dataset_size: 73989818 - config_name: unshuffled_deduplicated_azb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 20001183 num_examples: 9985 download_size: 5191704 dataset_size: 20001183 - config_name: unshuffled_deduplicated_be features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1077152244 num_examples: 307405 download_size: 306700943 dataset_size: 1077152244 - config_name: unshuffled_deduplicated_bo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 144506264 num_examples: 15762 download_size: 22365048 dataset_size: 144506264 - config_name: unshuffled_deduplicated_bxr features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 11325 num_examples: 36 download_size: 3666 dataset_size: 11325 - config_name: unshuffled_deduplicated_ceb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 24439249 num_examples: 26145 download_size: 7124786 dataset_size: 24439249 - config_name: unshuffled_deduplicated_az features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1526935070 num_examples: 626796 download_size: 521744076 dataset_size: 1526935070 - config_name: unshuffled_deduplicated_bcl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 900 num_examples: 1 download_size: 594 dataset_size: 900 - config_name: unshuffled_deduplicated_cy features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 140412555 num_examples: 98225 download_size: 53629697 dataset_size: 140412555 - config_name: unshuffled_deduplicated_dsb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 7589 num_examples: 37 download_size: 3640 dataset_size: 7589 - config_name: unshuffled_deduplicated_bn features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 6233041155 num_examples: 1114481 download_size: 1257218381 dataset_size: 6233041155 - config_name: unshuffled_deduplicated_bs features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 125977 num_examples: 702 download_size: 38669 dataset_size: 125977 - config_name: unshuffled_deduplicated_ce features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 7021674 num_examples: 2984 download_size: 1862792 dataset_size: 7021674 - config_name: unshuffled_deduplicated_cv features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 27359554 num_examples: 10130 download_size: 7461982 dataset_size: 27359554 - config_name: unshuffled_deduplicated_diq features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 161 num_examples: 1 download_size: 331 dataset_size: 161 - config_name: unshuffled_deduplicated_eml features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 24657 num_examples: 80 download_size: 10055 dataset_size: 24657 - config_name: unshuffled_deduplicated_et features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2434152666 num_examples: 1172041 download_size: 966785545 dataset_size: 2434152666 - config_name: unshuffled_deduplicated_bg features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 14420684170 num_examples: 3398679 download_size: 3848659853 dataset_size: 14420684170 - config_name: unshuffled_deduplicated_bpy features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1725535 num_examples: 1770 download_size: 191472 dataset_size: 1725535 - config_name: unshuffled_deduplicated_ca features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 4544123629 num_examples: 2458067 download_size: 1734548117 dataset_size: 4544123629 - config_name: unshuffled_deduplicated_ckb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 237229156 num_examples: 68210 download_size: 60319928 dataset_size: 237229156 - config_name: unshuffled_deduplicated_ar features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 33468271639 num_examples: 9006977 download_size: 9667185012 dataset_size: 33468271639 - config_name: unshuffled_deduplicated_av features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 334755 num_examples: 360 download_size: 75341 dataset_size: 334755 - config_name: unshuffled_deduplicated_bar features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 551 num_examples: 4 download_size: 354 dataset_size: 551 - config_name: unshuffled_deduplicated_bh features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 35216 num_examples: 82 download_size: 6003 dataset_size: 35216 - config_name: unshuffled_deduplicated_br features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 16712284 num_examples: 14724 download_size: 6468062 dataset_size: 16712284 - config_name: unshuffled_deduplicated_cbk features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 535 num_examples: 1 download_size: 247 dataset_size: 535 - config_name: unshuffled_deduplicated_da features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 10204168604 num_examples: 4771098 download_size: 3816376656 dataset_size: 10204168604 - config_name: unshuffled_deduplicated_dv features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 82122241 num_examples: 17024 download_size: 16836170 dataset_size: 82122241 - config_name: unshuffled_deduplicated_eo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 239597935 num_examples: 84752 download_size: 92858714 dataset_size: 239597935 - config_name: unshuffled_deduplicated_fa features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 39986583410 num_examples: 8203495 download_size: 10459318520 dataset_size: 39986583410 - config_name: unshuffled_deduplicated_fy features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 26562554 num_examples: 20661 download_size: 10270434 dataset_size: 26562554 - config_name: unshuffled_deduplicated_gn features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 24545 num_examples: 68 download_size: 9566 dataset_size: 24545 - config_name: unshuffled_deduplicated_cs features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 25590158564 num_examples: 12308039 download_size: 10494256383 dataset_size: 25590158564 - config_name: unshuffled_deduplicated_hi features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 9550345517 num_examples: 1909387 download_size: 2007441283 dataset_size: 9550345517 - config_name: unshuffled_deduplicated_hu features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 19027456462 num_examples: 6582908 download_size: 7368098962 dataset_size: 19027456462 - config_name: unshuffled_deduplicated_ie features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1688 num_examples: 11 download_size: 649 dataset_size: 1688 - config_name: unshuffled_deduplicated_fr features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 147774253219 num_examples: 59448891 download_size: 55462770729 dataset_size: 147774253219 - config_name: unshuffled_deduplicated_gd features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1339050 num_examples: 3883 download_size: 420601 dataset_size: 1339050 - config_name: unshuffled_deduplicated_gu features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 758319353 num_examples: 169834 download_size: 162974870 dataset_size: 758319353 - config_name: unshuffled_deduplicated_hsb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1821734 num_examples: 3084 download_size: 728158 dataset_size: 1821734 - config_name: unshuffled_deduplicated_ia features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 373710 num_examples: 529 download_size: 52722 dataset_size: 373710 - config_name: unshuffled_deduplicated_io features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 139493 num_examples: 617 download_size: 42813 dataset_size: 139493 - config_name: unshuffled_deduplicated_jbo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 700428 num_examples: 617 download_size: 203506 dataset_size: 700428 - config_name: unshuffled_deduplicated_km features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 609886370 num_examples: 108346 download_size: 114480044 dataset_size: 609886370 - config_name: unshuffled_deduplicated_ku features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 62855449 num_examples: 29054 download_size: 23343869 dataset_size: 62855449 - 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config_name: unshuffled_original_hy features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 3939672772 num_examples: 659430 download_size: 897364024 dataset_size: 3939672772 - config_name: unshuffled_original_ilo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 925809 num_examples: 2638 download_size: 267451 dataset_size: 925809 - config_name: unshuffled_original_ja features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 232216718556 num_examples: 62721527 download_size: 79564645083 dataset_size: 232216718556 - config_name: unshuffled_original_kk features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2833778199 num_examples: 524591 download_size: 615067761 dataset_size: 2833778199 - config_name: unshuffled_original_krc features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2688672 num_examples: 1581 download_size: 656496 dataset_size: 2688672 - config_name: unshuffled_original_ky features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 630794622 num_examples: 146993 download_size: 152636608 dataset_size: 630794622 - config_name: unshuffled_original_li features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 31312 num_examples: 137 download_size: 11793 dataset_size: 31312 - config_name: unshuffled_original_lt features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 9445278312 num_examples: 2977757 download_size: 3439789726 dataset_size: 9445278312 - config_name: unshuffled_original_mhr features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 7553453 num_examples: 3212 download_size: 1834912 dataset_size: 7553453 - config_name: unshuffled_original_mn features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2332897881 num_examples: 395605 download_size: 472357548 dataset_size: 2332897881 - config_name: unshuffled_original_mt features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 24470330 num_examples: 26598 download_size: 7533204 dataset_size: 24470330 - config_name: unshuffled_original_mzn features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 720229 num_examples: 1055 download_size: 177817 dataset_size: 720229 - config_name: unshuffled_original_ne features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1866852959 num_examples: 299938 download_size: 355291639 dataset_size: 1866852959 - config_name: unshuffled_original_no features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 8652054976 num_examples: 5546211 download_size: 3106155643 dataset_size: 8652054976 - config_name: unshuffled_original_pa features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 801167879 num_examples: 127467 download_size: 164207256 dataset_size: 801167879 - config_name: unshuffled_original_pnb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 12039418 num_examples: 4599 download_size: 3215579 dataset_size: 12039418 - config_name: unshuffled_original_rm features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 8027 num_examples: 41 download_size: 2691 dataset_size: 8027 - config_name: unshuffled_original_sah features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 43817239 num_examples: 22301 download_size: 9079982 dataset_size: 43817239 - config_name: unshuffled_original_si features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1469374795 num_examples: 203082 download_size: 310935021 dataset_size: 1469374795 - config_name: unshuffled_original_sq features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2440834375 num_examples: 672077 download_size: 861831806 dataset_size: 2440834375 - config_name: unshuffled_original_sw features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 14073775 num_examples: 41986 download_size: 3712739 dataset_size: 14073775 - config_name: unshuffled_original_th features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 38289228753 num_examples: 6064129 download_size: 7377469078 dataset_size: 38289228753 - config_name: unshuffled_original_tt features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 703412782 num_examples: 135923 download_size: 151056507 dataset_size: 703412782 - config_name: unshuffled_original_ur features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2802270961 num_examples: 638596 download_size: 712607161 dataset_size: 2802270961 - config_name: unshuffled_original_vo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2118909 num_examples: 3366 download_size: 307184 dataset_size: 2118909 - config_name: unshuffled_original_xal features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 116043 num_examples: 39 download_size: 32117 dataset_size: 116043 - config_name: unshuffled_original_yue features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 3899 num_examples: 11 download_size: 647 dataset_size: 3899 - config_name: unshuffled_original_en features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2525437912097 num_examples: 455994980 download_size: 903830686146 dataset_size: 2525437912097 - config_name: unshuffled_original_eu features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 894836188 num_examples: 506883 download_size: 248190119 dataset_size: 894836188 - config_name: unshuffled_original_frr features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 4507 num_examples: 7 download_size: 527 dataset_size: 4507 - config_name: unshuffled_original_gl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 656477422 num_examples: 544388 download_size: 235384299 dataset_size: 656477422 - config_name: unshuffled_original_he features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 21113706929 num_examples: 3808397 download_size: 5660026441 dataset_size: 21113706929 - config_name: unshuffled_original_ht features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 4083 num_examples: 13 download_size: 590 dataset_size: 4083 - config_name: unshuffled_original_id features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 32317679452 num_examples: 16236463 download_size: 10596988488 dataset_size: 32317679452 - config_name: unshuffled_original_is features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1524936467 num_examples: 625673 download_size: 533034495 dataset_size: 1524936467 - config_name: unshuffled_original_jv features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 691812 num_examples: 1445 download_size: 219246 dataset_size: 691812 - config_name: unshuffled_original_kn features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1763625096 num_examples: 350363 download_size: 342155433 dataset_size: 1763625096 - config_name: unshuffled_original_kv features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2379758 num_examples: 1549 download_size: 400725 dataset_size: 2379758 - config_name: unshuffled_original_lb features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 30595156 num_examples: 34807 download_size: 10725552 dataset_size: 30595156 - config_name: unshuffled_original_lo features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 182361509 num_examples: 52910 download_size: 33916738 dataset_size: 182361509 - config_name: unshuffled_original_mai features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 325990 num_examples: 123 download_size: 5563 dataset_size: 325990 - config_name: unshuffled_original_mk features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2202480390 num_examples: 437871 download_size: 508239918 dataset_size: 2202480390 - config_name: unshuffled_original_mrj features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1165977 num_examples: 757 download_size: 303447 dataset_size: 1165977 - config_name: unshuffled_original_my features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2021872493 num_examples: 232329 download_size: 369850157 dataset_size: 2021872493 - config_name: unshuffled_original_nap features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 17839 num_examples: 73 download_size: 5023 dataset_size: 17839 - config_name: unshuffled_original_nl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 83230965323 num_examples: 34682142 download_size: 29352811750 dataset_size: 83230965323 - config_name: unshuffled_original_or features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 260151226 num_examples: 59463 download_size: 49834443 dataset_size: 260151226 - config_name: unshuffled_original_pl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 117121370605 num_examples: 35440972 download_size: 42884898947 dataset_size: 117121370605 - config_name: unshuffled_original_pt features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 132635490139 num_examples: 42114520 download_size: 47257949300 dataset_size: 132635490139 - config_name: unshuffled_original_ru features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 1241627166551 num_examples: 161836003 download_size: 319755378587 dataset_size: 1241627166551 - config_name: unshuffled_original_sd features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 364256869 num_examples: 44280 download_size: 90621520 dataset_size: 364256869 - config_name: unshuffled_original_sl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2675665926 num_examples: 1746604 download_size: 956197026 dataset_size: 2675665926 - config_name: unshuffled_original_su features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 225627 num_examples: 805 download_size: 59643 dataset_size: 225627 - config_name: unshuffled_original_te features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2611548765 num_examples: 475703 download_size: 522470115 dataset_size: 2611548765 - config_name: unshuffled_original_tl features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 606295665 num_examples: 458206 download_size: 204895159 dataset_size: 606295665 - config_name: unshuffled_original_ug features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 127419368 num_examples: 22255 download_size: 27923925 dataset_size: 127419368 - config_name: unshuffled_original_vec features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 19182 num_examples: 73 download_size: 7672 dataset_size: 19182 - config_name: unshuffled_original_war features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 2682430 num_examples: 9760 download_size: 644576 dataset_size: 2682430 - config_name: unshuffled_original_yi features: - name: id dtype: int64 - name: text dtype: string splits: - name: train num_bytes: 147601654 num_examples: 59364 download_size: 33337157 dataset_size: 147601654 config_names: - unshuffled_deduplicated_af - unshuffled_deduplicated_als - unshuffled_deduplicated_am - unshuffled_deduplicated_an - unshuffled_deduplicated_ar - unshuffled_deduplicated_arz - unshuffled_deduplicated_as - unshuffled_deduplicated_ast - unshuffled_deduplicated_av - unshuffled_deduplicated_az - unshuffled_deduplicated_azb - unshuffled_deduplicated_ba - unshuffled_deduplicated_bar - unshuffled_deduplicated_bcl - unshuffled_deduplicated_be - unshuffled_deduplicated_bg - unshuffled_deduplicated_bh - unshuffled_deduplicated_bn - unshuffled_deduplicated_bo - unshuffled_deduplicated_bpy - unshuffled_deduplicated_br - unshuffled_deduplicated_bs - unshuffled_deduplicated_bxr - unshuffled_deduplicated_ca - unshuffled_deduplicated_cbk - unshuffled_deduplicated_ce - unshuffled_deduplicated_ceb - unshuffled_deduplicated_ckb - unshuffled_deduplicated_cs - unshuffled_deduplicated_cv - unshuffled_deduplicated_cy - unshuffled_deduplicated_da - unshuffled_deduplicated_de - unshuffled_deduplicated_diq - unshuffled_deduplicated_dsb - unshuffled_deduplicated_dv - unshuffled_deduplicated_el - unshuffled_deduplicated_eml - unshuffled_deduplicated_en - unshuffled_deduplicated_eo - unshuffled_deduplicated_es - unshuffled_deduplicated_et - unshuffled_deduplicated_eu - unshuffled_deduplicated_fa - unshuffled_deduplicated_fi - unshuffled_deduplicated_fr - unshuffled_deduplicated_frr - unshuffled_deduplicated_fy - unshuffled_deduplicated_ga - unshuffled_deduplicated_gd - unshuffled_deduplicated_gl - unshuffled_deduplicated_gn - unshuffled_deduplicated_gom - unshuffled_deduplicated_gu - unshuffled_deduplicated_he - unshuffled_deduplicated_hi - unshuffled_deduplicated_hr - unshuffled_deduplicated_hsb - unshuffled_deduplicated_ht - unshuffled_deduplicated_hu - unshuffled_deduplicated_hy - unshuffled_deduplicated_ia - unshuffled_deduplicated_id - unshuffled_deduplicated_ie - unshuffled_deduplicated_ilo - unshuffled_deduplicated_io - unshuffled_deduplicated_is - unshuffled_deduplicated_it - unshuffled_deduplicated_ja - unshuffled_deduplicated_jbo - unshuffled_deduplicated_jv - unshuffled_deduplicated_ka - unshuffled_deduplicated_kk - unshuffled_deduplicated_km - unshuffled_deduplicated_kn - unshuffled_deduplicated_ko - unshuffled_deduplicated_krc - unshuffled_deduplicated_ku - unshuffled_deduplicated_kv - unshuffled_deduplicated_kw - unshuffled_deduplicated_ky - unshuffled_deduplicated_la - unshuffled_deduplicated_lb - unshuffled_deduplicated_lez - unshuffled_deduplicated_li - unshuffled_deduplicated_lmo - unshuffled_deduplicated_lo - unshuffled_deduplicated_lrc - unshuffled_deduplicated_lt - unshuffled_deduplicated_lv - unshuffled_deduplicated_mai - unshuffled_deduplicated_mg - unshuffled_deduplicated_mhr - unshuffled_deduplicated_min - unshuffled_deduplicated_mk - unshuffled_deduplicated_ml - unshuffled_deduplicated_mn - unshuffled_deduplicated_mr - unshuffled_deduplicated_mrj - unshuffled_deduplicated_ms - unshuffled_deduplicated_mt - unshuffled_deduplicated_mwl - unshuffled_deduplicated_my - unshuffled_deduplicated_myv - unshuffled_deduplicated_mzn - unshuffled_deduplicated_nah - unshuffled_deduplicated_nap - unshuffled_deduplicated_nds - unshuffled_deduplicated_ne - unshuffled_deduplicated_new - unshuffled_deduplicated_nl - unshuffled_deduplicated_nn - unshuffled_deduplicated_no - unshuffled_deduplicated_oc - unshuffled_deduplicated_or - unshuffled_deduplicated_os - unshuffled_deduplicated_pa - unshuffled_deduplicated_pam - unshuffled_deduplicated_pl - unshuffled_deduplicated_pms - unshuffled_deduplicated_pnb - unshuffled_deduplicated_ps - unshuffled_deduplicated_pt - unshuffled_deduplicated_qu - unshuffled_deduplicated_rm - unshuffled_deduplicated_ro - unshuffled_deduplicated_ru - unshuffled_deduplicated_sa - unshuffled_deduplicated_sah - unshuffled_deduplicated_scn - unshuffled_deduplicated_sd - unshuffled_deduplicated_sh - unshuffled_deduplicated_si - unshuffled_deduplicated_sk - unshuffled_deduplicated_sl - unshuffled_deduplicated_so - unshuffled_deduplicated_sq - unshuffled_deduplicated_sr - unshuffled_deduplicated_su - unshuffled_deduplicated_sv - unshuffled_deduplicated_sw - unshuffled_deduplicated_ta - unshuffled_deduplicated_te - unshuffled_deduplicated_tg - unshuffled_deduplicated_th - unshuffled_deduplicated_tk - unshuffled_deduplicated_tl - unshuffled_deduplicated_tr - unshuffled_deduplicated_tt - unshuffled_deduplicated_tyv - unshuffled_deduplicated_ug - unshuffled_deduplicated_uk - unshuffled_deduplicated_ur - unshuffled_deduplicated_uz - unshuffled_deduplicated_vec - unshuffled_deduplicated_vi - unshuffled_deduplicated_vo - unshuffled_deduplicated_wa - unshuffled_deduplicated_war - unshuffled_deduplicated_wuu - unshuffled_deduplicated_xal - unshuffled_deduplicated_xmf - unshuffled_deduplicated_yi - unshuffled_deduplicated_yo - unshuffled_deduplicated_yue - unshuffled_deduplicated_zh - unshuffled_original_af - unshuffled_original_als - unshuffled_original_am - unshuffled_original_an - unshuffled_original_ar - unshuffled_original_arz - unshuffled_original_as - unshuffled_original_ast - unshuffled_original_av - unshuffled_original_az - unshuffled_original_azb - unshuffled_original_ba - unshuffled_original_bar - unshuffled_original_bcl - unshuffled_original_be - unshuffled_original_bg - unshuffled_original_bh - unshuffled_original_bn - unshuffled_original_bo - unshuffled_original_bpy - unshuffled_original_br - unshuffled_original_bs - unshuffled_original_bxr - unshuffled_original_ca - unshuffled_original_cbk - unshuffled_original_ce - unshuffled_original_ceb - unshuffled_original_ckb - unshuffled_original_cs - unshuffled_original_cv - unshuffled_original_cy - unshuffled_original_da - unshuffled_original_de - unshuffled_original_diq - unshuffled_original_dsb - unshuffled_original_dv - unshuffled_original_el - unshuffled_original_eml - unshuffled_original_en - unshuffled_original_eo - unshuffled_original_es - unshuffled_original_et - unshuffled_original_eu - unshuffled_original_fa - unshuffled_original_fi - unshuffled_original_fr - unshuffled_original_frr - unshuffled_original_fy - unshuffled_original_ga - unshuffled_original_gd - unshuffled_original_gl - unshuffled_original_gn - unshuffled_original_gom - unshuffled_original_gu - unshuffled_original_he - unshuffled_original_hi - unshuffled_original_hr - unshuffled_original_hsb - unshuffled_original_ht - unshuffled_original_hu - unshuffled_original_hy - unshuffled_original_ia - unshuffled_original_id - unshuffled_original_ie - unshuffled_original_ilo - unshuffled_original_io - unshuffled_original_is - unshuffled_original_it - unshuffled_original_ja - unshuffled_original_jbo - unshuffled_original_jv - unshuffled_original_ka - unshuffled_original_kk - unshuffled_original_km - unshuffled_original_kn - unshuffled_original_ko - unshuffled_original_krc - unshuffled_original_ku - unshuffled_original_kv - unshuffled_original_kw - unshuffled_original_ky - unshuffled_original_la - unshuffled_original_lb - unshuffled_original_lez - unshuffled_original_li - unshuffled_original_lmo - unshuffled_original_lo - unshuffled_original_lrc - unshuffled_original_lt - unshuffled_original_lv - unshuffled_original_mai - unshuffled_original_mg - unshuffled_original_mhr - unshuffled_original_min - unshuffled_original_mk - unshuffled_original_ml - unshuffled_original_mn - unshuffled_original_mr - unshuffled_original_mrj - unshuffled_original_ms - unshuffled_original_mt - unshuffled_original_mwl - unshuffled_original_my - unshuffled_original_myv - unshuffled_original_mzn - unshuffled_original_nah - unshuffled_original_nap - unshuffled_original_nds - unshuffled_original_ne - unshuffled_original_new - unshuffled_original_nl - unshuffled_original_nn - unshuffled_original_no - unshuffled_original_oc - unshuffled_original_or - unshuffled_original_os - unshuffled_original_pa - unshuffled_original_pam - unshuffled_original_pl - unshuffled_original_pms - unshuffled_original_pnb - unshuffled_original_ps - unshuffled_original_pt - unshuffled_original_qu - unshuffled_original_rm - unshuffled_original_ro - unshuffled_original_ru - unshuffled_original_sa - unshuffled_original_sah - unshuffled_original_scn - unshuffled_original_sd - unshuffled_original_sh - unshuffled_original_si - unshuffled_original_sk - unshuffled_original_sl - unshuffled_original_so - unshuffled_original_sq - unshuffled_original_sr - unshuffled_original_su - unshuffled_original_sv - unshuffled_original_sw - unshuffled_original_ta - unshuffled_original_te - unshuffled_original_tg - unshuffled_original_th - unshuffled_original_tk - unshuffled_original_tl - unshuffled_original_tr - unshuffled_original_tt - unshuffled_original_tyv - unshuffled_original_ug - unshuffled_original_uk - unshuffled_original_ur - unshuffled_original_uz - unshuffled_original_vec - unshuffled_original_vi - unshuffled_original_vo - unshuffled_original_wa - unshuffled_original_war - unshuffled_original_wuu - unshuffled_original_xal - unshuffled_original_xmf - unshuffled_original_yi - unshuffled_original_yo - unshuffled_original_yue - unshuffled_original_zh --- # Dataset Card for "oscar" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [https://oscar-corpus.com](https://oscar-corpus.com) - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Dataset Summary OSCAR or **O**pen **S**uper-large **C**rawled [**A**LMAnaCH](https://team.inria.fr/almanach/) co**R**pus is a huge multilingual corpus obtained by language classification and filtering of the [Common Crawl](https://commoncrawl.org/) corpus using the [goclassy](https://github.com/pjox/goclassy) architecture. Data is distributed by language in both original and deduplicated form. The version here is the original OSCAR 2019 release: https://oscar-project.org/post/oscar-2019/ For more recent versions, visit the [oscar-corpus](https://huggingface.co/oscar-corpus) organization on the Hub: - OSCAR 22.01 (released in January 2022): [oscar-corpus/OSCAR-2201](https://huggingface.co/datasets/oscar-corpus/OSCAR-2201) - OSCAR 21.09 (released in September 2021): [oscar-corpus/OSCAR-2109](https://huggingface.co/datasets/oscar-corpus/OSCAR-2109) ### Supported Tasks and Leaderboards OSCAR is mainly inteded to pretrain language models and word represantations. ### Languages All the data is distributed by language, both the original and the deduplicated versions of the data are available. 166 different languages are available. The table in subsection [Data Splits Sample Size](#data-splits-sample-size) provides the language code for each subcorpus as well as the number of words (space separated tokens), lines and sizes for both the original and the deduplicated versions of OSCAR. ## Dataset Structure We show detailed information for all the configurations of the dataset. ### Data Instances <details> <summary>Click to expand the Data/size information for each language (deduplicated)</summary> #### unshuffled_deduplicated_af - **Size of downloaded dataset files:** 65.99 MB - **Size of the generated dataset:** 172.30 MB - **Total amount of disk used:** 238.29 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "aanlyn markte as gevolg van ons voortgesette 'n begrip opsie handel sakeplan pdf terwyl ons steeds die gereelde ons binêre opsies handel" } ``` #### unshuffled_deduplicated_als - **Size of downloaded dataset files:** 1.26 MB - **Size of the generated dataset:** 2.96 MB - **Total amount of disk used:** 4.22 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"De Nazionalpark hät e Flächi vo 170,3 km² und isch dodemit s grösti Naturschutzgebiet vo de Schwiz. Er ligt uf em Gebiet vo de ..." } ``` #### unshuffled_deduplicated_am - **Size of downloaded dataset files:** 61.35 MB - **Size of the generated dataset:** 216.15 MB - **Total amount of disk used:** 277.50 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"አየር መንገዱ ከአዲስ አበባ ወደ ሮም ጣሊያን በማምራት ላይ በነበረበት ጊዜ ረዳት አብራሪው የጉዞውን አቅጣጫ በመቀየር ጄኔቭ አውሮፓላን ማረፊያ በማሳረፍ እጁን ለፖሊስ ሰጥቷል።\\nየኢትዮጵያ መንግስት የ..." } ``` #### unshuffled_deduplicated_an - **Size of downloaded dataset files:** 0.14 MB - **Size of the generated dataset:** 0.85 MB - **Total amount of disk used:** 0.99 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"واااااااأسفاه الأمم تفتخر ب 0 أمي ووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووو..." } ``` #### unshuffled_deduplicated_ar - **Size of downloaded dataset files:** 9.67 GB - **Size of the generated dataset:** 33.57 GB - **Total amount of disk used:** 43.23 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"مرحبا بك عزيز الزائر نتمنى لك أوقاتاً سعيدة معنا وأن نزداد شرفا بخدمتك ولا تنسى التسجيل معنا لتستفيد بكل جديد\\nأهلا وسهلا بك زا..." } ``` #### unshuffled_deduplicated_arz - **Size of downloaded dataset files:** 10.02 MB - **Size of the generated dataset:** 35.91 MB - **Total amount of disk used:** 45.94 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"بنى عجل : قبيلة من عجل بن لجيم بن صعب بن على بن بكر بن وائل انتقل اغلبهم الى البصرة فى العراق و اصفهان و خراسان فى ايران و اذرب..." } ``` #### unshuffled_deduplicated_as - **Size of downloaded dataset files:** 15.51 MB - **Size of the generated dataset:** 74.07 MB - **Total amount of disk used:** 89.58 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"আমি, এই সংগঠনৰ সদস্য সকলে একেলগ হৈ অসমকে ধৰি ভাৰতৰ উত্তৰ পূৰ্বাঞ্চলৰ অমূল্য কলা-সাংস্কৃতিক সম্পদৰাজি বৃহত্তৰ অষ্ট্ৰেলিয়াৰ সন্মু..." } ``` #### unshuffled_deduplicated_ast - **Size of downloaded dataset files:** 0.86 MB - **Size of the generated dataset:** 2.17 MB - **Total amount of disk used:** 3.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"The Killers llanzaron el so álbum debú, Hot Fuss, en xunu de 2004 nel Reinu Xuníu, al traviés de la discográfica Lizard King, y..." } ``` #### unshuffled_deduplicated_av - **Size of downloaded dataset files:** 0.07 MB - **Size of the generated dataset:** 0.34 MB - **Total amount of disk used:** 0.41 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Жинда малъараб ва божизе бегьулеб рагІудаса кьуризе бегьуларо гьев. Гьес насихІат гьабизе кколелъул бацІцІадаб диналъул рахъалъ..." } ``` #### unshuffled_deduplicated_az - **Size of downloaded dataset files:** 521.74 MB - **Size of the generated dataset:** 1.53 GB - **Total amount of disk used:** 2.05 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"AZTV-Artıq 7 ildir ki, Abşeron rayonu dotasiya almadan bütün xərclərini yerli daxilolmalar hesabına maliyyələşdirir.\\nDünən, 10..." } ``` #### unshuffled_deduplicated_azb - **Size of downloaded dataset files:** 5.19 MB - **Size of the generated dataset:** 20.08 MB - **Total amount of disk used:** 25.27 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"لعلی ١٣-جو عصرده یاشاییب یاراتمیش گؤرکملی آذربایجان شاعرلریندندیر. ١٢٢٤-جی ایلده تبریزده آنادان اولموشدور، گنج یاشلاریندا تیجار..." } ``` #### unshuffled_deduplicated_ba - **Size of downloaded dataset files:** 25.98 MB - **Size of the generated dataset:** 93.84 MB - **Total amount of disk used:** 119.82 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Күҙәтеү ҡуласаһы моделен хәҙер Мифтахетдин Аҡмулла исемендәге Башҡорт дәүләт педагогия университетында ла эшләргә мөмкин\\t\\nКүҙ..." } ``` #### unshuffled_deduplicated_bar - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": " vo" } ``` #### unshuffled_deduplicated_bcl - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"& ÿ ó / í 0 - ø û ù ö ú ð ï ú \\u0014 ù þ ô ö í ÷ ò \\u0014 ÷ í ù û ö í \\u0001 û ñ ç þ \\u0001 ð \\u0007 þ ò ñ ñ ò ô \\u0017 û ö ô ÷..." } ``` #### unshuffled_deduplicated_be - **Size of downloaded dataset files:** 306.70 MB - **Size of the generated dataset:** 1.08 GB - **Total amount of disk used:** 1.39 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Брэсцкія ўлады не дазволілі прафсаюзу РЭП правесці пікетаванне ў парку Воінаў-інтэрнацыяналістаў 30 мая 2018 года.\\nСітуацыю пр..." } ``` #### unshuffled_deduplicated_bg - **Size of downloaded dataset files:** 3.85 GB - **Size of the generated dataset:** 14.45 GB - **Total amount of disk used:** 18.30 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ЖАЛБОПОДАТЕЛЯТ директор на Дирекция „ Обжалване и данъчно-осигурителна практика“- Бургас, редовно призован, се представлява от ..." } ``` #### unshuffled_deduplicated_bh - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.04 MB - **Total amount of disk used:** 0.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"सुकमा जिला भारत के छत्तीसगढ़ राज्य में एगो जिला बाटे। एकर मुख्यालय सुकमा शहर बाटे। एकर कुल रकबा 5636 वर्ग कि॰मी॰ बाटे।\"..." } ``` #### unshuffled_deduplicated_bn - **Size of downloaded dataset files:** 1.26 GB - **Size of the generated dataset:** 6.24 GB - **Total amount of disk used:** 7.50 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ভড়ং সর্বস্ব বাংলা আর্ট অ্যান্ড কালচারের হিসাব গুলিয়ে দেওয়ার ম্যাজিকের নাম ব্রাত্য রাইসু November 23, 2017\\nTagged with ডায়োজিনি..." } ``` #### unshuffled_deduplicated_bo - **Size of downloaded dataset files:** 22.37 MB - **Size of the generated dataset:** 144.65 MB - **Total amount of disk used:** 167.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"བོད་མི་འདི་དག་ནི་རང་རྒྱུད་སྒོ་རུ་ཕུད་དེ་གཞན་རྒྱུད་པང་དུ་ཉར་ནས་གསོ་སྐྱོང་བྱེད་དགོས་ཟེར་བ་དང་གཅིག་མཚུངས་རེད།\\nཚན་རིག་ནི་དང་ཐོག་རང..." } ``` #### unshuffled_deduplicated_bpy - **Size of downloaded dataset files:** 0.19 MB - **Size of the generated dataset:** 1.78 MB - **Total amount of disk used:** 1.97 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"পৌরসভা এহার আয়তন (লয়াহান) ২,৭৩০,.৬৩ বর্গ কিলোমিটার। পৌরসভা এহার মাপাহানর অক্ষাংশ বারো দ্রাঘিমাংশ ইলতাই 18.63° S 48.18° W ।[১]..." } ``` #### unshuffled_deduplicated_br - **Size of downloaded dataset files:** 6.47 MB - **Size of the generated dataset:** 17.00 MB - **Total amount of disk used:** 23.47 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ar mank Magalhães(Daveoù a vank) a zo ur spesad evned, Spheniscus magellanicus an anv skiantel anezhañ.\\nGallout a reer implijo..." } ``` #### unshuffled_deduplicated_bs - **Size of downloaded dataset files:** 0.04 MB - **Size of the generated dataset:** 0.15 MB - **Total amount of disk used:** 0.18 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ž šř é ú šř šř ě šř ž é č ě ž ů ě ď éé ýš ě ě Ž č š ý ě ď é ýš ě ď ě éé ýš ě č ž ě š ý ď ě ýš é ú č ž č š ý ď ý ž é éě ď é č ýš..." } ``` #### unshuffled_deduplicated_bxr - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"2002 оной хабар буряад хэлэ бэшэгэй һалбари Үндэһэтэнэй хүмүүнлиг ухаанай дээдэ һургуули болгогдожо өөршэлэгдөө.\\nХарин мүнөө б..." } ``` #### unshuffled_deduplicated_ca - **Size of downloaded dataset files:** 1.73 GB - **Size of the generated dataset:** 4.57 GB - **Total amount of disk used:** 6.30 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Daniel Vendrell, conegut com Vandrell, ha sigut un dels il•lustradors contemporanis més influents, representant a la nova onada..." } ``` #### unshuffled_deduplicated_cbk - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano..." } ``` #### unshuffled_deduplicated_ce - **Size of downloaded dataset files:** 1.87 MB - **Size of the generated dataset:** 7.04 MB - **Total amount of disk used:** 8.90 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Шаьш анархисташ ду бохучу жигархойн дIахьедарехь дуьйцу, оьрсийн ницкъаллийн структурийн а, федералан каналан а Iалашонаш \\\"мар..." } ``` #### unshuffled_deduplicated_ceb - **Size of downloaded dataset files:** 7.12 MB - **Size of the generated dataset:** 24.83 MB - **Total amount of disk used:** 31.95 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Si Isko walay pupamilok nga nagtan-aw sa unahan, natugaw. “Naunsa ka gud diha Isko nga layo man kaayo ang imong panan-aw?” ni I..." } ``` #### unshuffled_deduplicated_ckb - **Size of downloaded dataset files:** 60.32 MB - **Size of the generated dataset:** 237.72 MB - **Total amount of disk used:** 298.05 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"رسی رۆژ - ساڵێک دوای بومەلەرزەی کرماشان میوانی بەرنامە : کاک سیاوەش حەیاتی چالاکی مەدەنی -قەسری شیرین\\nپارچە موزیک 30 / 10 / 20..." } ``` #### unshuffled_deduplicated_cs - **Size of downloaded dataset files:** 10.49 GB - **Size of the generated dataset:** 25.71 GB - **Total amount of disk used:** 36.20 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Akce anarchistů proti připravovanému novému služební řádu a nízkým mzdám 1903 – Historie českého anarchismu (1880 – 1939)\\nRost..." } ``` #### unshuffled_deduplicated_cv - **Size of downloaded dataset files:** 7.47 MB - **Size of the generated dataset:** 27.49 MB - **Total amount of disk used:** 34.95 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Шыранӑ чухне ӑнсӑртран латин кирилл саспаллисем вырӑнне латин саспаллисене ҫырсан, сайт эсир ҫырнине юсама тӑрӑшӗ.\\nКу сайтра ч..." } ``` #### unshuffled_deduplicated_cy - **Size of downloaded dataset files:** 53.63 MB - **Size of the generated dataset:** 141.22 MB - **Total amount of disk used:** 194.86 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Mae capeli Cymreig yr Andes ym Mhatagonia wedi cyhoeddi na fydd gwasanaethau yno weddill y mis, oherwydd yr eira trwm sydd wedi..." } ``` #### unshuffled_deduplicated_da - **Size of downloaded dataset files:** 3.82 GB - **Size of the generated dataset:** 10.24 GB - **Total amount of disk used:** 14.06 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Den 2.-5. februar 2016 løb det tredje kursus i uddannelsen af 4kommunesamarbejdets Local Impact Coaches, af stablen i Gentofte ..." } ``` #### unshuffled_deduplicated_de - **Size of downloaded dataset files:** 60.80 GB - **Size of the generated dataset:** 156.30 GB - **Total amount of disk used:** 217.10 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Auf dieser Seite gibt es mind. ein YouTube Video. Cookies für diese Website wurden abgelehnt. Dadurch können keine YouTube Vide..." } ``` #### unshuffled_deduplicated_diq - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Zıwanê Slawki, zıwano merdumanê Slawano. Zıwanê Slawki yew lızgeyê Zıwananê Hind u Ewropao. Keyeyê Zıwananê Slawki beno hirê letey:" } ``` #### unshuffled_deduplicated_dsb - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Pśiklaskaju južo pśed pśedstajenim... 1500 źiśi njamóžo wěcej docakaś, měsćańska hala w Chóśebuzu - wupśedana." } ``` #### unshuffled_deduplicated_dv - **Size of downloaded dataset files:** 16.84 MB - **Size of the generated dataset:** 82.19 MB - **Total amount of disk used:** 99.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ބ. އަތޮޅުގައި ހުޅުވަން ތައްޔާރުވަމުން އަންނަ ވައްކަރު ރިސޯޓުގައި ވަޒީފާ އަދާކުރަން ޝައުގުވެރިވާ ފަރާތްތަކަށް ކުރިމަތިލުމުގެ ފުރ..." } ``` #### unshuffled_deduplicated_el - **Size of downloaded dataset files:** 7.91 GB - **Size of the generated dataset:** 28.74 GB - **Total amount of disk used:** 36.65 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Νεκρός εντοπίστηκε μέσα στο σπίτι του στην οδό Ηρώδου Αττικού στον αριθμό 7 ο επικεφαλής του προξενικού τμήματος της Ρωσικής πρ..." } ``` #### unshuffled_deduplicated_eml - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"A séguit dal prucès ad rubutiśasiòṅ di abitànt dal pòpul ad Mikenes, Angoras 'l è finî dènt'r a 'n robot cun la tèsta dna rana ..." } ``` #### unshuffled_deduplicated_en - **Size of downloaded dataset files:** 496.50 GB - **Size of the generated dataset:** 1299.75 GB - **Total amount of disk used:** 1796.24 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Mtendere Village was inspired by the vision of Chief Napoleon Dzombe, which he shared with John Blanchard during his first visi..." } ``` #### unshuffled_deduplicated_eo - **Size of downloaded dataset files:** 92.86 MB - **Size of the generated dataset:** 240.12 MB - **Total amount of disk used:** 332.99 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ĉu ... preĝi | mediti | ricevi instigojn || kanti | muziki || informiĝi | legi | studi || prepari Diservon\\nTemas pri kolekto d..." } ``` #### unshuffled_deduplicated_es - **Size of downloaded dataset files:** 60.46 GB - **Size of the generated dataset:** 160.86 GB - **Total amount of disk used:** 221.32 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Como se librará de la celulitis en el gimnasio La piel superflua en las manos después del adelgazamiento, Los bailes fáciles pa..." } ``` #### unshuffled_deduplicated_et - **Size of downloaded dataset files:** 966.79 MB - **Size of the generated dataset:** 2.45 GB - **Total amount of disk used:** 3.41 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"MTÜ AB Video järgib oma tegevuses kodanikuühenduste eetilise tegevuse üldtunnustatud põhimõtteid, mis on lühidalt kokkuvõetud 7..." } ``` #### unshuffled_deduplicated_eu - **Size of downloaded dataset files:** 134.68 MB - **Size of the generated dataset:** 363.93 MB - **Total amount of disk used:** 498.61 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Gure jarduerek eraikuntzarekin, elkarbizitzarekin, hirigintzarekin eta ekologiarekin dute harremana, baita ideia eta konponbideak irudikatu eta garatzearekin ere, eraikuntza sektorea hobetuz, pertsonen erosotasuna eta bizi-kalitatea hobetzeko." } ``` #### unshuffled_deduplicated_fa - **Size of downloaded dataset files:** 10.46 GB - **Size of the generated dataset:** 40.06 GB - **Total amount of disk used:** 50.52 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"قـــــــــــــــــرار بود با هم کنـــــــــــــار بیایم نه اینکه از کنــــــــــــار هم رد بشیم...!!!\\nاگر روزی دلت لبریز غم بو..." } ``` #### unshuffled_deduplicated_fi - **Size of downloaded dataset files:** 5.38 GB - **Size of the generated dataset:** 13.99 GB - **Total amount of disk used:** 19.37 GB An example of 'train' looks as follows. ``` { "id": 1, "text": "Kiitos Deelle kaikesta - 1,5 viikkoa kulunut, kun Dee ei ole enää ollut omani. Reilu viikko sitten sunnuntaina vein Deen uuteen kotiinsa. Itselläni on ollut niin ristiriitaiset t..." } ``` #### unshuffled_deduplicated_fr - **Size of downloaded dataset files:** 55.46 GB - **Size of the generated dataset:** 148.28 GB - **Total amount of disk used:** 203.75 GB An example of 'train' looks as follows. ``` { "id": 0, "text": "Média de débat d'idées, de culture et de littérature. Récits, décryptages, analyses, portraits et critiques autour de la vie des idées. Magazine engagé, ouvert aux autres et au monde.. Bring up to date in french" } ``` #### unshuffled_deduplicated_frr - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Hiragana’ Practice’Sheet’1’(A -O)’ ’ Name:’________ __________________________’Section:’_______________ _’ ’ ’ ’ ’ ’ ’ ’ ’ ’ ’ ..." } ``` #### unshuffled_deduplicated_fy - **Size of downloaded dataset files:** 10.27 MB - **Size of the generated dataset:** 26.73 MB - **Total amount of disk used:** 37.00 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Nim in sêfte ride op Holmsjön, yn ien fan 'e lytse marren yn de omkriten, of nim se op avontueren lykas nonresidential. lâns Indalsälven wetter. Holm Sportklubb hawwe kano 's te huur, yn gearwurking mei de Baltyske Power konferinsje." } ``` #### unshuffled_deduplicated_ga - **Size of downloaded dataset files:** 22.22 MB - **Size of the generated dataset:** 63.86 MB - **Total amount of disk used:** 86.08 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Is fóram é seo chun plé a dhéanamh ar an leabhar atá roghnaithe do mhí na Samhna 2013 amháin. Ní féidir ach le baill chláraithe..." } ``` #### unshuffled_deduplicated_gd - **Size of downloaded dataset files:** 0.42 MB - **Size of the generated dataset:** 1.36 MB - **Total amount of disk used:** 1.78 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Zhou Yujun, a 'phàrtaidh Rùnaire Comataidh Sgìre Yanfeng ann Hengyang bhaile agus a Sgìre pàrtaidh agus an riaghaltas a' bhuidheann-riochdachaidh a 'tighinn a chèilidh air ar companaidh air Apr. 14, 2017." } ``` #### unshuffled_deduplicated_gl - **Size of downloaded dataset files:** 155.85 MB - **Size of the generated dataset:** 408.34 MB - **Total amount of disk used:** 564.19 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"O persoal de Inditex da provincia de Pontevedra segue a reclamar iguais condicións laborais no conxunto do país - CIG: Confeder..." } ``` #### unshuffled_deduplicated_gn - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"º ѐÆÚÓ À Ã Ð É Æ ¾ Ä ΠÀ ¼ Æ É ÄÛ = Ü Ý\\\"Þ ß†à á â ã ä å æçè ã é ê â å àë ì æê íî é á ë ï í çì àð í Ü à ñ ê é ò ä ì\"..." } ``` #### unshuffled_deduplicated_gom - **Size of downloaded dataset files:** 0.38 MB - **Size of the generated dataset:** 1.87 MB - **Total amount of disk used:** 2.24 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"दुष्ट शीळ हें कौरवांचें । रामें सविस्तर देखूनि साचें । बोलिले वचनें जें दुर्वाचे । करी तयांचें अनुस्मरण ॥२२०॥\"..." } ``` #### unshuffled_deduplicated_gu - **Size of downloaded dataset files:** 162.97 MB - **Size of the generated dataset:** 759.34 MB - **Total amount of disk used:** 922.32 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"અધિક માસ ચાલે છે. સમગ્ર ભારતમાં અને તેમાંય ખાસ કરીને પવિત્ર કે ધાર્મિક કહેવાય છે તેવા સ્થાનક પર કથાનો દોર ચાલે છે. ઉનાળાની કાળઝ..." } ``` #### unshuffled_deduplicated_he - **Size of downloaded dataset files:** 3.04 GB - **Size of the generated dataset:** 10.47 GB - **Total amount of disk used:** 13.51 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"זקוקים לרשתות נגד יתושים? מחפשים רשת מתאימה לחלון צר וקטן? רשתות נגד יתושים אקורדיון של חברת קליר-מש הן הפתרון.\\nרשתות לחלונות ..." } ``` #### unshuffled_deduplicated_hi - **Size of downloaded dataset files:** 2.01 GB - **Size of the generated dataset:** 9.57 GB - **Total amount of disk used:** 11.58 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"'आइटम गर्ल' बनकर हिट हुई थीं राखी सावंत, आज करीना-कटरीना तक फॉलो कर रही हैं ट्रेंड नक्‍सलियों का दम निकालेगा बाइक ग्रेनेड लॉन्च..." } ``` #### unshuffled_deduplicated_hr - **Size of downloaded dataset files:** 46.74 MB - **Size of the generated dataset:** 121.50 MB - **Total amount of disk used:** 168.23 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"U raspravi je sudjelovao i HSS-ov saborski zastupnik rekavši kako poljoprivrednici ne osjete mjere o kojima ministar govori jer..." } ``` #### unshuffled_deduplicated_hsb - **Size of downloaded dataset files:** 0.72 MB - **Size of the generated dataset:** 1.89 MB - **Total amount of disk used:** 2.61 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Budyšin (SN/BŠe). Elektronikarjo mějachu lětsa cyle hinaši zazběh do swojeho wukubłanja. Wokrjesne rjemjeslnistwo bě mjenujcy w..." } ``` #### unshuffled_deduplicated_ht - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan..." } ``` #### unshuffled_deduplicated_hu - **Size of downloaded dataset files:** 7.37 GB - **Size of the generated dataset:** 19.09 GB - **Total amount of disk used:** 26.46 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"monster - Amatőr, házi szex videók és kezdő csjaok pornó filmjei. - Free amateur, home made sex videos and online porn movies. ..." } ``` #### unshuffled_deduplicated_hy - **Size of downloaded dataset files:** 393.62 MB - **Size of the generated dataset:** 1.56 GB - **Total amount of disk used:** 1.96 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Արցախի Հանրապետության հռչակման 26-րդ տարեդարձի կապակցությամբ Շուշիի Արվեստի կենտրոնում կազմակերպվել է մոսկվաբնակ նկարիչներ՝ հայ..." } ``` #### unshuffled_deduplicated_ia - **Size of downloaded dataset files:** 0.05 MB - **Size of the generated dataset:** 0.38 MB - **Total amount of disk used:** 0.43 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha h..." } ``` #### unshuffled_deduplicated_id - **Size of downloaded dataset files:** 6.00 GB - **Size of the generated dataset:** 17.05 GB - **Total amount of disk used:** 23.05 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Perihal dari itu, kalau kunci hal yang demikian hilang, pemilik wajib melapor ke bengkel sah untuk dibuatkan kunci baru dengan ..." } ``` #### unshuffled_deduplicated_ie - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Plastic Yo Yo Metal Yo Yos Wooden Yo Yo Keychain Yo Yo Translucent Yo Yo Light Up Yo Yo Globe Yo Yo Stress Reliever Yo Yo Jellyfish Yo Yo Sports Ball Yo Yo Sound Yo Yo Miniature Yo Yo Promotional Yo Yo Novelty Yo Yo Video Game Yo Yo ECO Recycled Yo Yo" } ``` #### unshuffled_deduplicated_ilo - **Size of downloaded dataset files:** 0.23 MB - **Size of the generated dataset:** 0.68 MB - **Total amount of disk used:** 0.91 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Segun ken ni Ping-ay, ti yellow corn ti maysa kadagiti nadakamat a liberalized agricultural commodity iti daytoy a free trade k..." } ``` #### unshuffled_deduplicated_io - **Size of downloaded dataset files:** 0.04 MB - **Size of the generated dataset:** 0.14 MB - **Total amount of disk used:** 0.19 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Chekia esas parlamentala republiko. La chefo di stato esas la prezidanto. Til 2013 lu elektesis dal parlamento. Pos ta yaro, ol..." } ``` #### unshuffled_deduplicated_is - **Size of downloaded dataset files:** 332.87 MB - **Size of the generated dataset:** 894.28 MB - **Total amount of disk used:** 1.23 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Eyjar.net - upplýsinga- og fréttamiðill um Vestmannaeyjar - Fréttir - Nái núverandi stefna stjórnvalda fram að ganga mun það va..." } ``` #### unshuffled_deduplicated_it - **Size of downloaded dataset files:** 27.93 GB - **Size of the generated dataset:** 74.09 GB - **Total amount of disk used:** 102.03 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Jaundice - causes, treatment & pathology massaggio a osteochondrosis dellindizio di una controindicazione\\nTrattamento su un co..." } ``` #### unshuffled_deduplicated_ja - **Size of downloaded dataset files:** 40.80 GB - **Size of the generated dataset:** 113.63 GB - **Total amount of disk used:** 154.44 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"神社などへ一緒に同行して、様々な角度のショットで家族写真やお子様の写真を撮影致します！お好みに合わせて様々な写真を取ることができますので、その場でカメラマンへのリクエストも可能です！お子様の晴れ姿を、緊張していない自然な笑顔で残しませんか？\\n※七五三の..." } ``` #### unshuffled_deduplicated_jbo - **Size of downloaded dataset files:** 0.20 MB - **Size of the generated dataset:** 0.70 MB - **Total amount of disk used:** 0.91 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "ni'o 23 la cimast. cu 23moi djedi fi'o masti la cimast. noi ke'a cu cimoi masti .i 22 la cimast. cu purlamdei .ije 24 la cimast. cu bavlamdei" } ``` #### unshuffled_deduplicated_jv - **Size of downloaded dataset files:** 0.21 MB - **Size of the generated dataset:** 0.62 MB - **Total amount of disk used:** 0.82 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"José Mourinho (diwaca: [ʒuˈzɛ moˈɾiɲu]; lair ing Setubal, Portugal, 26 Januari 1963; umur 55 taun) iku salah siji pelatih bal k..." } ``` #### unshuffled_deduplicated_ka - **Size of downloaded dataset files:** 377.23 MB - **Size of the generated dataset:** 1.99 GB - **Total amount of disk used:** 2.36 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"წამიყვანე შენთან ერთად (ქართულად) / Возьми меня с собой (картулад) / (რუსული სერიალები ქართულად) (რუსების პორნო ონლაინში) (ruse..." } ``` #### unshuffled_deduplicated_kk - **Size of downloaded dataset files:** 389.12 MB - **Size of the generated dataset:** 1.59 GB - **Total amount of disk used:** 1.97 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Түлкібас ауданында «Латын негізді әліпби мен емле ережесі туралы насихат» жобасының тобы семинар өткізді\\nЕлорданың «Қазақстан»..." } ``` #### unshuffled_deduplicated_km - **Size of downloaded dataset files:** 114.48 MB - **Size of the generated dataset:** 610.61 MB - **Total amount of disk used:** 725.09 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ខ្សឹបដាក់ត្រចៀក៖ លោក សួស សុផានិត នាយផ្នែករដ្ឋបាលព្រៃឈើ ស្រុកភ្នំក្រវាញ់ ដែលទើបឡើងកាន់តំណែងថ្មី បើកដៃឲ្យឈ្នួញ ប្រព្រឹត្តបទល្មើស ..." } ``` #### unshuffled_deduplicated_kn - **Size of downloaded dataset files:** 215.52 MB - **Size of the generated dataset:** 1.08 GB - **Total amount of disk used:** 1.30 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ರಾಷ್ಟ್ರಪತಿ ಪ್ರಣಬ್ ಮುಖರ್ಜಿಯಿಂದ ಪದ್ಮ ಪ್ರಶಸ್ತಿ ಪ್ರದಾನ | President Pranab Mukherjee Confers Padma Awards | Photo Gallery on Kannada..." } ``` #### unshuffled_deduplicated_ko - **Size of downloaded dataset files:** 4.46 GB - **Size of the generated dataset:** 12.00 GB - **Total amount of disk used:** 16.47 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"CIA 프로젝트에서는 데이터베이스로 들어오는 요청을 중간에 수집(Sniffing)하고 수집한 데이터를 분석(Parsing)하여 그로 인한 결과를 판단하여 알릴 수 있는 시스템(Push Service)이 필요하다. 그리고 연구를 ..." } ``` #### unshuffled_deduplicated_krc - **Size of downloaded dataset files:** 0.62 MB - **Size of the generated dataset:** 2.41 MB - **Total amount of disk used:** 3.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Шамханланы, Бийлени къаршысына ябушуп, Батыр уланларыбызны къоллары булан «ортакъ ожакъ» къургъанбыз. Шо иш уллу зараллы иш бол..." } ``` #### unshuffled_deduplicated_ku - **Size of downloaded dataset files:** 23.34 MB - **Size of the generated dataset:** 63.09 MB - **Total amount of disk used:** 86.43 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Me di 114 bernameyên xwe yên berê da perçeyên ji berhemên zanyarî yên kurdzanên mezin bi wergera kurdî da ...\\nMe di 114 bernam..." } ``` #### unshuffled_deduplicated_kv - **Size of downloaded dataset files:** 0.33 MB - **Size of the generated dataset:** 1.21 MB - **Total amount of disk used:** 1.54 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Коми кытшыслӧн ыджытжык тор вӧр увтын куйлӧ, сійӧн и фаунасӧ татӧн аркмӧтӧны вӧрын олісь подаэз. Ассямаӧн лоӧ сія, мый кытшас с..." } ``` #### unshuffled_deduplicated_kw - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼Pray without ceasing🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏..." } ``` #### unshuffled_deduplicated_ky - **Size of downloaded dataset files:** 106.22 MB - **Size of the generated dataset:** 408.40 MB - **Total amount of disk used:** 514.61 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Turmush: Бишкек шаардык кеңешинин кезексиз отурумунда мэрге ишенбөөчүлүк көрсөтүү маселеси каралат, - депутат Т.Сагынов\\nБишкек..." } ``` #### unshuffled_deduplicated_la - **Size of downloaded dataset files:** 3.42 MB - **Size of the generated dataset:** 9.79 MB - **Total amount of disk used:** 13.22 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Hæ sunt generationes Noë: Noë vir justus atque perfectus fuit in generationibus suis; cum Deo ambulavit.\\nEcce ego adducam aqua..." } ``` #### unshuffled_deduplicated_lb - **Size of downloaded dataset files:** 8.30 MB - **Size of the generated dataset:** 21.42 MB - **Total amount of disk used:** 29.72 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Während dem Gaardefestival \\\"Ambiance Jardins\\\" vum 15. bis de 17. Mee huet den SNJ nees zesumme mam Groupe Animateur en Inform..." } ``` #### unshuffled_deduplicated_lez - **Size of downloaded dataset files:** 0.77 MB - **Size of the generated dataset:** 3.08 MB - **Total amount of disk used:** 3.84 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Ахцегь хуьр, виридалай ч1ехи лезги хуьрерикая я. Ам Урусатдин виридалай къиблепатавай хуьрерикай я. Ин хуьр...\"..." } ``` #### unshuffled_deduplicated_li - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.03 MB - **Total amount of disk used:** 0.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"'t Good Goedenraad aan de Ezerbaek besjteit oet 'n kesjtièl mèt gesjlote haof en 'n park van 26 hectare. Hie in sjtoon väól beu..." } ``` #### unshuffled_deduplicated_lmo - **Size of downloaded dataset files:** 0.10 MB - **Size of the generated dataset:** 0.46 MB - **Total amount of disk used:** 0.57 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Serét (en tortonés: Sregh; en piemontés: Srèj) l'è 'n cümü italià, de la regiù del Piemónt, en Pruvìncia de Alessandria. El g'h..." } ``` #### unshuffled_deduplicated_lo - **Size of downloaded dataset files:** 23.63 MB - **Size of the generated dataset:** 119.29 MB - **Total amount of disk used:** 142.92 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ຜູ້ພິພາກສາ ປະຈຳເຂດ ສຫລ ທ່ານນຶ່ງ ຕັດສິນວ່າ ໂຄງການເກັບກຳຂໍ້ມູນ ທາງໂທລະສັບ ຂອງອົງການ ຄວາມໝັ້ນຄົງແຫ່ງຊາດ ແມ່ນຖືກຕ້ອງ ຕາມກົດໝາຍ.\\nກະ..." } ``` #### unshuffled_deduplicated_lrc - **Size of downloaded dataset files:** 0.02 MB - **Size of the generated dataset:** 0.06 MB - **Total amount of disk used:** 0.08 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"آرلینگتون یئ گئل د شأریا ڤولاتچە ڤیرجینیا و یئ گئل د شأریا ڤولات ڤولاتچە یا یأکاگئرئتە ئمریکاە. ئی شأر دویومی کألوٙن شأر د راسا..." } ``` #### unshuffled_deduplicated_lt - **Size of downloaded dataset files:** 1.65 GB - **Size of the generated dataset:** 4.20 GB - **Total amount of disk used:** 5.86 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Čir vir vir pavasaris! Čia čia čia… dalinamės labai simpatiška video pamokėle, kurią pristato ab888art galerija.\\nBe galo papra..." } ``` #### unshuffled_deduplicated_lv - **Size of downloaded dataset files:** 710.45 MB - **Size of the generated dataset:** 1.91 GB - **Total amount of disk used:** 2.62 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Dekoratīvi sliekšņi MITSUBISHI OUTLANDER 2007, izgatavoti no ovālas formas, pulētas nerūsējošā tērauda caurules...\\ndažādas tūn..." } ``` #### unshuffled_deduplicated_mai - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"१ · २ · ३ · ४ · ५ · ६ · ७ · ८ · ९ · १० · ११ · १२ · १३ · १४ · १५ · १६ · १७ · १८ · १९ · २० · २१ · २२ · २३ · २४ · २५ · २६ · २७ · २..." } ``` #### unshuffled_deduplicated_mg - **Size of downloaded dataset files:** 4.30 MB - **Size of the generated dataset:** 13.59 MB - **Total amount of disk used:** 17.89 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Nanamboatra taratasy apetaka sy soso-kevitra ho an'ny olona te-hanatevin-daharana ity fihetsiketsehana ity i Anocrena.\\nNosorat..." } ``` #### unshuffled_deduplicated_mhr - **Size of downloaded dataset files:** 1.63 MB - **Size of the generated dataset:** 6.26 MB - **Total amount of disk used:** 7.89 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Акрет жап годым Уганда кундемым Пигмей племена- влак айлен шогеныт. мемнан эран 1 курым гыч Банту племена влакат тиде кундемышк..." } ``` #### unshuffled_deduplicated_min - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.31 MB - **Total amount of disk used:** 0.33 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ..." } ``` #### unshuffled_deduplicated_mk - **Size of downloaded dataset files:** 303.12 MB - **Size of the generated dataset:** 1.19 GB - **Total amount of disk used:** 1.49 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"„Филм плус“ е насловен првиот филмски месечник во Македонија, чиј прв број ќе биде промовиран вечер во „Менада“. Новото македон..." } ``` #### unshuffled_deduplicated_ml - **Size of downloaded dataset files:** 496.80 MB - **Size of the generated dataset:** 2.69 GB - **Total amount of disk used:** 3.18 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"സ്ത്രീ പ്രവേശനം സര്‍ക്കാര്‍ പൂര്‍ണമായും അംഗീകരിക്കുന്നുവെന്നും ശബരിമലയുടെ സുരക്ഷയില്‍ ഇടപെടുമെന്നും സര്‍ക്കാര്‍ ഹൈക്കോടതിയില്‍\\..." } ``` #### unshuffled_deduplicated_mn - **Size of downloaded dataset files:** 219.52 MB - **Size of the generated dataset:** 883.46 MB - **Total amount of disk used:** 1.10 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"МУБИС-ын багш мэргэжлийн хөрвөх сургалтыг төгссөн багшид багшлах эрх олгох тухай ~ БМДИ-ийн захирлын тушаал - Багшийн мэргэжил ..." } ``` #### unshuffled_deduplicated_mr - **Size of downloaded dataset files:** 299.68 MB - **Size of the generated dataset:** 1.49 GB - **Total amount of disk used:** 1.79 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Home / motivational marathi story / उद्योजकता (Entrepreneurship) / यांना हे जमलय, तर आपल्याला का नाही जमणार ?\\nयापैकी कोणाचीही ..." } ``` #### unshuffled_deduplicated_mrj - **Size of downloaded dataset files:** 0.29 MB - **Size of the generated dataset:** 1.10 MB - **Total amount of disk used:** 1.38 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Лӹпӹвлӓ (латинлӓ Lepidoptera ; алыкмарла лыве-влак) — капшангывлӓ йыхыш пырышы сӱмӓн нӹл шылдыран капшангывлӓ. Цилӓжӹ 180000 тӹ..." } ``` #### unshuffled_deduplicated_ms - **Size of downloaded dataset files:** 16.39 MB - **Size of the generated dataset:** 49.45 MB - **Total amount of disk used:** 65.85 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Sanad pertama daripada Zuhair bin Harb daripada ‘Affan daripada Hammad daripada Thabit daripada Anas.\\nSanad kedua daripada ‘Ab..." } ``` #### unshuffled_deduplicated_mt - **Size of downloaded dataset files:** 5.90 MB - **Size of the generated dataset:** 17.68 MB - **Total amount of disk used:** 23.58 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "tibgħat il-kawża lura lill-Qorti Ġenerali għall-annullament jew għat-tnaqqis tal-penalità imposta mill-Kummissjoni bid-deċiżjoni inizjali kif emendata bid-deċiżjoni ta’ rettifika;" } ``` #### unshuffled_deduplicated_mwl - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Deciplina social i outónoma que angloba atebidades de ouserbaçon, de análeze, de çcriçon, cumparaçon, de sistematizaçon i de sp..." } ``` #### unshuffled_deduplicated_my - **Size of downloaded dataset files:** 207.14 MB - **Size of the generated dataset:** 1.11 GB - **Total amount of disk used:** 1.32 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ျမ၀တီ - ရန္ကုန္တိုင္းေဒသႀကီး ေျမာက္ဥကၠလာပႏွင္႕ ဗဟန္းၿမိဳ႔နယ္ မေကြးတိုင္း ေဒသႀကီး ပခုကၠဴၿမိဳ႔နယ္တို႔၌ ျမန္မာ႕တပ္မေတာ္အား ေထာက္ခံ..." } ``` #### unshuffled_deduplicated_myv - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"2018 иень умарьковонь 6-це чистэ сась паро куля! Россиянь культурань Министерствась макссь невтемань конёв (прокатной удостовер..." } ``` #### unshuffled_deduplicated_mzn - **Size of downloaded dataset files:** 0.16 MB - **Size of the generated dataset:** 0.63 MB - **Total amount of disk used:** 0.79 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"قرآن یا قوران اسلام ِآسمونی کتاب هسته. مسلمونون گانّّه قرآن ره خدا، وحی جه برسنی‌یه، «محمد معجزه» هسته و ثقلین حدیث دله ونه خَو..." } ``` #### unshuffled_deduplicated_nah - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "In mācuīlpōhualxihuitl VI (inic chicuacē) in mācuīlpōhualli xiuhitl cāhuitl īhuīcpa 501 xihuitl oc 600 xihuitl." } ``` #### unshuffled_deduplicated_nap - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ò AUDIT í Ç è î ÿ å å 30 ò ÿ ÿ é, õ ñ ì ÿ, ê ã- ò à ì. å â å í ç â à à é ñ è å é ó ó ë. å å å û è å î é è à. à è à AUDIT 1-7 â ..." } ``` #### unshuffled_deduplicated_nds - **Size of downloaded dataset files:** 5.27 MB - **Size of the generated dataset:** 13.48 MB - **Total amount of disk used:** 18.76 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Dor kann sik vun nu af an de hele plattdüütsche Welt – vun Niebüll bit New York, vun Helgoland bit Honolulu – drapen. Allens, w..." } ``` #### unshuffled_deduplicated_ne - **Size of downloaded dataset files:** 240.63 MB - **Size of the generated dataset:** 1.24 GB - **Total amount of disk used:** 1.48 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"बर्दिबास नगरपालिकाको तेस्रो नगर परिषदबाट पारित आ.व.२०७३।७४ को संशोधित र २०७४।७५ को प्रस्तावित नीति, कार्यक्रम तथा बजेट\\nअार्थिक..." } ``` #### unshuffled_deduplicated_new - **Size of downloaded dataset files:** 0.83 MB - **Size of the generated dataset:** 4.26 MB - **Total amount of disk used:** 5.09 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"थ्व शहरयागु अक्षांश ३४.७००१६४ उत्तर व देशान्तर ८६.३७६४६९ पश्चिम खः (34.700164° N 86.376469° W)। थ्व थासे ७२२६७३२ वर्ग मिटर (२.७..." } ``` #### unshuffled_deduplicated_nl - **Size of downloaded dataset files:** 15.73 GB - **Size of the generated dataset:** 41.91 GB - **Total amount of disk used:** 57.65 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Op vrijdag 31 augustus wordt het nieuwe studiejaar van de masteropleiding architectuur geopend met een dagexcursie naar Venlo.\\..." } ``` #### unshuffled_deduplicated_nn - **Size of downloaded dataset files:** 23.58 MB - **Size of the generated dataset:** 58.32 MB - **Total amount of disk used:** 81.90 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Planomtale krav til innhald Bakgrunn: Spørsmål frå fleire kommunar om kva ein planomtale/planbeskrivelse bør innehalde Fylkeskommunen og fylkesmannen har i ein del saker reist motsegn på formelt grunnlag" } ``` #### unshuffled_deduplicated_no - **Size of downloaded dataset files:** 1.96 GB - **Size of the generated dataset:** 5.11 GB - **Total amount of disk used:** 7.07 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Ytterligere aktører i primærhelsetjenesten og andre NHS-virksomheter ble infisert, inkludert legekontor.Læreren vår er så attra..." } ``` #### unshuffled_deduplicated_oc - **Size of downloaded dataset files:** 1.34 MB - **Size of the generated dataset:** 4.00 MB - **Total amount of disk used:** 5.34 MB An example of 'train' looks as follows. ``` { "id": 1, "text": ".рф (rf, còdi punycode: .xn--p1ai)[1] es lo nom de domeni en rus per Russia. Foguèt activat lo 12 de mai de 2010. Lo còdi latin es .ru." } ``` #### unshuffled_deduplicated_or - **Size of downloaded dataset files:** 38.72 MB - **Size of the generated dataset:** 197.63 MB - **Total amount of disk used:** 236.36 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ଭୁବନେଶ୍ୱର, ୨୭/୧– (ଓଡ଼ିଆ ପୁଅ) ସିପିଆଇ ଜାତୀୟ ପରିଷଦର ଆହ୍ୱାନକ୍ରମେ ଗତକାଲି ଜାନୁୟାରୀ ୨୬ ସାଧାରଣତନ୍ତ୍ର ଦିବସକୁ ଦେଶ ବ୍ୟାପୀ ସମ୍ବିଧାନ ସୁରକ୍ଷା ..." } ``` #### unshuffled_deduplicated_os - **Size of downloaded dataset files:** 2.83 MB - **Size of the generated dataset:** 11.00 MB - **Total amount of disk used:** 13.83 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"1. Лæппу æмæ чызг казрæдзийы зæрдæмæ куы фæцæуынц æмæ, куы сфæнд кæнынц сæ цард баиу кæнын, уæд лæппу бар ракуры чызгæй, цæмæй ..." } ``` #### unshuffled_deduplicated_pa - **Size of downloaded dataset files:** 102.39 MB - **Size of the generated dataset:** 483.04 MB - **Total amount of disk used:** 585.42 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ਰਜਿ: ਨੰ: PB/JL-138/2018-20 ਜਿਲਦ 63, ਬਾਨੀ ਸੰਪਾਦਕ (ਸਵ:) ਡਾ: ਸਾਧੂ ਸਿੰਘ ਹਮਦਰਦ ਫ਼ੋਨ : 0181-2455961-62-63, 5032400, ਫੈਕਸ : 2455960, 2..." } ``` #### unshuffled_deduplicated_pam - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Áku pu i Anak ning Aláya at ngeni ipákit kó kékayu ngan nûng makanánu lang susúlat détinang kulit a mágkas. Lauan ya ing tarátu..." } ``` #### unshuffled_deduplicated_pl - **Size of downloaded dataset files:** 20.19 GB - **Size of the generated dataset:** 50.59 GB - **Total amount of disk used:** 70.78 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"System informatyczny - Załącznik nr 1 do zarządzenia Wójta Gminy Podegrodzie Nr 530/2013 z dnia 27 maja 2013 r\\nSystem informat..." } ``` #### unshuffled_deduplicated_pms - **Size of downloaded dataset files:** 0.71 MB - **Size of the generated dataset:** 2.00 MB - **Total amount of disk used:** 2.72 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Louvigné-du-Désert a l'é na comun-a fransèisa ant la region aministrativa dla Brëtagna, ant ël dipartiment d'Ille-et-Vilaine. A..." } ``` #### unshuffled_deduplicated_pnb - **Size of downloaded dataset files:** 2.58 MB - **Size of the generated dataset:** 9.44 MB - **Total amount of disk used:** 12.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ایہ فائل Wikimedia Commons توں اے تے دوجیاں ویونتاں تے وی ورتی جاےکدی اے۔ گل بات اس دے فائل گل بات صفہ تے تھلے دتی گئی۔\"..." } ``` #### unshuffled_deduplicated_ps - **Size of downloaded dataset files:** 71.83 MB - **Size of the generated dataset:** 254.79 MB - **Total amount of disk used:** 326.61 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Many people usually use the time period ‘business to business (B2B) advertising,’ however most of them do not know precisely wh..." } ``` #### unshuffled_deduplicated_pt - **Size of downloaded dataset files:** 26.00 GB - **Size of the generated dataset:** 68.37 GB - **Total amount of disk used:** 94.37 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Você pode estar lendo este texto no sofá, levantar pra pegar uma breja na geladeira, dar uma cagada e sentar novamente, sem int..." } ``` #### unshuffled_deduplicated_qu - **Size of downloaded dataset files:** 0.02 MB - **Size of the generated dataset:** 0.07 MB - **Total amount of disk used:** 0.09 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Warayu wichay (kastilla simipi: Ascensión de Guarayos) nisqaqa Buliwya mama llaqtapi, Santa Krus suyupi, huk llaqtam, Warayu pruwinsyap uma llaqtanmi." } ``` #### unshuffled_deduplicated_rm - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"practicists agrars / practicistas agraras AFP pon far ina furmaziun da basa scursanida per cuntanscher in attestat federal da q..." } ``` #### unshuffled_deduplicated_ro - **Size of downloaded dataset files:** 4.48 GB - **Size of the generated dataset:** 11.66 GB - **Total amount of disk used:** 16.14 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"“În viață, oportunitatea nu este totul. Cine atrage Lumina, cineva bun în umbră. Timpul ne creează.” maestru\\nLyn.Evans: Ce mar..." } ``` #### unshuffled_deduplicated_ru - **Size of downloaded dataset files:** 166.68 GB - **Size of the generated dataset:** 611.70 GB - **Total amount of disk used:** 778.38 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Доступ к данному профилю для публичного просмотра закрыт администрацией сайта - профиль находится на модерации.\\nРазработчикам ..." } ``` #### unshuffled_deduplicated_sa - **Size of downloaded dataset files:** 7.27 MB - **Size of the generated dataset:** 38.33 MB - **Total amount of disk used:** 45.60 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"अनिरुद्धनगरे क्रीडिता रामलीला सम्‍प्रति समाप्‍ता अस्ति । तस्‍य कानिचन् चित्राणि पूर्वमेव प्रकाशितानि सन्ति । द्वौ चलचित्रौ अपि ..." } ``` #### unshuffled_deduplicated_sah - **Size of downloaded dataset files:** 7.01 MB - **Size of the generated dataset:** 27.46 MB - **Total amount of disk used:** 34.49 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████..." } ``` #### unshuffled_deduplicated_scn - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "La gilusìa è nu sintimentu dulurusu ca nasci d'un disideriu di pussessu sclusivu ntê cunfrunti dâ pirsuna amata e dû timuri, dû suspettu o dâ cirtizza dâ sò nfidiltati." } ``` #### unshuffled_deduplicated_sd - **Size of downloaded dataset files:** 74.17 MB - **Size of the generated dataset:** 275.48 MB - **Total amount of disk used:** 349.66 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"هر ڪو ڄاڻي ٿو ته جڏهن توهان هڪ وڏي خريد ڪرڻ چاهيون ٿا, توهان پڄي ضروري حڪم ۾ ان جي ڪم ڪرڻ جي هٿ ۾ لاڳاپو ڪيو آهي. جي شيء آهي ته..." } ``` #### unshuffled_deduplicated_sh - **Size of downloaded dataset files:** 1.45 MB - **Size of the generated dataset:** 6.44 MB - **Total amount of disk used:** 7.87 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Opština Gornja Radgona se nalazi u sjeveroistočnoj Sloveniji i graniči s susjednom Austriji duž rijeke Mure. Sa tridesetim nase..." } ``` #### unshuffled_deduplicated_si - **Size of downloaded dataset files:** 175.62 MB - **Size of the generated dataset:** 842.57 MB - **Total amount of disk used:** 1.02 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ලාංකීය සිතිවිලි සිංහල බ්ලොග් කියවනය කොත්තු සින්ඩිය ලංකා Blogger හත්මාළුව ලංකා බ්ලොග් කියවනය මාතලන්ගේ සින්ඩිය මොබයිල්lk\\nඅවකාශය ..." } ``` #### unshuffled_deduplicated_sk - **Size of downloaded dataset files:** 1.96 GB - **Size of the generated dataset:** 4.80 GB - **Total amount of disk used:** 6.76 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Aktivity | Agentúra podporovaného zamestnávania | vzdelávanie pre klientov, vzdelávanie pre odborníkov, kurzy\\nŠpecializované k..." } ``` #### unshuffled_deduplicated_sl - **Size of downloaded dataset files:** 523.22 MB - **Size of the generated dataset:** 1.32 GB - **Total amount of disk used:** 1.85 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Če Creatures, ki je želel, da pridejo na čas, predvsem je povedlo – razlikuje od ljubosumja začel grizenja kolen (ali zadnjica)..." } ``` #### unshuffled_deduplicated_so - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"тттттттттттттттттттттттттттттттт тттттттттттттттттттттттттттттттт тттттттттттттттттттттттттттттттт ттттттттттттттттуууууууууууу..." } ``` #### unshuffled_deduplicated_sq - **Size of downloaded dataset files:** 445.36 MB - **Size of the generated dataset:** 1.21 GB - **Total amount of disk used:** 1.66 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Çfarë do të më pëlqente tek një femër ose çfarë do të më shndërronte në një shpërthim drite? – Albert Vataj\\nTë gjithëve një zo..." } ``` #### unshuffled_deduplicated_sr - **Size of downloaded dataset files:** 665.03 MB - **Size of the generated dataset:** 2.36 GB - **Total amount of disk used:** 3.03 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Корисни савети за сваки дан. На сајту су разне категорије, као што су љепота, мода, кување и поправка властитим рукама.\\nШколск..." } ``` #### unshuffled_deduplicated_su - **Size of downloaded dataset files:** 0.05 MB - **Size of the generated dataset:** 0.16 MB - **Total amount of disk used:** 0.21 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Kartu krédit nyaéta \"duit plastik\" anu dikaluarkeun ku bank pikeun alat pambayaran di tempat-tempat nu tangtu samisal jiga di hotél, réstoran, tempat rékréasi jeung sajabana.[1]" } ``` #### unshuffled_deduplicated_sv - **Size of downloaded dataset files:** 10.19 GB - **Size of the generated dataset:** 26.33 GB - **Total amount of disk used:** 36.51 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"1783 är ett viktigt årtal i den nya tidens historia. Det året slöts en fred i Paris och därmed blev de 13 brittiska kolonierna ..." } ``` #### unshuffled_deduplicated_sw - **Size of downloaded dataset files:** 2.95 MB - **Size of the generated dataset:** 8.98 MB - **Total amount of disk used:** 11.92 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Miripuko hiyo inakuja mwanzoni mwa Wiki Takatifu kuelekea Pasaka na ikiwa ni wiki chache tu kabla ya Papa Francis kuanza ziara yake katika nchi hiyo yenye idadi kubwa kabisa ya watu katika ulimwengu wa nchi za Kiarabu." } ``` #### unshuffled_deduplicated_ta - **Size of downloaded dataset files:** 971.12 MB - **Size of the generated dataset:** 5.48 GB - **Total amount of disk used:** 6.45 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"பொழுது சாய்ந்து வெகு நேரமாகிவிட்டது. கூலி வேலைக்குப் போயிருந்த 'சித்தாள் ' பெண்கள் எல்லோரும் வீடு திரும்பி விட்டார்கள். இன்னும்..." } ``` #### unshuffled_deduplicated_te - **Size of downloaded dataset files:** 342.43 MB - **Size of the generated dataset:** 1.70 GB - **Total amount of disk used:** 2.04 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"హర్యానాలో టోల్ దగ్గర సిబ్బంది.. స్థానిక ప్రజలు కొట్టుకున్నారు. కర్నాల్ అనే గ్రామానికి సమీపంలో టోల్ గేట్ ఉంది. అయితే సాధారణంగా స..." } ``` #### unshuffled_deduplicated_tg - **Size of downloaded dataset files:** 62.90 MB - **Size of the generated dataset:** 261.68 MB - **Total amount of disk used:** 324.60 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ҳумайро гуфтааст, мухолифи низом аст, низоме, ки дар Тоҷикистон вуҷуд дорад. Ба ин маънӣ, худро мухолифи давлату ҳукумати Тоҷик..." } ``` #### unshuffled_deduplicated_th - **Size of downloaded dataset files:** 3.54 GB - **Size of the generated dataset:** 17.11 GB - **Total amount of disk used:** 20.65 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ฟันที่แลดูขาวสะอาดไม่มีเศษอาหารติดอยู่ เหงือกสีชมพู ไม่เจ็บ หรือมีเลือดออกเวลาแปรงฟันหรือขัดฟัน ไม่มีปัญหาเรื่องกลิ่นปาก ทำให้ก..." } ``` #### unshuffled_deduplicated_tk - **Size of downloaded dataset files:** 2.22 MB - **Size of the generated dataset:** 7.12 MB - **Total amount of disk used:** 9.34 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Türkmenistanyň Prezidenti agyr atletika boýunça dünýä çempionatyna taýýarlyk işleriniň barşy bilen tanyşdy\\nHalallykdan kemal t..." } ``` #### unshuffled_deduplicated_tl - **Size of downloaded dataset files:** 151.34 MB - **Size of the generated dataset:** 431.69 MB - **Total amount of disk used:** 583.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"“Gusto ko manawagan sa mga Unit Head ng Chanel 2 Salve. Kasi napapansin ko iyon mga alaga ko ang taping halos once a week lang,..." } ``` #### unshuffled_deduplicated_tr - **Size of downloaded dataset files:** 10.39 GB - **Size of the generated dataset:** 28.47 GB - **Total amount of disk used:** 38.86 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Son yıllarda görülen ay tutulmalarına göre daha etkili olacağı söylenen Kanlı veya Kırmızı Ay Tutulmasına saatler kaldı. Bu akş..." } ``` #### unshuffled_deduplicated_tt - **Size of downloaded dataset files:** 85.89 MB - **Size of the generated dataset:** 321.37 MB - **Total amount of disk used:** 407.26 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"\\\"Иремнең вафатына 40 көн узгач, Алмаз да безнең өйгә кереп үлде\\\". Арчада 35 яшьлек ир өстенә кондызлар ега башлаган агач төшк..." } ``` #### unshuffled_deduplicated_tyv - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Экии, хүндүлуг аалчылар болгаш тыва дылдың деткикчилери! Тыва дылдың болгаш чогаалдың ховар бир башкызынга, Менги Ооржакка, ажы..." } ``` #### unshuffled_deduplicated_ug - **Size of downloaded dataset files:** 20.53 MB - **Size of the generated dataset:** 86.44 MB - **Total amount of disk used:** 106.97 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"زاڭ-ءتۇزىم | عىلىم-تەحنيكا | ءتىل-ادەبيەت | تۇرمىس | دەنە تاربيە | ساياحات-ورتا | سۋرەتتى حابار | سىر سۇحبات | ارناۋلى تاقىرىپ ..." } ``` #### unshuffled_deduplicated_uk - **Size of downloaded dataset files:** 8.04 GB - **Size of the generated dataset:** 29.86 GB - **Total amount of disk used:** 37.90 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Про надання роз'яснення (щодо форми письмового зобов'язання громадян про зворотне ввезення/вивезення товарів), Державна митна с..." } ``` #### unshuffled_deduplicated_ur - **Size of downloaded dataset files:** 483.59 MB - **Size of the generated dataset:** 1.82 GB - **Total amount of disk used:** 2.31 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"آئیے اہم اسلامی کتب کو یونیکوڈ میں انٹرنیٹ پر پیش کرنے کے لئے مل جل کر آن لائن ٹائپنگ کریں۔ محدث ٹائپنگ پراجیکٹ کے ذریعے آپ روز..." } ``` #### unshuffled_deduplicated_uz - **Size of downloaded dataset files:** 4.30 MB - **Size of the generated dataset:** 12.00 MB - **Total amount of disk used:** 16.29 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Qurama tog'lari tizmasining Toshkentdan 154 km uzoqlikdagi Toshkent-Ush yo'li yeqasidaxushmanzara tabiat qo'ynida joylashgan maydoni 30 ga.\nBolalarni sog'lomlashtirish oromgohi Bo'stonliq tumani Oqtosh muntaqasining soy-salqin gushasida joylashgan." } ``` #### unshuffled_deduplicated_vec - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Par ogni pónto, ła derivada ła xe ła pendensa de ła reta tangente a ła curva de ła funsion f. Ła reta de cołor róso l'è senpre ..." } ``` #### unshuffled_deduplicated_vi - **Size of downloaded dataset files:** 10.71 GB - **Size of the generated dataset:** 33.60 GB - **Total amount of disk used:** 44.31 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Canh chua cá bông lau không chỉ là món ăn giải nhiệt, thanh mát ngày hè mà còn là món siêu bổ dưỡng, rất tốt cho người gầy ốm. ..." } ``` #### unshuffled_deduplicated_vo - **Size of downloaded dataset files:** 0.30 MB - **Size of the generated dataset:** 2.10 MB - **Total amount of disk used:** 2.40 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Sarniguet binon zif in ziläk: Hautes-Pyrénées, in topäd: Midi-Pyrénées, in Fransän. Sarniguet topon videtü 43°19’ 7’’ N e lunetü 0°5’ 19’’ L." } ``` #### unshuffled_deduplicated_wa - **Size of downloaded dataset files:** 0.08 MB - **Size of the generated dataset:** 0.22 MB - **Total amount of disk used:** 0.29 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Cisse pådje ci n' est co k' on djermon, dj' ô bén k' el pådje est djusse sibåtcheye, eyet co trop tene; et s' divreut ele ecråxhî ene miete." } ``` #### unshuffled_deduplicated_war - **Size of downloaded dataset files:** 0.55 MB - **Size of the generated dataset:** 2.36 MB - **Total amount of disk used:** 2.90 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "An Honce amo in usa ka baryo ngan munisipalidad ha distrito han Rožňava ha rehiyon han Košice ha nasod han Slovakia.\nAn Rumegies amo in usa ka komyun ha departamento han Nord ngan ha rehiyon han Nord-Pas-de-Calais ha nasod han Fransya." } ``` #### unshuffled_deduplicated_wuu - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.03 MB - **Total amount of disk used:** 0.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"伊春元旦天气 伊春腊八天气 伊春春节天气 伊春情人节天气 伊春元宵节天气 伊春愚人节天气 伊春清明节天气 伊春劳动节天气 伊春母亲节天气 伊春端午节天气 伊春七夕节天气 伊春教师节天气 伊春中秋节天气 伊春国庆节天气 伊春重阳节天气 伊春万圣节天气 伊春..." } ``` #### unshuffled_deduplicated_xal - **Size of downloaded dataset files:** 0.03 MB - **Size of the generated dataset:** 0.12 MB - **Total amount of disk used:** 0.15 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Арнгудин Орн гисн Европд бәәдг һазр. 2007 җилин тooһaр эн орн нутгт 3,600,523 әмтн бәәдг билә. Арнгудин Орнин хотл балһсна нерн..." } ``` #### unshuffled_deduplicated_xmf - **Size of downloaded dataset files:** 0.94 MB - **Size of the generated dataset:** 4.63 MB - **Total amount of disk used:** 5.58 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"მოჩამილი ტექსტი წჷმორინელი რე Creative Commons Attribution-ShareAlike ლიცენზიათ; შილებე გეძინელი პირობეფიშ არსებუა. კილიშკილიშა..." } ``` #### unshuffled_deduplicated_yi - **Size of downloaded dataset files:** 22.20 MB - **Size of the generated dataset:** 88.29 MB - **Total amount of disk used:** 110.49 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ממשותדיק - חבֿרה, איך אַרבעט איצט אױף אַ זשורנאַל. טאָמער איר האָט עפּעס צוצוגעבן זאָלט איר שיקן מיר אַן אָנזאָג. ס'װעט הײסן \\\"..." } ``` #### unshuffled_deduplicated_yo - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.03 MB - **Total amount of disk used:** 0.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Copyright © 2018 BBC. BBC kò mọ̀ nípa àwọn ohun tí ó wà ní àwọn ojú òpó tí ó wà ní ìta. Ọwọ́ tí a fi mú ìbáṣepọ̀ ti ìta.\"..." } ``` #### unshuffled_deduplicated_yue - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 你還不爆 我累了 投降輸一半可以嗎\"..." } ``` #### unshuffled_deduplicated_zh - **Size of downloaded dataset files:** 99.98 GB - **Size of the generated dataset:** 267.88 GB - **Total amount of disk used:** 367.86 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"中国铝灰网 中国有色金属矿产网 中国黄莲网 中国水轮发电机网 中国抽油泵网 中国数控雕刻机网 中国不锈钢抛光网 中国磨具加工网 中国压铸铝网 中国耐水腻子网 中国手机摄像头网 中国粗粮网 中国车门锁网 中国钛粉网 中国轮圈网\\n天天中奖彩票图 天天中彩票..." } ``` </details> <details> <summary>Click to expand the Data/size information for each language (original)</summary> #### unshuffled_original_af - **Size of downloaded dataset files:** 85.79 MB - **Size of the generated dataset:** 254.08 MB - **Total amount of disk used:** 339.87 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "aanlyn markte as gevolg van ons voortgesette 'n begrip opsie handel sakeplan pdf terwyl ons steeds die gereelde ons binêre opsies handel" } ``` #### unshuffled_original_als - **Size of downloaded dataset files:** 1.49 MB - **Size of the generated dataset:** 5.30 MB - **Total amount of disk used:** 6.78 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"De Nazionalpark hät e Flächi vo 170,3 km² und isch dodemit s grösti Naturschutzgebiet vo de Schwiz. Er ligt uf em Gebiet vo de ..." } ``` #### unshuffled_original_am - **Size of downloaded dataset files:** 102.79 MB - **Size of the generated dataset:** 378.06 MB - **Total amount of disk used:** 480.85 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"አየር መንገዱ ከአዲስ አበባ ወደ ሮም ጣሊያን በማምራት ላይ በነበረበት ጊዜ ረዳት አብራሪው የጉዞውን አቅጣጫ በመቀየር ጄኔቭ አውሮፓላን ማረፊያ በማሳረፍ እጁን ለፖሊስ ሰጥቷል።\\nየኢትዮጵያ መንግስት የ..." } ``` #### unshuffled_original_an - **Size of downloaded dataset files:** 0.15 MB - **Size of the generated dataset:** 1.33 MB - **Total amount of disk used:** 1.48 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"واااااااأسفاه الأمم تفتخر ب 0 أمي ووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووووو..." } ``` #### unshuffled_original_ar - **Size of downloaded dataset files:** 22.23 GB - **Size of the generated dataset:** 87.94 GB - **Total amount of disk used:** 110.17 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"مرحبا بك عزيز الزائر نتمنى لك أوقاتاً سعيدة معنا وأن نزداد شرفا بخدمتك ولا تنسى التسجيل معنا لتستفيد بكل جديد\\nأهلا وسهلا بك زا..." } ``` #### unshuffled_original_arz - **Size of downloaded dataset files:** 15.90 MB - **Size of the generated dataset:** 70.13 MB - **Total amount of disk used:** 86.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"بنى عجل : قبيلة من عجل بن لجيم بن صعب بن على بن بكر بن وائل انتقل اغلبهم الى البصرة فى العراق و اصفهان و خراسان فى ايران و اذرب..." } ``` #### unshuffled_original_as - **Size of downloaded dataset files:** 21.43 MB - **Size of the generated dataset:** 117.73 MB - **Total amount of disk used:** 139.17 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"আমি, এই সংগঠনৰ সদস্য সকলে একেলগ হৈ অসমকে ধৰি ভাৰতৰ উত্তৰ পূৰ্বাঞ্চলৰ অমূল্য কলা-সাংস্কৃতিক সম্পদৰাজি বৃহত্তৰ অষ্ট্ৰেলিয়াৰ সন্মু..." } ``` #### unshuffled_original_ast - **Size of downloaded dataset files:** 0.92 MB - **Size of the generated dataset:** 2.54 MB - **Total amount of disk used:** 3.46 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"The Killers llanzaron el so álbum debú, Hot Fuss, en xunu de 2004 nel Reinu Xuníu, al traviés de la discográfica Lizard King, y..." } ``` #### unshuffled_original_av - **Size of downloaded dataset files:** 0.08 MB - **Size of the generated dataset:** 0.42 MB - **Total amount of disk used:** 0.50 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Жинда малъараб ва божизе бегьулеб рагІудаса кьуризе бегьуларо гьев. Гьес насихІат гьабизе кколелъул бацІцІадаб диналъул рахъалъ..." } ``` #### unshuffled_original_az - **Size of downloaded dataset files:** 927.76 MB - **Size of the generated dataset:** 2.96 GB - **Total amount of disk used:** 3.89 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"AZTV-Artıq 7 ildir ki, Abşeron rayonu dotasiya almadan bütün xərclərini yerli daxilolmalar hesabına maliyyələşdirir.\\nDünən, 10..." } ``` #### unshuffled_original_azb - **Size of downloaded dataset files:** 6.64 MB - **Size of the generated dataset:** 28.47 MB - **Total amount of disk used:** 35.11 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"لعلی ١٣-جو عصرده یاشاییب یاراتمیش گؤرکملی آذربایجان شاعرلریندندیر. ١٢٢٤-جی ایلده تبریزده آنادان اولموشدور، گنج یاشلاریندا تیجار..." } ``` #### unshuffled_original_ba - **Size of downloaded dataset files:** 33.22 MB - **Size of the generated dataset:** 133.70 MB - **Total amount of disk used:** 166.92 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Күҙәтеү ҡуласаһы моделен хәҙер Мифтахетдин Аҡмулла исемендәге Башҡорт дәүләт педагогия университетында ла эшләргә мөмкин\\t\\nКүҙ..." } ``` #### unshuffled_original_bar - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": " vo" } ``` #### unshuffled_original_bcl - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"& ÿ ó / í 0 - ø û ù ö ú ð ï ú \\u0014 ù þ ô ö í ÷ ò \\u0014 ÷ í ù û ö í \\u0001 û ñ ç þ \\u0001 ð \\u0007 þ ò ñ ñ ò ô \\u0017 û ö ô ÷..." } ``` #### unshuffled_original_be - **Size of downloaded dataset files:** 498.29 MB - **Size of the generated dataset:** 1.88 GB - **Total amount of disk used:** 2.38 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Брэсцкія ўлады не дазволілі прафсаюзу РЭП правесці пікетаванне ў парку Воінаў-інтэрнацыяналістаў 30 мая 2018 года.\\nСітуацыю пр..." } ``` #### unshuffled_original_bg - **Size of downloaded dataset files:** 8.34 GB - **Size of the generated dataset:** 33.75 GB - **Total amount of disk used:** 42.09 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ЖАЛБОПОДАТЕЛЯТ директор на Дирекция „ Обжалване и данъчно-осигурителна практика“- Бургас, редовно призован, се представлява от ..." } ``` #### unshuffled_original_bh - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.12 MB - **Total amount of disk used:** 0.13 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"सुकमा जिला भारत के छत्तीसगढ़ राज्य में एगो जिला बाटे। एकर मुख्यालय सुकमा शहर बाटे। एकर कुल रकबा 5636 वर्ग कि॰मी॰ बाटे।\"..." } ``` #### unshuffled_original_bn - **Size of downloaded dataset files:** 2.14 GB - **Size of the generated dataset:** 10.77 GB - **Total amount of disk used:** 12.91 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ভড়ং সর্বস্ব বাংলা আর্ট অ্যান্ড কালচারের হিসাব গুলিয়ে দেওয়ার ম্যাজিকের নাম ব্রাত্য রাইসু November 23, 2017\\nভড়ং সর্বস্ব বাংলা আর..." } ``` #### unshuffled_original_bo - **Size of downloaded dataset files:** 28.94 MB - **Size of the generated dataset:** 195.40 MB - **Total amount of disk used:** 224.34 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"བོད་མི་འདི་དག་ནི་རང་རྒྱུད་སྒོ་རུ་ཕུད་དེ་གཞན་རྒྱུད་པང་དུ་ཉར་ནས་གསོ་སྐྱོང་བྱེད་དགོས་ཟེར་བ་དང་གཅིག་མཚུངས་རེད།\\nཚན་རིག་ནི་དང་ཐོག་རང..." } ``` #### unshuffled_original_bpy - **Size of downloaded dataset files:** 0.34 MB - **Size of the generated dataset:** 4.35 MB - **Total amount of disk used:** 4.69 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"পৌরসভা এহার আয়তন (লয়াহান) ২,৭৩০,.৬৩ বর্গ কিলোমিটার। পৌরসভা এহার মাপাহানর অক্ষাংশ বারো দ্রাঘিমাংশ ইলতাই 18.63° S 48.18° W ।[১]..." } ``` #### unshuffled_original_br - **Size of downloaded dataset files:** 9.18 MB - **Size of the generated dataset:** 30.20 MB - **Total amount of disk used:** 39.38 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ar mank Magalhães(Daveoù a vank) a zo ur spesad evned, Spheniscus magellanicus an anv skiantel anezhañ.\\nGallout a reer implijo..." } ``` #### unshuffled_original_bs - **Size of downloaded dataset files:** 0.05 MB - **Size of the generated dataset:** 0.48 MB - **Total amount of disk used:** 0.53 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ž šř é ú šř šř ě šř ž é č ě ž ů ě ď éé ýš ě ě Ž č š ý ě ď é ýš ě ď ě éé ýš ě č ž ě š ý ď ě ýš é ú č ž č š ý ď ý ž é éě ď é č ýš..." } ``` #### unshuffled_original_bxr - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"2002 оной хабар буряад хэлэ бэшэгэй һалбари Үндэһэтэнэй хүмүүнлиг ухаанай дээдэ һургуули болгогдожо өөршэлэгдөө.\\nХарин мүнөө б..." } ``` #### unshuffled_original_ca - **Size of downloaded dataset files:** 3.10 GB - **Size of the generated dataset:** 8.62 GB - **Total amount of disk used:** 11.73 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Daniel Vendrell, conegut com Vandrell, ha sigut un dels il•lustradors contemporanis més influents, representant a la nova onada..." } ``` #### unshuffled_original_cbk - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano yo gano..." } ``` #### unshuffled_original_ce - **Size of downloaded dataset files:** 2.09 MB - **Size of the generated dataset:** 8.73 MB - **Total amount of disk used:** 10.82 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Шаьш анархисташ ду бохучу жигархойн дIахьедарехь дуьйцу, оьрсийн ницкъаллийн структурийн а, федералан каналан а Iалашонаш \\\"мар..." } ``` #### unshuffled_original_ceb - **Size of downloaded dataset files:** 11.07 MB - **Size of the generated dataset:** 40.97 MB - **Total amount of disk used:** 52.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Si Isko walay pupamilok nga nagtan-aw sa unahan, natugaw. “Naunsa ka gud diha Isko nga layo man kaayo ang imong panan-aw?” ni I..." } ``` #### unshuffled_original_ckb - **Size of downloaded dataset files:** 111.88 MB - **Size of the generated dataset:** 510.97 MB - **Total amount of disk used:** 622.85 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"رسی رۆژ - ساڵێک دوای بومەلەرزەی کرماشان میوانی بەرنامە : کاک سیاوەش حەیاتی چالاکی مەدەنی -قەسری شیرین\\nپارچە موزیک 30 / 10 / 20..." } ``` #### unshuffled_original_cs - **Size of downloaded dataset files:** 21.72 GB - **Size of the generated dataset:** 57.08 GB - **Total amount of disk used:** 78.80 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Akce anarchistů proti připravovanému novému služební řádu a nízkým mzdám 1903 – Historie českého anarchismu (1880 – 1939)\\nRost..." } ``` #### unshuffled_original_cv - **Size of downloaded dataset files:** 9.40 MB - **Size of the generated dataset:** 41.05 MB - **Total amount of disk used:** 50.45 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Шыранӑ чухне ӑнсӑртран латин кирилл саспаллисем вырӑнне латин саспаллисене ҫырсан, сайт эсир ҫырнине юсама тӑрӑшӗ.\\nКу сайтра ч..." } ``` #### unshuffled_original_cy - **Size of downloaded dataset files:** 81.74 MB - **Size of the generated dataset:** 224.93 MB - **Total amount of disk used:** 306.67 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Mae capeli Cymreig yr Andes ym Mhatagonia wedi cyhoeddi na fydd gwasanaethau yno weddill y mis, oherwydd yr eira trwm sydd wedi..." } ``` #### unshuffled_original_da - **Size of downloaded dataset files:** 6.00 GB - **Size of the generated dataset:** 16.76 GB - **Total amount of disk used:** 22.76 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Den 2.-5. februar 2016 løb det tredje kursus i uddannelsen af 4kommunesamarbejdets Local Impact Coaches, af stablen i Gentofte ..." } ``` #### unshuffled_original_de - **Size of downloaded dataset files:** 119.51 GB - **Size of the generated dataset:** 331.22 GB - **Total amount of disk used:** 450.73 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Auf dieser Seite gibt es mind. ein YouTube Video. Cookies für diese Website wurden abgelehnt. Dadurch können keine YouTube Vide..." } ``` #### unshuffled_original_diq - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Zıwanê Slawki, zıwano merdumanê Slawano. Zıwanê Slawki yew lızgeyê Zıwananê Hind u Ewropao. Keyeyê Zıwananê Slawki beno hirê letey:" } ``` #### unshuffled_original_dsb - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Pśiklaskaju južo pśed pśedstajenim... 1500 źiśi njamóžo wěcej docakaś, měsćańska hala w Chóśebuzu - wupśedana." } ``` #### unshuffled_original_dv - **Size of downloaded dataset files:** 24.91 MB - **Size of the generated dataset:** 131.63 MB - **Total amount of disk used:** 156.54 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ބ. އަތޮޅުގައި ހުޅުވަން ތައްޔާރުވަމުން އަންނަ ވައްކަރު ރިސޯޓުގައި ވަޒީފާ އަދާކުރަން ޝައުގުވެރިވާ ފަރާތްތަކަށް ކުރިމަތިލުމުގެ ފުރ..." } ``` #### unshuffled_original_el - **Size of downloaded dataset files:** 17.31 GB - **Size of the generated dataset:** 66.27 GB - **Total amount of disk used:** 83.58 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Νεκρός εντοπίστηκε μέσα στο σπίτι του στην οδό Ηρώδου Αττικού στον αριθμό 7 ο επικεφαλής του προξενικού τμήματος της Ρωσικής πρ..." } ``` #### unshuffled_original_eml - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"A séguit dal prucès ad rubutiśasiòṅ di abitànt dal pòpul ad Mikenes, Angoras 'l è finî dènt'r a 'n robot cun la tèsta dna rana ..." } ``` #### unshuffled_original_en - **Size of downloaded dataset files:** 903.83 GB - **Size of the generated dataset:** 2525.44 GB - **Total amount of disk used:** 3429.27 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Mtendere Village was inspired by the vision of Chief Napoleon Dzombe, which he shared with John Blanchard during his first visi..." } ``` #### unshuffled_original_eo - **Size of downloaded dataset files:** 117.07 MB - **Size of the generated dataset:** 314.18 MB - **Total amount of disk used:** 431.27 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ĉu ... preĝi | mediti | ricevi instigojn || kanti | muziki || informiĝi | legi | studi || prepari Diservon\\nTemas pri kolekto d..." } ``` #### unshuffled_original_es - **Size of downloaded dataset files:** 106.04 GB - **Size of the generated dataset:** 298.49 GB - **Total amount of disk used:** 404.53 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Como se librará de la celulitis en el gimnasio La piel superflua en las manos después del adelgazamiento, Los bailes fáciles pa..." } ``` #### unshuffled_original_et - **Size of downloaded dataset files:** 1.88 GB - **Size of the generated dataset:** 5.17 GB - **Total amount of disk used:** 7.06 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"MTÜ AB Video järgib oma tegevuses kodanikuühenduste eetilise tegevuse üldtunnustatud põhimõtteid, mis on lühidalt kokkuvõetud 7..." } ``` #### unshuffled_original_eu - **Size of downloaded dataset files:** 248.19 MB - **Size of the generated dataset:** 894.83 MB - **Total amount of disk used:** 1.14 GB An example of 'train' looks as follows. ``` { "id": 0, "text": "Gure jarduerek eraikuntzarekin, elkarbizitzarekin, hirigintzarekin eta ekologiarekin dute harremana, baita ideia eta konponbideak irudikatu eta garatzearekin ere, eraikuntza sektorea hobetuz, pertsonen erosotasuna eta bizi-kalitatea hobetzeko." } ``` #### unshuffled_original_fa - **Size of downloaded dataset files:** 20.96 GB - **Size of the generated dataset:** 84.21 GB - **Total amount of disk used:** 105.17 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"قـــــــــــــــــرار بود با هم کنـــــــــــــار بیایم نه اینکه از کنــــــــــــار هم رد بشیم...!!!\\nاگر روزی دلت لبریز غم بو..." } ``` #### unshuffled_original_fi - **Size of downloaded dataset files:** 9.97 GB - **Size of the generated dataset:** 28.57 GB - **Total amount of disk used:** 38.54 GB An example of 'train' looks as follows. ``` { "id": 1, "text": "Kiitos Deelle kaikesta - 1,5 viikkoa kulunut, kun Dee ei ole enää ollut omani. Reilu viikko sitten sunnuntaina vein Deen uuteen kotiinsa. Itselläni on ollut niin ristiriitaiset t..." } ``` #### unshuffled_original_fr - **Size of downloaded dataset files:** 105.32 GB - **Size of the generated dataset:** 303.19 GB - **Total amount of disk used:** 408.51 GB An example of 'train' looks as follows. ``` { "id": 0, "text": "Média de débat d'idées, de culture et de littérature. Récits, décryptages, analyses, portraits et critiques autour de la vie des idées. Magazine engagé, ouvert aux autres et au monde.. Bring up to date in french" } ``` #### unshuffled_original_frr - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Hiragana’ Practice’Sheet’1’(A -O)’ ’ Name:’________ __________________________’Section:’_______________ _’ ’ ’ ’ ’ ’ ’ ’ ’ ’ ’ ..." } ``` #### unshuffled_original_fy - **Size of downloaded dataset files:** 12.40 MB - **Size of the generated dataset:** 36.24 MB - **Total amount of disk used:** 48.64 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Nim in sêfte ride op Holmsjön, yn ien fan 'e lytse marren yn de omkriten, of nim se op avontueren lykas nonresidential. lâns Indalsälven wetter. Holm Sportklubb hawwe kano 's te huur, yn gearwurking mei de Baltyske Power konferinsje." } ``` #### unshuffled_original_ga - **Size of downloaded dataset files:** 29.27 MB - **Size of the generated dataset:** 92.37 MB - **Total amount of disk used:** 121.63 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Is fóram é seo chun plé a dhéanamh ar an leabhar atá roghnaithe do mhí na Samhna 2013 amháin. Ní féidir ach le baill chláraithe..." } ``` #### unshuffled_original_gd - **Size of downloaded dataset files:** 0.52 MB - **Size of the generated dataset:** 2.02 MB - **Total amount of disk used:** 2.55 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Zhou Yujun, a 'phàrtaidh Rùnaire Comataidh Sgìre Yanfeng ann Hengyang bhaile agus a Sgìre pàrtaidh agus an riaghaltas a' bhuidheann-riochdachaidh a 'tighinn a chèilidh air ar companaidh air Apr. 14, 2017." } ``` #### unshuffled_original_gl - **Size of downloaded dataset files:** 235.38 MB - **Size of the generated dataset:** 656.48 MB - **Total amount of disk used:** 891.87 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"O persoal de Inditex da provincia de Pontevedra segue a reclamar iguais condicións laborais no conxunto do país - CIG: Confeder..." } ``` #### unshuffled_original_gn - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.04 MB - **Total amount of disk used:** 0.05 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"º ѐÆÚÓ À Ã Ð É Æ ¾ Ä ΠÀ ¼ Æ É ÄÛ = Ü Ý\\\"Þ ß†à á â ã ä å æçè ã é ê â å àë ì æê íî é á ë ï í çì àð í Ü à ñ ê é ò ä ì\"..." } ``` #### unshuffled_original_gom - **Size of downloaded dataset files:** 0.44 MB - **Size of the generated dataset:** 2.25 MB - **Total amount of disk used:** 2.71 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"दुष्ट शीळ हें कौरवांचें । रामें सविस्तर देखूनि साचें । बोलिले वचनें जें दुर्वाचे । करी तयांचें अनुस्मरण ॥२२०॥\"..." } ``` #### unshuffled_original_gu - **Size of downloaded dataset files:** 232.02 MB - **Size of the generated dataset:** 1.09 GB - **Total amount of disk used:** 1.33 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"અધિક માસ ચાલે છે. સમગ્ર ભારતમાં અને તેમાંય ખાસ કરીને પવિત્ર કે ધાર્મિક કહેવાય છે તેવા સ્થાનક પર કથાનો દોર ચાલે છે. ઉનાળાની કાળઝ..." } ``` #### unshuffled_original_he - **Size of downloaded dataset files:** 5.66 GB - **Size of the generated dataset:** 21.11 GB - **Total amount of disk used:** 26.77 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"זקוקים לרשתות נגד יתושים? מחפשים רשת מתאימה לחלון צר וקטן? רשתות נגד יתושים אקורדיון של חברת קליר-מש הן הפתרון.\\nרשתות לחלונות ..." } ``` #### unshuffled_original_hi - **Size of downloaded dataset files:** 3.66 GB - **Size of the generated dataset:** 17.93 GB - **Total amount of disk used:** 21.59 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"'आइटम गर्ल' बनकर हिट हुई थीं राखी सावंत, आज करीना-कटरीना तक फॉलो कर रही हैं ट्रेंड नक्‍सलियों का दम निकालेगा बाइक ग्रेनेड लॉन्च..." } ``` #### unshuffled_original_hr - **Size of downloaded dataset files:** 79.42 MB - **Size of the generated dataset:** 243.83 MB - **Total amount of disk used:** 323.24 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"U raspravi je sudjelovao i HSS-ov saborski zastupnik rekavši kako poljoprivrednici ne osjete mjere o kojima ministar govori jer..." } ``` #### unshuffled_original_hsb - **Size of downloaded dataset files:** 1.39 MB - **Size of the generated dataset:** 4.49 MB - **Total amount of disk used:** 5.87 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Budyšin (SN/BŠe). Elektronikarjo mějachu lětsa cyle hinaši zazběh do swojeho wukubłanja. Wokrjesne rjemjeslnistwo bě mjenujcy w..." } ``` #### unshuffled_original_ht - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan nan..." } ``` #### unshuffled_original_hu - **Size of downloaded dataset files:** 15.69 GB - **Size of the generated dataset:** 43.07 GB - **Total amount of disk used:** 58.77 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"monster - Amatőr, házi szex videók és kezdő csjaok pornó filmjei. - Free amateur, home made sex videos and online porn movies. ..." } ``` #### unshuffled_original_hy - **Size of downloaded dataset files:** 897.36 MB - **Size of the generated dataset:** 3.94 GB - **Total amount of disk used:** 4.84 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Արցախի Հանրապետության հռչակման 26-րդ տարեդարձի կապակցությամբ Շուշիի Արվեստի կենտրոնում կազմակերպվել է մոսկվաբնակ նկարիչներ՝ հայ..." } ``` #### unshuffled_original_ia - **Size of downloaded dataset files:** 0.08 MB - **Size of the generated dataset:** 0.69 MB - **Total amount of disk used:** 0.78 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha ha h..." } ``` #### unshuffled_original_id - **Size of downloaded dataset files:** 10.60 GB - **Size of the generated dataset:** 32.32 GB - **Total amount of disk used:** 42.91 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Perihal dari itu, kalau kunci hal yang demikian hilang, pemilik wajib melapor ke bengkel sah untuk dibuatkan kunci baru dengan ..." } ``` #### unshuffled_original_ie - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Plastic Yo Yo Metal Yo Yos Wooden Yo Yo Keychain Yo Yo Translucent Yo Yo Light Up Yo Yo Globe Yo Yo Stress Reliever Yo Yo Jellyfish Yo Yo Sports Ball Yo Yo Sound Yo Yo Miniature Yo Yo Promotional Yo Yo Novelty Yo Yo Video Game Yo Yo ECO Recycled Yo Yo" } ``` #### unshuffled_original_ilo - **Size of downloaded dataset files:** 0.27 MB - **Size of the generated dataset:** 0.92 MB - **Total amount of disk used:** 1.20 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Segun ken ni Ping-ay, ti yellow corn ti maysa kadagiti nadakamat a liberalized agricultural commodity iti daytoy a free trade k..." } ``` #### unshuffled_original_io - **Size of downloaded dataset files:** 0.04 MB - **Size of the generated dataset:** 0.16 MB - **Total amount of disk used:** 0.20 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Chekia esas parlamentala republiko. La chefo di stato esas la prezidanto. Til 2013 lu elektesis dal parlamento. Pos ta yaro, ol..." } ``` #### unshuffled_original_is - **Size of downloaded dataset files:** 533.03 MB - **Size of the generated dataset:** 1.52 GB - **Total amount of disk used:** 2.06 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Eyjar.net - upplýsinga- og fréttamiðill um Vestmannaeyjar - Fréttir - Nái núverandi stefna stjórnvalda fram að ganga mun það va..." } ``` #### unshuffled_original_it - **Size of downloaded dataset files:** 52.16 GB - **Size of the generated dataset:** 147.38 GB - **Total amount of disk used:** 199.54 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Jaundice - causes, treatment & pathology massaggio a osteochondrosis dellindizio di una controindicazione\\nTrattamento su un co..." } ``` #### unshuffled_original_ja - **Size of downloaded dataset files:** 79.56 GB - **Size of the generated dataset:** 232.22 GB - **Total amount of disk used:** 311.78 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"神社などへ一緒に同行して、様々な角度のショットで家族写真やお子様の写真を撮影致します！お好みに合わせて様々な写真を取ることができますので、その場でカメラマンへのリクエストも可能です！お子様の晴れ姿を、緊張していない自然な笑顔で残しませんか？\\n※七五三の..." } ``` #### unshuffled_original_jbo - **Size of downloaded dataset files:** 0.21 MB - **Size of the generated dataset:** 0.77 MB - **Total amount of disk used:** 0.98 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "ni'o 23 la cimast. cu 23moi djedi fi'o masti la cimast. noi ke'a cu cimoi masti .i 22 la cimast. cu purlamdei .ije 24 la cimast. cu bavlamdei" } ``` #### unshuffled_original_jv - **Size of downloaded dataset files:** 0.22 MB - **Size of the generated dataset:** 0.69 MB - **Total amount of disk used:** 0.91 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"José Mourinho (diwaca: [ʒuˈzɛ moˈɾiɲu]; lair ing Setubal, Portugal, 26 Januari 1963; umur 55 taun) iku salah siji pelatih bal k..." } ``` #### unshuffled_original_ka - **Size of downloaded dataset files:** 680.74 MB - **Size of the generated dataset:** 3.77 GB - **Total amount of disk used:** 4.45 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"წამიყვანე შენთან ერთად (ქართულად) / Возьми меня с собой (картулад) / (რუსული სერიალები ქართულად) (რუსების პორნო ონლაინში) (ruse..." } ``` #### unshuffled_original_kk - **Size of downloaded dataset files:** 615.06 MB - **Size of the generated dataset:** 2.83 GB - **Total amount of disk used:** 3.45 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Түлкібас ауданында «Латын негізді әліпби мен емле ережесі туралы насихат» жобасының тобы семинар өткізді\\nЕлорданың «Қазақстан»..." } ``` #### unshuffled_original_km - **Size of downloaded dataset files:** 193.28 MB - **Size of the generated dataset:** 1.10 GB - **Total amount of disk used:** 1.30 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ខ្សឹបដាក់ត្រចៀក៖ លោក សួស សុផានិត នាយផ្នែករដ្ឋបាលព្រៃឈើ ស្រុកភ្នំក្រវាញ់ ដែលទើបឡើងកាន់តំណែងថ្មី បើកដៃឲ្យឈ្នួញ ប្រព្រឹត្តបទល្មើស ..." } ``` #### unshuffled_original_kn - **Size of downloaded dataset files:** 342.15 MB - **Size of the generated dataset:** 1.76 GB - **Total amount of disk used:** 2.11 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ರಾಷ್ಟ್ರಪತಿ ಪ್ರಣಬ್ ಮುಖರ್ಜಿಯಿಂದ ಪದ್ಮ ಪ್ರಶಸ್ತಿ ಪ್ರದಾನ | President Pranab Mukherjee Confers Padma Awards | Photo Gallery on Kannada..." } ``` #### unshuffled_original_ko - **Size of downloaded dataset files:** 8.81 GB - **Size of the generated dataset:** 25.29 GB - **Total amount of disk used:** 34.10 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"CIA 프로젝트에서는 데이터베이스로 들어오는 요청을 중간에 수집(Sniffing)하고 수집한 데이터를 분석(Parsing)하여 그로 인한 결과를 판단하여 알릴 수 있는 시스템(Push Service)이 필요하다. 그리고 연구를 ..." } ``` #### unshuffled_original_krc - **Size of downloaded dataset files:** 0.66 MB - **Size of the generated dataset:** 2.68 MB - **Total amount of disk used:** 3.34 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Шамханланы, Бийлени къаршысына ябушуп, Батыр уланларыбызны къоллары булан «ортакъ ожакъ» къургъанбыз. Шо иш уллу зараллы иш бол..." } ``` #### unshuffled_original_ku - **Size of downloaded dataset files:** 33.38 MB - **Size of the generated dataset:** 99.06 MB - **Total amount of disk used:** 132.44 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Me di 114 bernameyên xwe yên berê da perçeyên ji berhemên zanyarî yên kurdzanên mezin bi wergera kurdî da ...\\nMe di 114 bernam..." } ``` #### unshuffled_original_kv - **Size of downloaded dataset files:** 0.40 MB - **Size of the generated dataset:** 2.38 MB - **Total amount of disk used:** 2.78 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Коми кытшыслӧн ыджытжык тор вӧр увтын куйлӧ, сійӧн и фаунасӧ татӧн аркмӧтӧны вӧрын олісь подаэз. Ассямаӧн лоӧ сія, мый кытшас с..." } ``` #### unshuffled_original_kw - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.04 MB - **Total amount of disk used:** 0.05 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼Pray without ceasing🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏🏼🙏..." } ``` #### unshuffled_original_ky - **Size of downloaded dataset files:** 152.64 MB - **Size of the generated dataset:** 630.79 MB - **Total amount of disk used:** 783.43 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Turmush: Бишкек шаардык кеңешинин кезексиз отурумунда мэрге ишенбөөчүлүк көрсөтүү маселеси каралат, - депутат Т.Сагынов\\nБишкек..." } ``` #### unshuffled_original_la - **Size of downloaded dataset files:** 5.46 MB - **Size of the generated dataset:** 27.80 MB - **Total amount of disk used:** 33.26 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Hæ sunt generationes Noë: Noë vir justus atque perfectus fuit in generationibus suis; cum Deo ambulavit.\\nEcce ego adducam aqua..." } ``` #### unshuffled_original_lb - **Size of downloaded dataset files:** 10.73 MB - **Size of the generated dataset:** 30.60 MB - **Total amount of disk used:** 41.32 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Während dem Gaardefestival \\\"Ambiance Jardins\\\" vum 15. bis de 17. Mee huet den SNJ nees zesumme mam Groupe Animateur en Inform..." } ``` #### unshuffled_original_lez - **Size of downloaded dataset files:** 0.83 MB - **Size of the generated dataset:** 3.38 MB - **Total amount of disk used:** 4.20 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Ахцегь хуьр, виридалай ч1ехи лезги хуьрерикая я. Ам Урусатдин виридалай къиблепатавай хуьрерикай я. Ин хуьр...\"..." } ``` #### unshuffled_original_li - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.03 MB - **Total amount of disk used:** 0.04 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"'t Good Goedenraad aan de Ezerbaek besjteit oet 'n kesjtièl mèt gesjlote haof en 'n park van 26 hectare. Hie in sjtoon väól beu..." } ``` #### unshuffled_original_lmo - **Size of downloaded dataset files:** 0.10 MB - **Size of the generated dataset:** 0.47 MB - **Total amount of disk used:** 0.58 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Serét (en tortonés: Sregh; en piemontés: Srèj) l'è 'n cümü italià, de la regiù del Piemónt, en Pruvìncia de Alessandria. El g'h..." } ``` #### unshuffled_original_lo - **Size of downloaded dataset files:** 33.92 MB - **Size of the generated dataset:** 182.36 MB - **Total amount of disk used:** 216.28 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ຜູ້ພິພາກສາ ປະຈຳເຂດ ສຫລ ທ່ານນຶ່ງ ຕັດສິນວ່າ ໂຄງການເກັບກຳຂໍ້ມູນ ທາງໂທລະສັບ ຂອງອົງການ ຄວາມໝັ້ນຄົງແຫ່ງຊາດ ແມ່ນຖືກຕ້ອງ ຕາມກົດໝາຍ.\\nກະ..." } ``` #### unshuffled_original_lrc - **Size of downloaded dataset files:** 0.02 MB - **Size of the generated dataset:** 0.07 MB - **Total amount of disk used:** 0.09 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"آرلینگتون یئ گئل د شأریا ڤولاتچە ڤیرجینیا و یئ گئل د شأریا ڤولات ڤولاتچە یا یأکاگئرئتە ئمریکاە. ئی شأر دویومی کألوٙن شأر د راسا..." } ``` #### unshuffled_original_lt - **Size of downloaded dataset files:** 3.44 GB - **Size of the generated dataset:** 9.45 GB - **Total amount of disk used:** 12.89 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Čir vir vir pavasaris! Čia čia čia… dalinamės labai simpatiška video pamokėle, kurią pristato ab888art galerija.\\nBe galo papra..." } ``` #### unshuffled_original_lv - **Size of downloaded dataset files:** 1.49 GB - **Size of the generated dataset:** 4.27 GB - **Total amount of disk used:** 5.75 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Dekoratīvi sliekšņi MITSUBISHI OUTLANDER 2007, izgatavoti no ovālas formas, pulētas nerūsējošā tērauda caurules...\\ndažādas tūn..." } ``` #### unshuffled_original_mai - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.33 MB - **Total amount of disk used:** 0.34 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"१ · २ · ३ · ४ · ५ · ६ · ७ · ८ · ९ · १० · ११ · १२ · १३ · १४ · १५ · १६ · १७ · १८ · १९ · २० · २१ · २२ · २३ · २४ · २५ · २६ · २७ · २..." } ``` #### unshuffled_original_mg - **Size of downloaded dataset files:** 6.22 MB - **Size of the generated dataset:** 21.79 MB - **Total amount of disk used:** 28.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Nanamboatra taratasy apetaka sy soso-kevitra ho an'ny olona te-hanatevin-daharana ity fihetsiketsehana ity i Anocrena.\\nNosorat..." } ``` #### unshuffled_original_mhr - **Size of downloaded dataset files:** 1.84 MB - **Size of the generated dataset:** 7.55 MB - **Total amount of disk used:** 9.38 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Акрет жап годым Уганда кундемым Пигмей племена- влак айлен шогеныт. мемнан эран 1 курым гыч Банту племена влакат тиде кундемышк..." } ``` #### unshuffled_original_min - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.63 MB - **Total amount of disk used:** 0.64 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ‏‏‎ ..." } ``` #### unshuffled_original_mk - **Size of downloaded dataset files:** 508.24 MB - **Size of the generated dataset:** 2.20 GB - **Total amount of disk used:** 2.71 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"„Филм плус“ е насловен првиот филмски месечник во Македонија, чиј прв број ќе биде промовиран вечер во „Менада“. Новото македон..." } ``` #### unshuffled_original_ml - **Size of downloaded dataset files:** 938.69 MB - **Size of the generated dataset:** 5.24 GB - **Total amount of disk used:** 6.18 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"സ്ത്രീ പ്രവേശനം സര്‍ക്കാര്‍ പൂര്‍ണമായും അംഗീകരിക്കുന്നുവെന്നും ശബരിമലയുടെ സുരക്ഷയില്‍ ഇടപെടുമെന്നും സര്‍ക്കാര്‍ ഹൈക്കോടതിയില്‍\\..." } ``` #### unshuffled_original_mn - **Size of downloaded dataset files:** 472.36 MB - **Size of the generated dataset:** 2.33 GB - **Total amount of disk used:** 2.81 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Монгол улс, Улаанбаатар хот - 14191 Энхтайваны өргөн чөлөө - 10, Багш хөгжлийн ордон, Багшийн мэргэжил дээшлүүлэх институт\\nБаг..." } ``` #### unshuffled_original_mr - **Size of downloaded dataset files:** 525.31 MB - **Size of the generated dataset:** 2.82 GB - **Total amount of disk used:** 3.34 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Home / motivational marathi story / उद्योजकता (Entrepreneurship) / यांना हे जमलय, तर आपल्याला का नाही जमणार ?\\nयापैकी कोणाचीही ..." } ``` #### unshuffled_original_mrj - **Size of downloaded dataset files:** 0.30 MB - **Size of the generated dataset:** 1.16 MB - **Total amount of disk used:** 1.47 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Лӹпӹвлӓ (латинлӓ Lepidoptera ; алыкмарла лыве-влак) — капшангывлӓ йыхыш пырышы сӱмӓн нӹл шылдыран капшангывлӓ. Цилӓжӹ 180000 тӹ..." } ``` #### unshuffled_original_ms - **Size of downloaded dataset files:** 28.46 MB - **Size of the generated dataset:** 122.33 MB - **Total amount of disk used:** 150.79 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Sanad pertama daripada Zuhair bin Harb daripada ‘Affan daripada Hammad daripada Thabit daripada Anas.\\nSanad kedua daripada ‘Ab..." } ``` #### unshuffled_original_mt - **Size of downloaded dataset files:** 7.53 MB - **Size of the generated dataset:** 24.47 MB - **Total amount of disk used:** 32.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "tibgħat il-kawża lura lill-Qorti Ġenerali għall-annullament jew għat-tnaqqis tal-penalità imposta mill-Kummissjoni bid-deċiżjoni inizjali kif emendata bid-deċiżjoni ta’ rettifika;" } ``` #### unshuffled_original_mwl - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Deciplina social i outónoma que angloba atebidades de ouserbaçon, de análeze, de çcriçon, cumparaçon, de sistematizaçon i de sp..." } ``` #### unshuffled_original_my - **Size of downloaded dataset files:** 369.85 MB - **Size of the generated dataset:** 2.02 GB - **Total amount of disk used:** 2.39 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ျမ၀တီ - ရန္ကုန္တိုင္းေဒသႀကီး ေျမာက္ဥကၠလာပႏွင္႕ ဗဟန္းၿမိဳ႔နယ္ မေကြးတိုင္း ေဒသႀကီး ပခုကၠဴၿမိဳ႔နယ္တို႔၌ ျမန္မာ႕တပ္မေတာ္အား ေထာက္ခံ..." } ``` #### unshuffled_original_myv - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"2018 иень умарьковонь 6-це чистэ сась паро куля! Россиянь культурань Министерствась макссь невтемань конёв (прокатной удостовер..." } ``` #### unshuffled_original_mzn - **Size of downloaded dataset files:** 0.18 MB - **Size of the generated dataset:** 0.72 MB - **Total amount of disk used:** 0.90 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"قرآن یا قوران اسلام ِآسمونی کتاب هسته. مسلمونون گانّّه قرآن ره خدا، وحی جه برسنی‌یه، «محمد معجزه» هسته و ثقلین حدیث دله ونه خَو..." } ``` #### unshuffled_original_nah - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "In mācuīlpōhualxihuitl VI (inic chicuacē) in mācuīlpōhualli xiuhitl cāhuitl īhuīcpa 501 xihuitl oc 600 xihuitl." } ``` #### unshuffled_original_nap - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.02 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ò AUDIT í Ç è î ÿ å å 30 ò ÿ ÿ é, õ ñ ì ÿ, ê ã- ò à ì. å â å í ç â à à é ñ è å é ó ó ë. å å å û è å î é è à. à è à AUDIT 1-7 â ..." } ``` #### unshuffled_original_nds - **Size of downloaded dataset files:** 6.74 MB - **Size of the generated dataset:** 18.23 MB - **Total amount of disk used:** 24.99 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Dor kann sik vun nu af an de hele plattdüütsche Welt – vun Niebüll bit New York, vun Helgoland bit Honolulu – drapen. Allens, w..." } ``` #### unshuffled_original_ne - **Size of downloaded dataset files:** 355.29 MB - **Size of the generated dataset:** 1.87 GB - **Total amount of disk used:** 2.22 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"बर्दिबास नगरपालिकाको तेस्रो नगर परिषदबाट पारित आ.व.२०७३।७४ को संशोधित र २०७४।७५ को प्रस्तावित नीति, कार्यक्रम तथा बजेट\\nअार्थिक..." } ``` #### unshuffled_original_new - **Size of downloaded dataset files:** 1.03 MB - **Size of the generated dataset:** 5.77 MB - **Total amount of disk used:** 6.79 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"थ्व शहरयागु अक्षांश ३४.७००१६४ उत्तर व देशान्तर ८६.३७६४६९ पश्चिम खः (34.700164° N 86.376469° W)। थ्व थासे ७२२६७३२ वर्ग मिटर (२.७..." } ``` #### unshuffled_original_nl - **Size of downloaded dataset files:** 29.35 GB - **Size of the generated dataset:** 83.23 GB - **Total amount of disk used:** 112.58 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Op vrijdag 31 augustus wordt het nieuwe studiejaar van de masteropleiding architectuur geopend met een dagexcursie naar Venlo.\\..." } ``` #### unshuffled_original_nn - **Size of downloaded dataset files:** 32.86 MB - **Size of the generated dataset:** 90.84 MB - **Total amount of disk used:** 123.70 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "Planomtale krav til innhald Bakgrunn: Spørsmål frå fleire kommunar om kva ein planomtale/planbeskrivelse bør innehalde Fylkeskommunen og fylkesmannen har i ein del saker reist motsegn på formelt grunnlag" } ``` #### unshuffled_original_no - **Size of downloaded dataset files:** 3.11 GB - **Size of the generated dataset:** 8.65 GB - **Total amount of disk used:** 11.76 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Ytterligere aktører i primærhelsetjenesten og andre NHS-virksomheter ble infisert, inkludert legekontor.Læreren vår er så attra..." } ``` #### unshuffled_original_oc - **Size of downloaded dataset files:** 1.57 MB - **Size of the generated dataset:** 6.12 MB - **Total amount of disk used:** 7.71 MB An example of 'train' looks as follows. ``` { "id": 1, "text": ".рф (rf, còdi punycode: .xn--p1ai)[1] es lo nom de domeni en rus per Russia. Foguèt activat lo 12 de mai de 2010. Lo còdi latin es .ru." } ``` #### unshuffled_original_or - **Size of downloaded dataset files:** 49.84 MB - **Size of the generated dataset:** 260.15 MB - **Total amount of disk used:** 309.99 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ଭୁବନେଶ୍ୱର, ୨୭/୧– (ଓଡ଼ିଆ ପୁଅ) ସିପିଆଇ ଜାତୀୟ ପରିଷଦର ଆହ୍ୱାନକ୍ରମେ ଗତକାଲି ଜାନୁୟାରୀ ୨୬ ସାଧାରଣତନ୍ତ୍ର ଦିବସକୁ ଦେଶ ବ୍ୟାପୀ ସମ୍ବିଧାନ ସୁରକ୍ଷା ..." } ``` #### unshuffled_original_os - **Size of downloaded dataset files:** 3.09 MB - **Size of the generated dataset:** 12.90 MB - **Total amount of disk used:** 15.99 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"1. Лæппу æмæ чызг казрæдзийы зæрдæмæ куы фæцæуынц æмæ, куы сфæнд кæнынц сæ цард баиу кæнын, уæд лæппу бар ракуры чызгæй, цæмæй ..." } ``` #### unshuffled_original_pa - **Size of downloaded dataset files:** 164.21 MB - **Size of the generated dataset:** 801.16 MB - **Total amount of disk used:** 965.37 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ਰਜਿ: ਨੰ: PB/JL-138/2018-20 ਜਿਲਦ 63, ਬਾਨੀ ਸੰਪਾਦਕ (ਸਵ:) ਡਾ: ਸਾਧੂ ਸਿੰਘ ਹਮਦਰਦ ਫ਼ੋਨ : 0181-2455961-62-63, 5032400, ਫੈਕਸ : 2455960, 2..." } ``` #### unshuffled_original_pam - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Áku pu i Anak ning Aláya at ngeni ipákit kó kékayu ngan nûng makanánu lang susúlat détinang kulit a mágkas. Lauan ya ing tarátu..." } ``` #### unshuffled_original_pl - **Size of downloaded dataset files:** 42.88 GB - **Size of the generated dataset:** 117.12 GB - **Total amount of disk used:** 160.01 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"System informatyczny - Załącznik nr 1 do zarządzenia Wójta Gminy Podegrodzie Nr 530/2013 z dnia 27 maja 2013 r\\nSystem informat..." } ``` #### unshuffled_original_pms - **Size of downloaded dataset files:** 0.75 MB - **Size of the generated dataset:** 2.15 MB - **Total amount of disk used:** 2.92 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Louvigné-du-Désert a l'é na comun-a fransèisa ant la region aministrativa dla Brëtagna, ant ël dipartiment d'Ille-et-Vilaine. A..." } ``` #### unshuffled_original_pnb - **Size of downloaded dataset files:** 3.22 MB - **Size of the generated dataset:** 12.04 MB - **Total amount of disk used:** 15.26 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ایہ فائل Wikimedia Commons توں اے تے دوجیاں ویونتاں تے وی ورتی جاےکدی اے۔ گل بات اس دے فائل گل بات صفہ تے تھلے دتی گئی۔\"..." } ``` #### unshuffled_original_ps - **Size of downloaded dataset files:** 103.66 MB - **Size of the generated dataset:** 379.51 MB - **Total amount of disk used:** 483.17 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Many people usually use the time period ‘business to business (B2B) advertising,’ however most of them do not know precisely wh..." } ``` #### unshuffled_original_pt - **Size of downloaded dataset files:** 47.26 GB - **Size of the generated dataset:** 132.64 GB - **Total amount of disk used:** 179.89 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Você pode estar lendo este texto no sofá, levantar pra pegar uma breja na geladeira, dar uma cagada e sentar novamente, sem int..." } ``` #### unshuffled_original_qu - **Size of downloaded dataset files:** 0.02 MB - **Size of the generated dataset:** 0.08 MB - **Total amount of disk used:** 0.10 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Warayu wichay (kastilla simipi: Ascensión de Guarayos) nisqaqa Buliwya mama llaqtapi, Santa Krus suyupi, huk llaqtam, Warayu pruwinsyap uma llaqtanmi." } ``` #### unshuffled_original_rm - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"practicists agrars / practicistas agraras AFP pon far ina furmaziun da basa scursanida per cuntanscher in attestat federal da q..." } ``` #### unshuffled_original_ro - **Size of downloaded dataset files:** 9.53 GB - **Size of the generated dataset:** 26.87 GB - **Total amount of disk used:** 36.40 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"“În viață, oportunitatea nu este totul. Cine atrage Lumina, cineva bun în umbră. Timpul ne creează.” maestru\\nLyn.Evans: Ce mar..." } ``` #### unshuffled_original_ru - **Size of downloaded dataset files:** 319.76 GB - **Size of the generated dataset:** 1241.63 GB - **Total amount of disk used:** 1561.38 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Доступ к данному профилю для публичного просмотра закрыт администрацией сайта - профиль находится на модерации.\\nРазработчикам ..." } ``` #### unshuffled_original_sa - **Size of downloaded dataset files:** 17.52 MB - **Size of the generated dataset:** 97.06 MB - **Total amount of disk used:** 114.58 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"अनिरुद्धनगरे क्रीडिता रामलीला सम्‍प्रति समाप्‍ता अस्ति । तस्‍य कानिचन् चित्राणि पूर्वमेव प्रकाशितानि सन्ति । द्वौ चलचित्रौ अपि ..." } ``` #### unshuffled_original_sah - **Size of downloaded dataset files:** 9.08 MB - **Size of the generated dataset:** 43.82 MB - **Total amount of disk used:** 52.90 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████..." } ``` #### unshuffled_original_scn - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` { "id": 0, "text": "La gilusìa è nu sintimentu dulurusu ca nasci d'un disideriu di pussessu sclusivu ntê cunfrunti dâ pirsuna amata e dû timuri, dû suspettu o dâ cirtizza dâ sò nfidiltati." } ``` #### unshuffled_original_sd - **Size of downloaded dataset files:** 90.62 MB - **Size of the generated dataset:** 364.25 MB - **Total amount of disk used:** 454.88 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"هر ڪو ڄاڻي ٿو ته جڏهن توهان هڪ وڏي خريد ڪرڻ چاهيون ٿا, توهان پڄي ضروري حڪم ۾ ان جي ڪم ڪرڻ جي هٿ ۾ لاڳاپو ڪيو آهي. جي شيء آهي ته..." } ``` #### unshuffled_original_sh - **Size of downloaded dataset files:** 3.46 MB - **Size of the generated dataset:** 25.84 MB - **Total amount of disk used:** 29.30 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Opština Gornja Radgona se nalazi u sjeveroistočnoj Sloveniji i graniči s susjednom Austriji duž rijeke Mure. Sa tridesetim nase..." } ``` #### unshuffled_original_si - **Size of downloaded dataset files:** 310.93 MB - **Size of the generated dataset:** 1.47 GB - **Total amount of disk used:** 1.78 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"ලාංකීය සිතිවිලි සිංහල බ්ලොග් කියවනය කොත්තු සින්ඩිය ලංකා Blogger හත්මාළුව ලංකා බ්ලොග් කියවනය මාතලන්ගේ සින්ඩිය මොබයිල්lk\\nඅවකාශය ..." } ``` #### unshuffled_original_sk - **Size of downloaded dataset files:** 3.71 GB - **Size of the generated dataset:** 9.81 GB - **Total amount of disk used:** 13.52 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Aktivity | Agentúra podporovaného zamestnávania | vzdelávanie pre klientov, vzdelávanie pre odborníkov, kurzy\\nŠpecializované k..." } ``` #### unshuffled_original_sl - **Size of downloaded dataset files:** 956.20 MB - **Size of the generated dataset:** 2.68 GB - **Total amount of disk used:** 3.63 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Če Creatures, ki je želel, da pridejo na čas, predvsem je povedlo – razlikuje od ljubosumja začel grizenja kolen (ali zadnjica)..." } ``` #### unshuffled_original_so - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.06 MB - **Total amount of disk used:** 0.06 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"тттттттттттттттттттттттттттттттт тттттттттттттттттттттттттттттттт тттттттттттттттттттттттттттттттт ттттттттттттттттуууууууууууу..." } ``` #### unshuffled_original_sq - **Size of downloaded dataset files:** 861.84 MB - **Size of the generated dataset:** 2.44 GB - **Total amount of disk used:** 3.30 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Çfarë do të më pëlqente tek një femër ose çfarë do të më shndërronte në një shpërthim drite? – Albert Vataj\\nTë gjithëve një zo..." } ``` #### unshuffled_original_sr - **Size of downloaded dataset files:** 1.08 GB - **Size of the generated dataset:** 4.13 GB - **Total amount of disk used:** 5.21 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Корисни савети за сваки дан. На сајту су разне категорије, као што су љепота, мода, кување и поправка властитим рукама.\\nШколск..." } ``` #### unshuffled_original_su - **Size of downloaded dataset files:** 0.06 MB - **Size of the generated dataset:** 0.23 MB - **Total amount of disk used:** 0.28 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Kartu krédit nyaéta \"duit plastik\" anu dikaluarkeun ku bank pikeun alat pambayaran di tempat-tempat nu tangtu samisal jiga di hotél, réstoran, tempat rékréasi jeung sajabana.[1]" } ``` #### unshuffled_original_sv - **Size of downloaded dataset files:** 17.18 GB - **Size of the generated dataset:** 47.00 GB - **Total amount of disk used:** 64.18 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"1783 är ett viktigt årtal i den nya tidens historia. Det året slöts en fred i Paris och därmed blev de 13 brittiska kolonierna ..." } ``` #### unshuffled_original_sw - **Size of downloaded dataset files:** 3.71 MB - **Size of the generated dataset:** 14.07 MB - **Total amount of disk used:** 17.78 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Miripuko hiyo inakuja mwanzoni mwa Wiki Takatifu kuelekea Pasaka na ikiwa ni wiki chache tu kabla ya Papa Francis kuanza ziara yake katika nchi hiyo yenye idadi kubwa kabisa ya watu katika ulimwengu wa nchi za Kiarabu." } ``` #### unshuffled_original_ta - **Size of downloaded dataset files:** 1.74 GB - **Size of the generated dataset:** 9.93 GB - **Total amount of disk used:** 11.67 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"பொழுது சாய்ந்து வெகு நேரமாகிவிட்டது. கூலி வேலைக்குப் போயிருந்த 'சித்தாள் ' பெண்கள் எல்லோரும் வீடு திரும்பி விட்டார்கள். இன்னும்..." } ``` #### unshuffled_original_te - **Size of downloaded dataset files:** 522.47 MB - **Size of the generated dataset:** 2.61 GB - **Total amount of disk used:** 3.13 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"హర్యానాలో టోల్ దగ్గర సిబ్బంది.. స్థానిక ప్రజలు కొట్టుకున్నారు. కర్నాల్ అనే గ్రామానికి సమీపంలో టోల్ గేట్ ఉంది. అయితే సాధారణంగా స..." } ``` #### unshuffled_original_tg - **Size of downloaded dataset files:** 90.97 MB - **Size of the generated dataset:** 397.43 MB - **Total amount of disk used:** 488.41 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Ҳумайро гуфтааст, мухолифи низом аст, низоме, ки дар Тоҷикистон вуҷуд дорад. Ба ин маънӣ, худро мухолифи давлату ҳукумати Тоҷик..." } ``` #### unshuffled_original_th - **Size of downloaded dataset files:** 7.38 GB - **Size of the generated dataset:** 38.29 GB - **Total amount of disk used:** 45.67 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ฟันที่แลดูขาวสะอาดไม่มีเศษอาหารติดอยู่ เหงือกสีชมพู ไม่เจ็บ หรือมีเลือดออกเวลาแปรงฟันหรือขัดฟัน ไม่มีปัญหาเรื่องกลิ่นปาก ทำให้ก..." } ``` #### unshuffled_original_tk - **Size of downloaded dataset files:** 2.96 MB - **Size of the generated dataset:** 10.66 MB - **Total amount of disk used:** 13.62 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"Türkmenistanyň Prezidenti agyr atletika boýunça dünýä çempionatyna taýýarlyk işleriniň barşy bilen tanyşdy\\nHalallykdan kemal t..." } ``` #### unshuffled_original_tl - **Size of downloaded dataset files:** 204.89 MB - **Size of the generated dataset:** 606.30 MB - **Total amount of disk used:** 811.19 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"“Gusto ko manawagan sa mga Unit Head ng Chanel 2 Salve. Kasi napapansin ko iyon mga alaga ko ang taping halos once a week lang,..." } ``` #### unshuffled_original_tr - **Size of downloaded dataset files:** 21.96 GB - **Size of the generated dataset:** 63.58 GB - **Total amount of disk used:** 85.54 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Son yıllarda görülen ay tutulmalarına göre daha etkili olacağı söylenen Kanlı veya Kırmızı Ay Tutulmasına saatler kaldı. Bu akş..." } ``` #### unshuffled_original_tt - **Size of downloaded dataset files:** 151.06 MB - **Size of the generated dataset:** 703.42 MB - **Total amount of disk used:** 854.47 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"\\\"Иремнең вафатына 40 көн узгач, Алмаз да безнең өйгә кереп үлде\\\". Арчада 35 яшьлек ир өстенә кондызлар ега башлаган агач төшк..." } ``` #### unshuffled_original_tyv - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.01 MB - **Total amount of disk used:** 0.01 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Экии, хүндүлуг аалчылар болгаш тыва дылдың деткикчилери! Тыва дылдың болгаш чогаалдың ховар бир башкызынга, Менги Ооржакка, ажы..." } ``` #### unshuffled_original_ug - **Size of downloaded dataset files:** 27.92 MB - **Size of the generated dataset:** 127.42 MB - **Total amount of disk used:** 155.35 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"زاڭ-ءتۇزىم | عىلىم-تەحنيكا | ءتىل-ادەبيەت | تۇرمىس | دەنە تاربيە | ساياحات-ورتا | سۋرەتتى حابار | سىر سۇحبات | ارناۋلى تاقىرىپ ..." } ``` #### unshuffled_original_uk - **Size of downloaded dataset files:** 14.42 GB - **Size of the generated dataset:** 56.44 GB - **Total amount of disk used:** 70.86 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Про надання роз'яснення (щодо форми письмового зобов'язання громадян про зворотне ввезення/вивезення товарів), Державна митна с..." } ``` #### unshuffled_original_ur - **Size of downloaded dataset files:** 712.61 MB - **Size of the generated dataset:** 2.80 GB - **Total amount of disk used:** 3.51 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"آئیے اہم اسلامی کتب کو یونیکوڈ میں انٹرنیٹ پر پیش کرنے کے لئے مل جل کر آن لائن ٹائپنگ کریں۔ محدث ٹائپنگ پراجیکٹ کے ذریعے آپ روز..." } ``` #### unshuffled_original_uz - **Size of downloaded dataset files:** 5.78 MB - **Size of the generated dataset:** 21.46 MB - **Total amount of disk used:** 27.24 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Qurama tog'lari tizmasining Toshkentdan 154 km uzoqlikdagi Toshkent-Ush yo'li yeqasidaxushmanzara tabiat qo'ynida joylashgan maydoni 30 ga.\nBolalarni sog'lomlashtirish oromgohi Bo'stonliq tumani Oqtosh muntaqasining soy-salqin gushasida joylashgan." } ``` #### unshuffled_original_vec - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.02 MB - **Total amount of disk used:** 0.03 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Par ogni pónto, ła derivada ła xe ła pendensa de ła reta tangente a ła curva de ła funsion f. Ła reta de cołor róso l'è senpre ..." } ``` #### unshuffled_original_vi - **Size of downloaded dataset files:** 21.50 GB - **Size of the generated dataset:** 72.23 GB - **Total amount of disk used:** 93.73 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Canh chua cá bông lau không chỉ là món ăn giải nhiệt, thanh mát ngày hè mà còn là món siêu bổ dưỡng, rất tốt cho người gầy ốm. ..." } ``` #### unshuffled_original_vo - **Size of downloaded dataset files:** 0.30 MB - **Size of the generated dataset:** 2.12 MB - **Total amount of disk used:** 2.42 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Sarniguet binon zif in ziläk: Hautes-Pyrénées, in topäd: Midi-Pyrénées, in Fransän. Sarniguet topon videtü 43°19’ 7’’ N e lunetü 0°5’ 19’’ L." } ``` #### unshuffled_original_wa - **Size of downloaded dataset files:** 0.09 MB - **Size of the generated dataset:** 0.29 MB - **Total amount of disk used:** 0.38 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "Cisse pådje ci n' est co k' on djermon, dj' ô bén k' el pådje est djusse sibåtcheye, eyet co trop tene; et s' divreut ele ecråxhî ene miete." } ``` #### unshuffled_original_war - **Size of downloaded dataset files:** 0.64 MB - **Size of the generated dataset:** 2.68 MB - **Total amount of disk used:** 3.32 MB An example of 'train' looks as follows. ``` { "id": 1, "text": "An Honce amo in usa ka baryo ngan munisipalidad ha distrito han Rožňava ha rehiyon han Košice ha nasod han Slovakia.\nAn Rumegies amo in usa ka komyun ha departamento han Nord ngan ha rehiyon han Nord-Pas-de-Calais ha nasod han Fransya." } ``` #### unshuffled_original_wuu - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.12 MB - **Total amount of disk used:** 0.13 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"伊春元旦天气 伊春腊八天气 伊春春节天气 伊春情人节天气 伊春元宵节天气 伊春愚人节天气 伊春清明节天气 伊春劳动节天气 伊春母亲节天气 伊春端午节天气 伊春七夕节天气 伊春教师节天气 伊春中秋节天气 伊春国庆节天气 伊春重阳节天气 伊春万圣节天气 伊春..." } ``` #### unshuffled_original_xal - **Size of downloaded dataset files:** 0.03 MB - **Size of the generated dataset:** 0.12 MB - **Total amount of disk used:** 0.15 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Арнгудин Орн гисн Европд бәәдг һазр. 2007 җилин тooһaр эн орн нутгт 3,600,523 әмтн бәәдг билә. Арнгудин Орнин хотл балһсна нерн..." } ``` #### unshuffled_original_xmf - **Size of downloaded dataset files:** 1.05 MB - **Size of the generated dataset:** 6.12 MB - **Total amount of disk used:** 7.17 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"მოჩამილი ტექსტი წჷმორინელი რე Creative Commons Attribution-ShareAlike ლიცენზიათ; შილებე გეძინელი პირობეფიშ არსებუა. კილიშკილიშა..." } ``` #### unshuffled_original_yi - **Size of downloaded dataset files:** 33.33 MB - **Size of the generated dataset:** 147.60 MB - **Total amount of disk used:** 180.94 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"ממשותדיק - חבֿרה, איך אַרבעט איצט אױף אַ זשורנאַל. טאָמער איר האָט עפּעס צוצוגעבן זאָלט איר שיקן מיר אַן אָנזאָג. ס'װעט הײסן \\\"..." } ``` #### unshuffled_original_yo - **Size of downloaded dataset files:** 0.01 MB - **Size of the generated dataset:** 0.06 MB - **Total amount of disk used:** 0.06 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 0, "text": "\"Copyright © 2018 BBC. BBC kò mọ̀ nípa àwọn ohun tí ó wà ní àwọn ojú òpó tí ó wà ní ìta. Ọwọ́ tí a fi mú ìbáṣepọ̀ ti ìta.\"..." } ``` #### unshuffled_original_yue - **Size of downloaded dataset files:** 0.00 MB - **Size of the generated dataset:** 0.00 MB - **Total amount of disk used:** 0.00 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 我 灌 我 灌 我 灌 灌 灌 你還不爆 我累了 投降輸一半可以嗎\"..." } ``` #### unshuffled_original_zh - **Size of downloaded dataset files:** 206.00 GB - **Size of the generated dataset:** 545.61 GB - **Total amount of disk used:** 751.61 GB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "id": 1, "text": "\"中国铝灰网 中国有色金属矿产网 中国黄莲网 中国水轮发电机网 中国抽油泵网 中国数控雕刻机网 中国不锈钢抛光网 中国磨具加工网 中国压铸铝网 中国耐水腻子网 中国手机摄像头网 中国粗粮网 中国车门锁网 中国钛粉网 中国轮圈网\\n天天中奖彩票图 天天中彩票..." } ``` </details> ### Data Fields The data fields are the same among all configs. - `id`: a `int64` feature. - `text`: a `string` feature. ### Data Splits <details> <summary>Click to expand the number of samples per configuration</summary> | Language | Language code | Name original | Train original | Words original | Size original | Name deduplicated | Train deduplicated | Words deduplicated | Size deduplicated | | ----------------- | ------------- | ----------------------- | -------------- | --------------- | ------------- | --------------------------- | ------------------ | ------------------ | ----------------- | | Afrikaans | af | unshuffled_original_af | 201117 | 43,482,801 | 241M | unshuffled_deduplicated_af | 130640 | 29,533,437 | 163M | | Albanian | sq | unshuffled_original_sq | 672077 | 374,196,110 | 2.3G | unshuffled_deduplicated_sq | 461598 | 186,856,699 | 1.2G | | Alemannic | als | unshuffled_original_als | 7324 | 841,750 | 5.0M | unshuffled_deduplicated_als | 4518 | 459,001 | 2.8M | | Amharic | am | unshuffled_original_am | 83663 | 28,301,601 | 360M | unshuffled_deduplicated_am | 43102 | 16,086,628 | 206M | | Arabic | ar | unshuffled_original_ar | 16365602 | 8,117,162,828 | 82G | unshuffled_deduplicated_ar | 9006977 | 3,171,221,354 | 32G | | Aragonese | an | unshuffled_original_an | 2449 | 52,896 | 1.3M | unshuffled_deduplicated_an | 2025 | 45,669 | 801K | | Armenian | hy | unshuffled_original_hy | 659430 | 273,919,388 | 3.7G | unshuffled_deduplicated_hy | 396093 | 110,196,043 | 1.5G | | Assamese | as | unshuffled_original_as | 14985 | 6,956,663 | 113M | unshuffled_deduplicated_as | 9212 | 4,366,570 | 71M | | Asturian | ast | unshuffled_original_ast | 6999 | 381,005 | 2.4M | unshuffled_deduplicated_ast | 5343 | 325,237 | 2.0M | | Avaric | av | unshuffled_original_av | 456 | 24,720 | 409K | unshuffled_deduplicated_av | 360 | 19,478 | 324K | | Azerbaijani | az | unshuffled_original_az | 912330 | 322,641,710 | 2.8G | unshuffled_deduplicated_az | 626796 | 167,742,296 | 1.5G | | Bashkir | ba | unshuffled_original_ba | 42551 | 9,796,764 | 128M | unshuffled_deduplicated_ba | 27050 | 6,922,589 | 90M | | Basque | eu | unshuffled_original_eu | 506883 | 120,456,652 | 848M | unshuffled_deduplicated_eu | 256513 | 45,359,710 | 342M | | Bavarian | bar | unshuffled_original_bar | 4 | 399 | 503 | unshuffled_deduplicated_bar | 4 | 399 | 503 | | Belarusian | be | unshuffled_original_be | 586031 | 144,579,630 | 1.8G | unshuffled_deduplicated_be | 307405 | 83,499,037 | 1.1G | | Bengali | bn | unshuffled_original_bn | 1675515 | 623,575,733 | 11G | unshuffled_deduplicated_bn | 1114481 | 363,766,143 | 5.8G | | Bihari | bh | unshuffled_original_bh | 336 | 8,848 | 110K | unshuffled_deduplicated_bh | 82 | 2,875 | 34K | | Bishnupriya | bpy | unshuffled_original_bpy | 6046 | 198,286 | 4.1M | unshuffled_deduplicated_bpy | 1770 | 96,940 | 1.7M | | Bosnian | bs | unshuffled_original_bs | 2143 | 106,448 | 447K | unshuffled_deduplicated_bs | 702 | 20,485 | 116K | | Breton | br | unshuffled_original_br | 37085 | 5,013,241 | 29M | unshuffled_deduplicated_br | 14724 | 2,890,384 | 16M | | Bulgarian | bg | unshuffled_original_bg | 5869686 | 2,947,648,106 | 32G | unshuffled_deduplicated_bg | 3398679 | 1,268,114,977 | 14G | | Burmese | my | unshuffled_original_my | 232329 | 56,111,184 | 1.9G | unshuffled_deduplicated_my | 136639 | 30,102,173 | 1.1G | | Catalan | ca | unshuffled_original_ca | 4390754 | 1,360,212,450 | 8.0G | unshuffled_deduplicated_ca | 2458067 | 729,333,440 | 4.3G | | Cebuano | ceb | unshuffled_original_ceb | 56248 | 6,603,567 | 39M | unshuffled_deduplicated_ceb | 26145 | 3,675,024 | 24M | | Central Bikol | bcl | unshuffled_original_bcl | 1 | 312 | 885 | unshuffled_deduplicated_bcl | 1 | 312 | 885 | | Central Khmer | km | unshuffled_original_km | 159363 | 20,690,610 | 1.1G | unshuffled_deduplicated_km | 108346 | 10,082,245 | 581M | | Central Kurdish | ckb | unshuffled_original_ckb | 103639 | 48,478,334 | 487M | unshuffled_deduplicated_ckb | 68210 | 18,726,721 | 226M | | Chavacano | cbk | unshuffled_original_cbk | 1 | 130 | 520 | unshuffled_deduplicated_cbk | 1 | 130 | 520 | | Chechen | ce | unshuffled_original_ce | 4042 | 711,051 | 8.3M | unshuffled_deduplicated_ce | 2984 | 568,146 | 6.7M | | Chinese | zh | unshuffled_original_zh | 60137667 | 14,986,424,850 | 508G | unshuffled_deduplicated_zh | 41708901 | 6,350,215,113 | 249G | | Chuvash | cv | unshuffled_original_cv | 20281 | 3,041,614 | 39M | unshuffled_deduplicated_cv | 10130 | 2,054,810 | 26M | | Cornish | kw | unshuffled_original_kw | 203 | 8,329 | 44K | unshuffled_deduplicated_kw | 68 | 2,704 | 14K | | Croatian | hr | unshuffled_original_hr | 582219 | 34,232,765 | 226M | unshuffled_deduplicated_hr | 321484 | 16,727,640 | 110M | | Czech | cs | unshuffled_original_cs | 21001388 | 7,715,977,441 | 53G | unshuffled_deduplicated_cs | 12308039 | 3,540,997,509 | 24G | | Danish | da | unshuffled_original_da | 7664010 | 2,637,463,889 | 16G | unshuffled_deduplicated_da | 4771098 | 1,620,091,317 | 9.5G | | Dhivehi | dv | unshuffled_original_dv | 21018 | 7,559,472 | 126M | unshuffled_deduplicated_dv | 17024 | 4,726,660 | 79M | | Dimli | diq | unshuffled_original_diq | 1 | 19 | 146 | unshuffled_deduplicated_diq | 1 | 19 | 146 | | Dutch | nl | unshuffled_original_nl | 34682142 | 13,020,136,373 | 78G | unshuffled_deduplicated_nl | 20812149 | 6,598,786,137 | 39G | | Eastern Mari | mhr | unshuffled_original_mhr | 3212 | 565,992 | 7.2M | unshuffled_deduplicated_mhr | 2515 | 469,297 | 6.0M | | Egyptian Arabic | arz | unshuffled_original_arz | 158113 | 7,305,151 | 66M | unshuffled_deduplicated_arz | 79928 | 3,659,419 | 33M | | Emilian-Romagnol | eml | unshuffled_original_eml | 84 | 6,376 | 25K | unshuffled_deduplicated_eml | 80 | 6,121 | 24K | | English | en | unshuffled_original_en | 455994980 | 418,187,793,408 | 2.3T | unshuffled_deduplicated_en | 304230423 | 215,841,256,971 | 1.2T | | Erzya | myv | unshuffled_original_myv | 6 | 90 | 1.4K | unshuffled_deduplicated_myv | 5 | 78 | 1.2K | | Esperanto | eo | unshuffled_original_eo | 121171 | 48,486,161 | 299M | unshuffled_deduplicated_eo | 84752 | 37,324,446 | 228M | | Estonian | et | unshuffled_original_et | 2093621 | 643,163,730 | 4.8G | unshuffled_deduplicated_et | 1172041 | 309,931,463 | 2.3G | | Finnish | fi | unshuffled_original_fi | 8557453 | 3,196,666,419 | 27G | unshuffled_deduplicated_fi | 5326443 | 1,597,855,468 | 13G | | French | fr | unshuffled_original_fr | 96742378 | 46,896,036,417 | 282G | unshuffled_deduplicated_fr | 59448891 | 23,206,776,649 | 138G | | Galician | gl | unshuffled_original_gl | 544388 | 102,011,291 | 620M | unshuffled_deduplicated_gl | 284320 | 63,600,602 | 384M | | Georgian | ka | unshuffled_original_ka | 563916 | 171,950,621 | 3.6G | unshuffled_deduplicated_ka | 372158 | 91,569,739 | 1.9G | | German | de | unshuffled_original_de | 104913504 | 44,878,908,446 | 308G | unshuffled_deduplicated_de | 62398034 | 21,529,164,172 | 145G | | Goan Konkani | gom | unshuffled_original_gom | 640 | 124,277 | 2.2M | unshuffled_deduplicated_gom | 484 | 102,306 | 1.8M | | Guarani | gn | unshuffled_original_gn | 106 | 7,382 | 36K | unshuffled_deduplicated_gn | 68 | 4,680 | 24K | | Gujarati | gu | unshuffled_original_gu | 240691 | 72,045,701 | 1.1G | unshuffled_deduplicated_gu | 169834 | 50,023,432 | 722M | | Haitian | ht | unshuffled_original_ht | 13 | 1,014 | 3.9K | unshuffled_deduplicated_ht | 9 | 832 | 3.3K | | Hebrew | he | unshuffled_original_he | 3808397 | 2,067,753,528 | 20G | unshuffled_deduplicated_he | 2375030 | 1,032,018,056 | 9.8G | | Hindi | hi | unshuffled_original_hi | 3264660 | 1,372,234,782 | 17G | unshuffled_deduplicated_hi | 1909387 | 745,774,934 | 8.9G | | Hungarian | hu | unshuffled_original_hu | 11197780 | 5,163,936,345 | 40G | unshuffled_deduplicated_hu | 6582908 | 2,339,127,555 | 18G | | Icelandic | is | unshuffled_original_is | 625673 | 219,900,094 | 1.5G | unshuffled_deduplicated_is | 389515 | 129,818,331 | 846M | | Ido | io | unshuffled_original_io | 694 | 25,702 | 147K | unshuffled_deduplicated_io | 617 | 22,773 | 130K | | Iloko | ilo | unshuffled_original_ilo | 2638 | 142,942 | 874K | unshuffled_deduplicated_ilo | 1578 | 105,564 | 636K | | Indonesian | id | unshuffled_original_id | 16236463 | 4,574,692,265 | 30G | unshuffled_deduplicated_id | 9948521 | 2,394,957,629 | 16G | | Interlingua | ia | unshuffled_original_ia | 1040 | 180,231 | 662K | unshuffled_deduplicated_ia | 529 | 100,019 | 360K | | Interlingue | ie | unshuffled_original_ie | 101 | 5,352 | 24K | unshuffled_deduplicated_ie | 11 | 602 | 1.6K | | Irish | ga | unshuffled_original_ga | 83223 | 14,483,593 | 88M | unshuffled_deduplicated_ga | 46493 | 10,017,303 | 60M | | Italian | it | unshuffled_original_it | 46981781 | 22,248,707,341 | 137G | unshuffled_deduplicated_it | 28522082 | 11,250,012,896 | 69G | | Japanese | ja | unshuffled_original_ja | 62721527 | 4,962,979,182 | 216G | unshuffled_deduplicated_ja | 39496439 | 1,123,067,063 | 106G | | Javanese | jv | unshuffled_original_jv | 1445 | 104,896 | 659K | unshuffled_deduplicated_jv | 1163 | 86,654 | 583K | | Kalmyk | xal | unshuffled_original_xal | 39 | 10,277 | 113K | unshuffled_deduplicated_xal | 36 | 10,155 | 112K | | Kannada | kn | unshuffled_original_kn | 350363 | 81,186,863 | 1.7G | unshuffled_deduplicated_kn | 251064 | 49,343,462 | 1.1G | | Karachay-Balkar | krc | unshuffled_original_krc | 1581 | 185,436 | 2.6M | unshuffled_deduplicated_krc | 1377 | 166,496 | 2.3M | | Kazakh | kk | unshuffled_original_kk | 524591 | 191,126,469 | 2.7G | unshuffled_deduplicated_kk | 338073 | 108,388,743 | 1.5G | | Kirghiz | ky | unshuffled_original_ky | 146993 | 44,194,823 | 600M | unshuffled_deduplicated_ky | 86561 | 28,982,620 | 388M | | Komi | kv | unshuffled_original_kv | 1549 | 201,404 | 2.3M | unshuffled_deduplicated_kv | 924 | 95,243 | 1.2M | | Korean | ko | unshuffled_original_ko | 7345075 | 2,368,765,142 | 24G | unshuffled_deduplicated_ko | 3675420 | 1,120,375,149 | 12G | | Kurdish | ku | unshuffled_original_ku | 46535 | 15,561,003 | 94M | unshuffled_deduplicated_ku | 29054 | 9,946,440 | 60M | | Lao | lo | unshuffled_original_lo | 52910 | 4,133,311 | 174M | unshuffled_deduplicated_lo | 32652 | 2,583,342 | 114M | | Latin | la | unshuffled_original_la | 94588 | 4,122,201 | 26M | unshuffled_deduplicated_la | 18808 | 1,328,038 | 8.3M | | Latvian | lv | unshuffled_original_lv | 1593820 | 520,761,977 | 4.0G | unshuffled_deduplicated_lv | 843195 | 236,428,905 | 1.8G | | Lezghian | lez | unshuffled_original_lez | 1485 | 247,646 | 3.3M | unshuffled_deduplicated_lez | 1381 | 224,871 | 3.0M | | Limburgan | li | unshuffled_original_li | 137 | 4,730 | 29K | unshuffled_deduplicated_li | 118 | 4,283 | 27K | | Lithuanian | lt | unshuffled_original_lt | 2977757 | 1,159,661,742 | 8.8G | unshuffled_deduplicated_lt | 1737411 | 516,183,525 | 3.9G | | Lojban | jbo | unshuffled_original_jbo | 832 | 154,330 | 736K | unshuffled_deduplicated_jbo | 617 | 141,973 | 678K | | Lombard | lmo | unshuffled_original_lmo | 1401 | 75,229 | 443K | unshuffled_deduplicated_lmo | 1374 | 73,665 | 433K | | Low German | nds | unshuffled_original_nds | 18174 | 2,906,347 | 18M | unshuffled_deduplicated_nds | 8714 | 2,146,417 | 13M | | Lower Sorbian | dsb | unshuffled_original_dsb | 65 | 1,787 | 13K | unshuffled_deduplicated_dsb | 37 | 966 | 7.1K | | Luxembourgish | lb | unshuffled_original_lb | 34807 | 4,403,577 | 29M | unshuffled_deduplicated_lb | 21735 | 3,087,650 | 21M | | Macedonian | mk | unshuffled_original_mk | 437871 | 189,289,873 | 2.1G | unshuffled_deduplicated_mk | 299457 | 102,849,595 | 1.2G | | Maithili | mai | unshuffled_original_mai | 123 | 69,161 | 317K | unshuffled_deduplicated_mai | 25 | 874 | 11K | | Malagasy | mg | unshuffled_original_mg | 17957 | 3,068,360 | 21M | unshuffled_deduplicated_mg | 13343 | 1,872,044 | 13M | | Malay | ms | unshuffled_original_ms | 534016 | 16,696,882 | 111M | unshuffled_deduplicated_ms | 183443 | 6,045,753 | 42M | | Malayalam | ml | unshuffled_original_ml | 603937 | 189,534,472 | 4.9G | unshuffled_deduplicated_ml | 453904 | 95,892,551 | 2.5G | | Maltese | mt | unshuffled_original_mt | 26598 | 2,995,654 | 24M | unshuffled_deduplicated_mt | 16383 | 2,163,358 | 17M | | Marathi | mr | unshuffled_original_mr | 326804 | 162,609,404 | 2.7G | unshuffled_deduplicated_mr | 212556 | 82,130,803 | 1.4G | | Mazanderani | mzn | unshuffled_original_mzn | 1055 | 73,870 | 691K | unshuffled_deduplicated_mzn | 917 | 64,481 | 602K | | Minangkabau | min | unshuffled_original_min | 220 | 5,682 | 608K | unshuffled_deduplicated_min | 166 | 4,825 | 310K | | Mingrelian | xmf | unshuffled_original_xmf | 3783 | 299,098 | 5.8M | unshuffled_deduplicated_xmf | 2418 | 228,629 | 4.4M | | Mirandese | mwl | unshuffled_original_mwl | 8 | 171 | 1.2K | unshuffled_deduplicated_mwl | 7 | 152 | 1.1K | | Modern Greek | el | unshuffled_original_el | 10425596 | 5,479,180,137 | 62G | unshuffled_deduplicated_el | 6521169 | 2,412,419,435 | 27G | | Mongolian | mn | unshuffled_original_mn | 395605 | 181,307,167 | 2.2G | unshuffled_deduplicated_mn | 197878 | 68,362,013 | 838M | | Nahuatl languages | nah | unshuffled_original_nah | 61 | 1,234 | 12K | unshuffled_deduplicated_nah | 58 | 1,193 | 11K | | Neapolitan | nap | unshuffled_original_nap | 73 | 5,282 | 17K | unshuffled_deduplicated_nap | 55 | 4,147 | 13K | | Nepali | ne | unshuffled_original_ne | 299938 | 107,448,208 | 1.8G | unshuffled_deduplicated_ne | 219334 | 71,628,317 | 1.2G | | Newari | new | unshuffled_original_new | 4696 | 564,697 | 5.5M | unshuffled_deduplicated_new | 2126 | 288,995 | 4.1M | | Northern Frisian | frr | unshuffled_original_frr | 7 | 1,516 | 4.4K | unshuffled_deduplicated_frr | 7 | 1,516 | 4.4K | | Northern Luri | lrc | unshuffled_original_lrc | 88 | 8,022 | 76K | unshuffled_deduplicated_lrc | 72 | 6,740 | 63K | | Norwegian | no | unshuffled_original_no | 5546211 | 1,344,326,388 | 8.0G | unshuffled_deduplicated_no | 3229940 | 804,894,377 | 4.7G | | Norwegian Nynorsk | nn | unshuffled_original_nn | 185884 | 14,764,980 | 85M | unshuffled_deduplicated_nn | 109118 | 9,435,139 | 54M | | Occitan | oc | unshuffled_original_oc | 10709 | 750,301 | 5.8M | unshuffled_deduplicated_oc | 6485 | 512,678 | 3.7M | | Oriya | or | unshuffled_original_or | 59463 | 14,938,567 | 248M | unshuffled_deduplicated_or | 44230 | 11,321,740 | 188M | | Ossetian | os | unshuffled_original_os | 5213 | 1,031,268 | 13M | unshuffled_deduplicated_os | 2559 | 878,765 | 11M | | Pampanga | pam | unshuffled_original_pam | 3 | 130 | 760 | unshuffled_deduplicated_pam | 1 | 52 | 304 | | Panjabi | pa | unshuffled_original_pa | 127467 | 61,847,806 | 763M | unshuffled_deduplicated_pa | 87235 | 37,555,835 | 460M | | Persian | fa | unshuffled_original_fa | 13704702 | 9,096,554,121 | 79G | unshuffled_deduplicated_fa | 8203495 | 4,363,505,319 | 38G | | Piemontese | pms | unshuffled_original_pms | 3225 | 362,013 | 2.1M | unshuffled_deduplicated_pms | 2859 | 337,246 | 1.9M | | Polish | pl | unshuffled_original_pl | 35440972 | 15,277,255,137 | 109G | unshuffled_deduplicated_pl | 20682611 | 6,708,709,674 | 47G | | Portuguese | pt | unshuffled_original_pt | 42114520 | 20,641,903,898 | 124G | unshuffled_deduplicated_pt | 26920397 | 10,751,156,918 | 64G | | Pushto | ps | unshuffled_original_ps | 98216 | 46,559,441 | 361M | unshuffled_deduplicated_ps | 67921 | 31,347,348 | 242M | | Quechua | qu | unshuffled_original_qu | 452 | 10,186 | 78K | unshuffled_deduplicated_qu | 411 | 8,691 | 67K | | Romanian | ro | unshuffled_original_ro | 9387265 | 3,984,317,058 | 25G | unshuffled_deduplicated_ro | 5044757 | 1,741,794,069 | 11G | | Romansh | rm | unshuffled_original_rm | 41 | 1,093 | 7.4K | unshuffled_deduplicated_rm | 34 | 960 | 6.5K | | Russia Buriat | bxr | unshuffled_original_bxr | 42 | 963 | 13K | unshuffled_deduplicated_bxr | 36 | 809 | 11K | | Russian | ru | unshuffled_original_ru | 161836003 | 92,522,407,837 | 1.2T | unshuffled_deduplicated_ru | 115954598 | 46,692,691,520 | 568G | | Sanskrit | sa | unshuffled_original_sa | 14291 | 4,331,569 | 93M | unshuffled_deduplicated_sa | 7121 | 1,713,930 | 37M | | Scottish Gaelic | gd | unshuffled_original_gd | 5799 | 310,689 | 1.9M | unshuffled_deduplicated_gd | 3883 | 207,110 | 1.3M | | Serbian | sr | unshuffled_original_sr | 1013619 | 364,395,411 | 3.9G | unshuffled_deduplicated_sr | 645747 | 207,561,168 | 2.2G | | Serbo-Croatian | sh | unshuffled_original_sh | 36700 | 5,292,184 | 25M | unshuffled_deduplicated_sh | 17610 | 1,040,573 | 5.8M | | Sicilian | scn | unshuffled_original_scn | 21 | 554 | 3.3K | unshuffled_deduplicated_scn | 17 | 468 | 2.8K | | Sindhi | sd | unshuffled_original_sd | 44280 | 43,530,158 | 347M | unshuffled_deduplicated_sd | 33925 | 33,028,015 | 263M | | Sinhala | si | unshuffled_original_si | 203082 | 93,053,465 | 1.4G | unshuffled_deduplicated_si | 120684 | 50,864,857 | 802M | | Slovak | sk | unshuffled_original_sk | 5492194 | 1,322,247,763 | 9.1G | unshuffled_deduplicated_sk | 2820821 | 656,346,179 | 4.5G | | Slovenian | sl | unshuffled_original_sl | 1746604 | 387,399,700 | 2.5G | unshuffled_deduplicated_sl | 886223 | 193,926,684 | 1.3G | | Somali | so | unshuffled_original_so | 156 | 1,202 | 61K | unshuffled_deduplicated_so | 42 | 472 | 16K | | South Azerbaijani | azb | unshuffled_original_azb | 15446 | 2,175,054 | 27M | unshuffled_deduplicated_azb | 9985 | 1,528,709 | 19M | | Spanish | es | unshuffled_original_es | 88199221 | 47,545,122,279 | 278G | unshuffled_deduplicated_es | 56326016 | 25,928,290,729 | 149G | | Sundanese | su | unshuffled_original_su | 805 | 30,321 | 211K | unshuffled_deduplicated_su | 511 | 20,278 | 141K | | Swahili | sw | unshuffled_original_sw | 41986 | 2,211,927 | 13M | unshuffled_deduplicated_sw | 24803 | 1,376,963 | 8.1M | | Swedish | sv | unshuffled_original_sv | 17395625 | 7,155,994,312 | 44G | unshuffled_deduplicated_sv | 11014487 | 4,106,120,608 | 25G | | Tagalog | tl | unshuffled_original_tl | 458206 | 98,949,299 | 573M | unshuffled_deduplicated_tl | 294132 | 70,121,601 | 407M | | Tajik | tg | unshuffled_original_tg | 89002 | 31,758,142 | 379M | unshuffled_deduplicated_tg | 56259 | 21,029,893 | 249M | | Tamil | ta | unshuffled_original_ta | 1263280 | 420,537,132 | 9.3G | unshuffled_deduplicated_ta | 833101 | 226,013,330 | 5.1G | | Tatar | tt | unshuffled_original_tt | 135923 | 51,034,893 | 670M | unshuffled_deduplicated_tt | 82738 | 23,825,695 | 305M | | Telugu | te | unshuffled_original_te | 475703 | 123,711,517 | 2.5G | unshuffled_deduplicated_te | 312644 | 79,094,167 | 1.6G | | Thai | th | unshuffled_original_th | 6064129 | 951,743,087 | 36G | unshuffled_deduplicated_th | 3749826 | 368,965,202 | 16G | | Tibetan | bo | unshuffled_original_bo | 26795 | 1,483,589 | 187M | unshuffled_deduplicated_bo | 15762 | 936,556 | 138M | | Turkish | tr | unshuffled_original_tr | 18535253 | 7,577,388,700 | 60G | unshuffled_deduplicated_tr | 11596446 | 3,365,734,289 | 27G | | Turkmen | tk | unshuffled_original_tk | 6456 | 1,113,869 | 11M | unshuffled_deduplicated_tk | 4694 | 752,326 | 6.8M | | Tuvinian | tyv | unshuffled_original_tyv | 34 | 759 | 12K | unshuffled_deduplicated_tyv | 24 | 540 | 7.9K | | Uighur | ug | unshuffled_original_ug | 22255 | 8,657,141 | 122M | unshuffled_deduplicated_ug | 15503 | 5,852,225 | 83M | | Ukrainian | uk | unshuffled_original_uk | 12973467 | 4,204,381,276 | 53G | unshuffled_deduplicated_uk | 7782375 | 2,252,380,351 | 28G | | Upper Sorbian | hsb | unshuffled_original_hsb | 7959 | 545,351 | 4.2M | unshuffled_deduplicated_hsb | 3084 | 236,867 | 1.8M | | Urdu | ur | unshuffled_original_ur | 638596 | 331,817,982 | 2.7G | unshuffled_deduplicated_ur | 428674 | 218,030,228 | 1.7G | | Uzbek | uz | unshuffled_original_uz | 27537 | 2,450,256 | 21M | unshuffled_deduplicated_uz | 15074 | 1,381,644 | 12M | | Venetian | vec | unshuffled_original_vec | 73 | 3,492 | 18K | unshuffled_deduplicated_vec | 64 | 3,199 | 17K | | Vietnamese | vi | unshuffled_original_vi | 14898250 | 12,036,845,359 | 68G | unshuffled_deduplicated_vi | 9897709 | 5,577,159,843 | 32G | | Volapük | vo | unshuffled_original_vo | 3366 | 321,121 | 2.0M | unshuffled_deduplicated_vo | 3317 | 318,568 | 2.0M | | Walloon | wa | unshuffled_original_wa | 1001 | 50,720 | 273K | unshuffled_deduplicated_wa | 677 | 37,543 | 203K | | Waray | war | unshuffled_original_war | 9760 | 397,315 | 2.5M | unshuffled_deduplicated_war | 9161 | 336,311 | 2.2M | | Welsh | cy | unshuffled_original_cy | 157698 | 37,422,441 | 213M | unshuffled_deduplicated_cy | 98225 | 23,574,673 | 133M | | Western Frisian | fy | unshuffled_original_fy | 33053 | 5,691,077 | 35M | unshuffled_deduplicated_fy | 20661 | 4,223,816 | 26M | | Western Mari | mrj | unshuffled_original_mrj | 757 | 93,338 | 1.2M | unshuffled_deduplicated_mrj | 669 | 87,780 | 1.1M | | Western Panjabi | pnb | unshuffled_original_pnb | 4599 | 1,426,986 | 12M | unshuffled_deduplicated_pnb | 3463 | 1,111,112 | 9.0M | | Wu Chinese | wuu | unshuffled_original_wuu | 214 | 11,189 | 109K | unshuffled_deduplicated_wuu | 64 | 4,333 | 32K | | Yakut | sah | unshuffled_original_sah | 22301 | 2,547,623 | 42M | unshuffled_deduplicated_sah | 8555 | 1,789,174 | 26M | | Yiddish | yi | unshuffled_original_yi | 59364 | 13,834,320 | 141M | unshuffled_deduplicated_yi | 32919 | 8,212,970 | 84M | | Yoruba | yo | unshuffled_original_yo | 214 | 8,906 | 55K | unshuffled_deduplicated_yo | 49 | 3,518 | 27K | | Yue Chinese | yue | unshuffled_original_yue | 11 | 186 | 3.7K | unshuffled_deduplicated_yue | 7 | 128 | 2.2K | </details> ## Dataset Creation ### Curation Rationale OSCAR was constructed new pipeline derived from the [fastText's one](https://github.com/facebookresearch/fastText), called [_goclassy_](https://github.com/pjox/goclassy). Goclassy reuses the [fastText linear classifier](https://fasttext.cc) and the pre-trained fastText model for language recognition, but it completely rewrites and parallelises their pipeline in an asynchronous manner. The order of operations is more or less the same as in the fastText pre-processing pipeline but instead of clustering multiple operations into a single blocking process, a worker is launched for each operation but bounding the number of possible parallel operations at a given time by the number of available threads instead of the number of CPUs. Goclassy is implemented in the [Go programming language](https://golang.org/) so it lets the [Go runtime](https://golang.org/src/runtime/mprof.go) handle the scheduling of the processes. Thus the goclassy's pipeline one does not have to wait for a whole WET file to download, decompress and classify in order to start downloading and processing the next one, a new file will start downloading and processing as soon as the scheduler is able to allocate a new process. Filtering and cleaning processes at line level are done before feeding each line to the classifier. Lines shorter than 100 UTF-8 characters and lines containing invalid UTF-8 characters are discarted and are not classified. After all files are proccesed the deduplicated versions are constructed and everything is then splitted in shards and compressed. ### Source Data #### Initial Data Collection and Normalization [Common Crawl](https://commoncrawl.org/) is a non-profit foundation which produces and maintains an open repository of web crawled data that is both accessible and analysable. Common Crawl's complete web archive consists of petabytes of data collected over 8 years of web crawling. The repository contains raw web page HTML data (WARC files), metdata extracts (WAT files) and plain text extracts (WET files). The organisation's crawlers has always respected [nofollow](http://microformats.org/wiki/rel-nofollow) and [robots.txt](https://www.robotstxt.org/) policies. Each monthly Common Crawl snapshot is in itself a massive multilingual corpus, where every single file contains data coming from multiple web pages written in a large variety of languages and covering all possible types of topics. To construct OSCAR the WET files of Common Crawl were used. These contain the extracted plain texts from the websites mostly converted to UTF-8, as well as headers containing the metatada of each crawled document. Each WET file comes compressed in gzip format and is stored on Amazon Web Services. In the case of OSCAR, the **November 2018** snapshot was used. It surpasses 20TB of uncompressed data and contains more than 50 thousand plain text files where each file consists of the plain text from multiple websites along its metadata header. #### Who are the source language producers? The data comes from multiple web pages in a large variety of languages. ### Annotations The dataset does not contain any additional annotations. #### Annotation process N/A #### Who are the annotators? N/A ### Personal and Sensitive Information Being constructed from Common Crawl, Personal and sensitive information might be present. This **must** be considered before training deep learning models with OSCAR, specially in the case of text-generation models. ## Considerations for Using the Data ### Social Impact of Dataset OSCAR is intended to bring more data to a wide variety of lanuages, the aim of the corpus is to make large amounts of data available to lower resource languages in order to facilitate the pre-training of state-of-the-art language modeling architectures. ### Discussion of Biases OSCAR is not properly filtered yet and this can be reflected on the models trained with it. Care is advised specially concerning biases of the resulting models. ### Other Known Limitations The [fastText linear classifier](https://fasttext.cc) is limed both in performance and the variety of languages it can recognize, so the quality of some OSCAR sub-corpora might be lower than expected, specially for the lowest-resource langiuages. Some audits have already been done by [third parties](https://arxiv.org/abs/2010.14571). ## Additional Information ### Dataset Curators The corpus was put together by [Pedro J. Ortiz](https://pjortiz.eu/), [Benoît Sagot](http://pauillac.inria.fr/~sagot/), and [Laurent Romary](https://cv.archives-ouvertes.fr/laurentromary), during work done at [Inria](https://www.inria.fr/en), particularly at the [ALMAnaCH team](https://team.inria.fr/almanach/). ### Licensing Information These data are released under this licensing scheme We do not own any of the text from which these data has been extracted. We license the actual packaging of these data under the Creative Commons CC0 license ("no rights reserved") http://creativecommons.org/publicdomain/zero/1.0/ To the extent possible under law, Inria has waived all copyright and related or neighboring rights to OSCAR This work is published from: France. Should you consider that our data contains material that is owned by you and should therefore not be reproduced here, please: * Clearly identify yourself, with detailed contact data such as an address, telephone number or email address at which you can be contacted. * Clearly identify the copyrighted work claimed to be infringed. * Clearly identify the material that is claimed to be infringing and information reasonably sufficient to allow us to locate the material. We will comply to legitimate requests by removing the affected sources from the next release of the corpus. ### Citation Information ``` @inproceedings{ortiz-suarez-etal-2020-monolingual, title = "A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages", author = "Ortiz Su{'a}rez, Pedro Javier and Romary, Laurent and Sagot, Benoit", booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics", month = jul, year = "2020", address = "Online", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/2020.acl-main.156", pages = "1703--1714", abstract = "We use the multilingual OSCAR corpus, extracted from Common Crawl via language classification, filtering and cleaning, to train monolingual contextualized word embeddings (ELMo) for five mid-resource languages. We then compare the performance of OSCAR-based and Wikipedia-based ELMo embeddings for these languages on the part-of-speech tagging and parsing tasks. We show that, despite the noise in the Common-Crawl-based OSCAR data, embeddings trained on OSCAR perform much better than monolingual embeddings trained on Wikipedia. They actually equal or improve the current state of the art in tagging and parsing for all five languages. In particular, they also improve over multilingual Wikipedia-based contextual embeddings (multilingual BERT), which almost always constitutes the previous state of the art, thereby showing that the benefit of a larger, more diverse corpus surpasses the cross-lingual benefit of multilingual embedding architectures.", } @inproceedings{OrtizSuarezSagotRomary2019, author = {Pedro Javier {Ortiz Su{'a}rez} and Benoit Sagot and Laurent Romary}, title = {Asynchronous pipelines for processing huge corpora on medium to low resource infrastructures}, series = {Proceedings of the Workshop on Challenges in the Management of Large Corpora (CMLC-7) 2019. Cardiff, 22nd July 2019}, editor = {Piotr Bański and Adrien Barbaresi and Hanno Biber and Evelyn Breiteneder and Simon Clematide and Marc Kupietz and Harald L{"u}ngen and Caroline Iliadi}, publisher = {Leibniz-Institut f{"u}r Deutsche Sprache}, address = {Mannheim}, doi = {10.14618/ids-pub-9021}, url = {http://nbn-resolving.de/urn:nbn:de:bsz:mh39-90215}, pages = {9 -- 16}, year = {2019}, abstract = {Common Crawl is a considerably large, heterogeneous multilingual corpus comprised of crawled documents from the internet, surpassing 20TB of data and distributed as a set of more than 50 thousand plain text files where each contains many documents written in a wide variety of languages. Even though each document has a metadata block associated to it, this data lacks any information about the language in which each document is written, making it extremely difficult to use Common Crawl for monolingual applications. We propose a general, highly parallel, multithreaded pipeline to clean and classify Common Crawl by language; we specifically design it so that it runs efficiently on medium to low resource infrastructures where I/O speeds are the main constraint. We develop the pipeline so that it can be easily reapplied to any kind of heterogeneous corpus and so that it can be parameterised to a wide range of infrastructures. We also distribute a 6.3TB version of Common Crawl, filtered, classified by language, shuffled at line level in order to avoid copyright issues, and ready to be used for NLP applications.}, language = {en} } ``` ### Contributions Thanks to [@pjox](https://github.com/pjox) and [@lhoestq](https://github.com/lhoestq) for adding this dataset.

Lichess/standard-chess-games

Lichess

--- license: cc0-1.0 pretty_name: Lichess Standard Rated Games configs: - config_name: default data_files: - split: train path: data/**/train-* tags: - chess - games - game - lichess size_categories: - 1B<n<10B --- > [!CAUTION] > This dataset is still a work in progress and some breaking changes might occur. In the meantime, please use https://database.lichess.org/#standard_games > # Dataset Card for the Lichess Rated Standard Chess Games Dataset ## Dataset Description **6,399,222,183** standard rated games, played on [lichess.org](https://lichess.org), updated monthly from the [database dumps](https://database.lichess.org/#standard_games). This version of the data is meant for data analysis. If you need PGN files you can find those [here](https://database.lichess.org/#standard_games). That said, once you have a subset of interest, it is trivial to convert it back to PGN as shown in the [Dataset Usage](#dataset-usage) section. This dataset is hive-partitioned into multiple parquet files on two keys: `year` and `month`: ```bash . ├── data │   └── year=2015 │   ├── month=01 │   │   ├── train-00000-of-00003.parquet │   │   ├── train-00001-of-00003.parquet │   │   └── train-00002-of-00003.parquet │   ├── month=02 │   │   ├── train-00000-of-00003.parquet │   │   ├── train-00001-of-00003.parquet │   │   └── train-00002-of-00003.parquet │   ├── ... ``` ### Dataset Usage <!-- Using the `datasets` library: ```python from datasets import load_dataset dset = load_dataset("Lichess/chess-evaluations", split="train") ``` Using the `polars` library: Using DuckDB: Using `python-chess`: --> ## Dataset Details ### Dataset Sample <!-- One row of the dataset looks like this: ```python { "Event":, "Site":, } ``` --> ### Dataset Fields <!-- Every row of the dataset contains the following fields: - **`Event`**: `string`, - **`Site`**: `string`, --> ### Notes - About 6% of the games include Stockfish analysis evaluations: [%eval 2.35] (235 centipawn advantage), [%eval #-4] (getting mated in 4), always from White's point of view. - The WhiteElo and BlackElo tags contain Glicko2 ratings. - The `movetext` column contains clock information as PGN %clk comments since April 2017. - The schema doesn't include the `Date` header, typically part of the [Seven Tag Roster](https://en.wikipedia.org/wiki/Portable_Game_Notation#Seven_Tag_Roster) as we deemed the `UTCDate` field to be enough. - A future version of the data will include the addition of a `UCI` column containing the corresponding moves in [UCI format](https://en.wikipedia.org/wiki/Universal_Chess_Interface).

jackyhate/text-to-image-2M

jackyhate

--- license: mit task_categories: - text-to-image - image-to-text - image-classification language: - en size_categories: - 1M<n<10M --- # text-to-image-2M: A High-Quality, Diverse Text-to-Image Training Dataset ## Overview `text-to-image-2M` is a curated text-image pair dataset designed for fine-tuning text-to-image models. The dataset consists of approximately 2 million samples, carefully selected and enhanced to meet the high demands of text-to-image model training. The motivation behind creating this dataset stems from the observation that datasets with over 1 million samples tend to produce better fine-tuning results. However, existing publicly available datasets often have limitations: - **Image Understanding Datasets**: Not guarantee the quality of image. - **Informal collected or Task-Specific Datasets**: Not category balanced or lacks diversity. - **Size Constraints**: Available datasets are either too small or too large. (subset sampled from large datasets often lack diversity.) To address these issues, we combined and enhanced existing high-quality datasets using state-of-the-art text-to-image and captioning models to create `text-to-image-2M`. This includes data_512_2M, a 2M 512x512 fine-tuning dataset and data_1024_10K, a 10K high-quality, high-resolution dataset (for high-resolution adaptation). ## Dataset Composition ### data_512_2M The dataset is composed of several high-quality subsets, as detailed below: | **Source** | **Samples** | **Prompts** | **Images** | |-------------------------------------------------|-------------|--------------------------------------|---------------------------------------------| | [**LLaVA-next fine-tuning dataset**](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Data) | ~700K | Re-captioned using Qwen2-VL | Original images | | [**LLaVA-pretrain dataset**](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) | ~500K | Original prompts | Images generated by Flux-dev | | [**ProGamerGov synthetic dataset (DALL·E 3)**](https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions) | ~900K | Filtered for validity | Center-cropped and validity-filtered images | | **GPT-4o generated dataset** | 100K | Generated by GPT-4o | Images generated by Flux-dev | ### data_1024_10K 10K images generated by Flux-dev with prompts generated by GPT-4o ## **Usage**: The dataset uses the [WebDataset](https://github.com/webdataset/webdataset) format and can be easily accessed and used with HuggingFace's datasets library like so: ```py from datasets import load_dataset base_url = "https://huggingface.co/datasets/jackyhate/text-to-image-2M/resolve/main/data_512_2M/data_{i:06d}.tar" num_shards = 46 # Number of webdataset tar files urls = [base_url.format(i=i) for i in range(num_shards)] dataset = load_dataset("webdataset", data_files={"train": urls}, split="train", streaming=True) # Example of iterating through the dataset for image in dataset: print(image) # single image in row with associated columns break ``` * Note that as long as `streaming=True` in the above example, the dataset does not have to be downloaded in full. ## Acknowledgments This dataset builds on the work of several open-source projects, including: - [**LLaVA-next fine-tuning dataset**](https://huggingface.co/datasets/lmms-lab/LLaVA-NeXT-Data) - [**LLaVA-pretrain dataset**](https://huggingface.co/datasets/liuhaotian/LLaVA-Pretrain) - [**ProGamerGov synthetic dataset (DALL·E 3)**](https://huggingface.co/datasets/ProGamerGov/synthetic-dataset-1m-dalle3-high-quality-captions) - **GPT-4o** - **Flux-1.0-dev** We thank the contributors of these datasets and models for making this project possible.

cardiffnlp/databench

cardiffnlp

--- language: - en - es pretty_name: " 💾🏋️💾 DataBench 💾🏋️💾" tags: - table-question-answering - table - qa license: mit task_categories: - table-question-answering - question-answering default: qa configs: - config_name: qa data_files: - data/001_Forbes/qa.parquet - data/002_Titanic/qa.parquet - data/003_Love/qa.parquet - data/004_Taxi/qa.parquet - data/005_NYC/qa.parquet - data/006_London/qa.parquet - data/007_Fifa/qa.parquet - data/008_Tornados/qa.parquet - data/009_Central/qa.parquet - data/010_ECommerce/qa.parquet - data/011_SF/qa.parquet - data/012_Heart/qa.parquet - data/013_Roller/qa.parquet - data/014_Airbnb/qa.parquet - data/015_Food/qa.parquet - data/016_Holiday/qa.parquet - data/017_Hacker/qa.parquet - data/018_Staff/qa.parquet - data/019_Aircraft/qa.parquet - data/020_Real/qa.parquet - data/021_Telco/qa.parquet - data/022_Airbnbs/qa.parquet - data/023_Climate/qa.parquet - data/024_Salary/qa.parquet - data/025_Data/qa.parquet - data/026_Predicting/qa.parquet - data/027_Supermarket/qa.parquet - data/028_Predict/qa.parquet - data/029_NYTimes/qa.parquet - data/030_Professionals/qa.parquet - data/031_Trustpilot/qa.parquet - data/032_Delicatessen/qa.parquet - data/033_Employee/qa.parquet - data/034_World/qa.parquet - data/035_Billboard/qa.parquet - data/036_US/qa.parquet - data/037_Ted/qa.parquet - data/038_Stroke/qa.parquet - data/039_Happy/qa.parquet - data/040_Speed/qa.parquet - data/041_Airline/qa.parquet - data/042_Predict/qa.parquet - data/043_Predict/qa.parquet - data/044_IMDb/qa.parquet - data/045_Predict/qa.parquet - data/046_120/qa.parquet - data/047_Bank/qa.parquet - data/048_Data/qa.parquet - data/049_Boris/qa.parquet - data/050_ING/qa.parquet - data/051_Pokemon/qa.parquet - data/052_Professional/qa.parquet - data/053_Patents/qa.parquet - data/054_Joe/qa.parquet - data/055_German/qa.parquet - data/056_Emoji/qa.parquet - data/057_Spain/qa.parquet - data/058_US/qa.parquet - data/059_Second/qa.parquet - data/060_Bakery/qa.parquet - data/061_Disneyland/qa.parquet - data/062_Trump/qa.parquet - data/063_Influencers/qa.parquet - data/064_Clustering/qa.parquet - data/065_RFM/qa.parquet # - split: 001_Forbes # path: data/001_Forbes/qa.parquet # - split: 002_Titanic # path: data/002_Titanic/qa.parquet # - split: 003_Love # path: data/003_Love/qa.parquet # - split: 004_Taxi # path: data/004_Taxi/qa.parquet # - split: 005_NYC # path: data/005_NYC/qa.parquet # - split: 006_London # path: data/006_London/qa.parquet # - split: 007_Fifa # path: data/007_Fifa/qa.parquet # - split: 008_Tornados # path: data/008_Tornados/qa.parquet # - split: 009_Central # path: data/009_Central/qa.parquet # - split: 010_ECommerce # path: data/010_ECommerce/qa.parquet # - split: 011_SF # path: data/011_SF/qa.parquet # - split: 012_Heart # path: data/012_Heart/qa.parquet # - split: 013_Roller # path: data/013_Roller/qa.parquet # - split: 014_Airbnb # path: data/014_Airbnb/qa.parquet # - split: 015_Food # path: data/015_Food/qa.parquet # - split: 016_Holiday # path: data/016_Holiday/qa.parquet # - split: 017_Hacker # path: data/017_Hacker/qa.parquet # - split: 018_Staff # path: data/018_Staff/qa.parquet # - split: 019_Aircraft # path: data/019_Aircraft/qa.parquet # - split: 020_Real # path: data/020_Real/qa.parquet # - split: 021_Telco # path: data/021_Telco/qa.parquet # - split: 022_Airbnbs # path: data/022_Airbnbs/qa.parquet # - split: 023_Climate # path: data/023_Climate/qa.parquet # - split: 024_Salary # path: data/024_Salary/qa.parquet # - split: 025_Data # path: data/025_Data/qa.parquet # - split: 026_Predicting # path: data/026_Predicting/qa.parquet # - split: 027_Supermarket # path: data/027_Supermarket/qa.parquet # - split: 028_Predict # path: data/028_Predict/qa.parquet # - split: 029_NYTimes # path: data/029_NYTimes/qa.parquet # - split: 030_Professionals # path: data/030_Professionals/qa.parquet # - split: 031_Trustpilot # path: data/031_Trustpilot/qa.parquet # - split: 032_Delicatessen # path: data/032_Delicatessen/qa.parquet # - split: 033_Employee # path: data/033_Employee/qa.parquet # - split: 034_World # path: data/034_World/qa.parquet # - split: 035_Billboard # path: data/035_Billboard/qa.parquet # - split: 036_US # path: data/036_US/qa.parquet # - split: 037_Ted # path: data/037_Ted/qa.parquet # - split: 038_Stroke # path: data/038_Stroke/qa.parquet # - split: 039_Happy # path: data/039_Happy/qa.parquet # - split: 040_Speed # path: data/040_Speed/qa.parquet # - split: 041_Airline # path: data/041_Airline/qa.parquet # - split: 042_Predict # path: data/042_Predict/qa.parquet # - split: 043_Predict # path: data/043_Predict/qa.parquet # - split: 044_IMDb # path: data/044_IMDb/qa.parquet # - split: 045_Predict # path: data/045_Predict/qa.parquet # - split: "046_120" # path: data/046_120/qa.parquet # - split: 047_Bank # path: data/047_Bank/qa.parquet # - split: 048_Data # path: data/048_Data/qa.parquet # - split: 049_Boris # path: data/049_Boris/qa.parquet # - split: 050_ING # path: data/050_ING/qa.parquet # - split: 051_Pokemon # path: data/051_Pokemon/qa.parquet # - split: 052_Professional # path: data/052_Professional/qa.parquet # - split: 053_Patents # path: data/053_Patents/qa.parquet # - split: 054_Joe # path: data/054_Joe/qa.parquet # - split: 055_German # path: data/055_German/qa.parquet # - split: 056_Emoji # path: data/056_Emoji/qa.parquet # - split: 057_Spain # path: data/057_Spain/qa.parquet # - split: 058_US # path: data/058_US/qa.parquet # - split: 059_Second # path: data/059_Second/qa.parquet # - split: 060_Bakery # path: data/060_Bakery/qa.parquet # - split: 061_Disneyland # path: data/061_Disneyland/qa.parquet # - split: 062_Trump # path: data/062_Trump/qa.parquet # - split: 063_Influencers # path: data/063_Influencers/qa.parquet # - split: 064_Clustering # path: data/064_Clustering/qa.parquet # - split: 065_RFM # path: data/065_RFM/qa.parquet # - config_name: 001_Forbes # data_files: # - split: full # path: data/001_Forbes/all.parquet # - split: lite # path: data/001_Forbes/sample.parquet # - config_name: 002_Titanic # data_files: # - split: full # path: data/002_Titanic/all.parquet # - split: lite # path: data/002_Titanic/sample.parquet # - config_name: 003_Love # data_files: # - split: full # path: data/003_Love/all.parquet # - split: lite # path: data/003_Love/sample.parquet # - config_name: 004_Taxi # data_files: # - split: full # path: data/004_Taxi/all.parquet # - split: lite # path: data/004_Taxi/sample.parquet # - config_name: 005_NYC # data_files: # - split: full # path: data/005_NYC/all.parquet # - split: lite # path: data/005_NYC/sample.parquet # - config_name: 006_London # data_files: # - split: full # path: data/006_London/all.parquet # - split: lite # path: data/006_London/sample.parquet # - config_name: 007_Fifa # data_files: # - split: full # path: data/007_Fifa/all.parquet # - split: lite # path: data/007_Fifa/sample.parquet # - config_name: 008_Tornados # data_files: # - split: full # path: data/008_Tornados/all.parquet # - split: lite # path: data/008_Tornados/sample.parquet # - config_name: 009_Central # data_files: # - split: full # path: data/009_Central/all.parquet # - split: lite # path: data/009_Central/sample.parquet # - config_name: 010_ECommerce # data_files: # - split: full # path: data/010_ECommerce/all.parquet # - split: lite # path: data/010_ECommerce/sample.parquet # - config_name: 011_SF # data_files: # - split: full # path: data/011_SF/all.parquet # - split: lite # path: data/011_SF/sample.parquet # - config_name: 012_Heart # data_files: # - split: full # path: data/012_Heart/all.parquet # - split: lite # path: data/012_Heart/sample.parquet # - config_name: 013_Roller # data_files: # - split: full # path: data/013_Roller/all.parquet # - split: lite # path: data/013_Roller/sample.parquet # - config_name: 014_Airbnb # data_files: # - split: full # path: data/014_Airbnb/all.parquet # - split: lite # path: data/014_Airbnb/sample.parquet # - config_name: 015_Food # data_files: # - split: full # path: data/015_Food/all.parquet # - split: lite # path: data/015_Food/sample.parquet # - config_name: 016_Holiday # data_files: # - split: full # path: data/016_Holiday/all.parquet # - split: lite # path: data/016_Holiday/sample.parquet # - config_name: 017_Hacker # data_files: # - split: full # path: data/017_Hacker/all.parquet # - split: lite # path: data/017_Hacker/sample.parquet # - config_name: 018_Staff # data_files: # - split: full # path: data/018_Staff/all.parquet # - split: lite # path: data/018_Staff/sample.parquet # - config_name: 019_Aircraft # data_files: # - split: full # path: data/019_Aircraft/all.parquet # - split: lite # path: data/019_Aircraft/sample.parquet # - config_name: 020_Real # data_files: # - split: full # path: data/020_Real/all.parquet # - split: lite # path: data/020_Real/sample.parquet # - config_name: 021_Telco # data_files: # - split: full # path: data/021_Telco/all.parquet # - split: lite # path: data/021_Telco/sample.parquet # - config_name: 022_Airbnbs # data_files: # - split: full # path: data/022_Airbnbs/all.parquet # - split: lite # path: data/022_Airbnbs/sample.parquet # - config_name: 023_Climate # data_files: # - split: full # path: data/023_Climate/all.parquet # - split: lite # path: data/023_Climate/sample.parquet # - config_name: 024_Salary # data_files: # - split: full # path: data/024_Salary/all.parquet # - split: lite # path: data/024_Salary/sample.parquet # - config_name: 025_Data # data_files: # - split: full # path: data/025_Data/all.parquet # - split: lite # path: data/025_Data/sample.parquet # - config_name: 026_Predicting # data_files: # - split: full # path: data/026_Predicting/all.parquet # - split: lite # path: data/026_Predicting/sample.parquet # - config_name: 027_Supermarket # data_files: # - split: full # path: data/027_Supermarket/all.parquet # - split: lite # path: data/027_Supermarket/sample.parquet # - config_name: 028_Predict # data_files: # - split: full # path: data/028_Predict/all.parquet # - split: lite # path: data/028_Predict/sample.parquet # - config_name: 029_NYTimes # data_files: # - split: full # path: data/029_NYTimes/all.parquet # - split: lite # path: data/029_NYTimes/sample.parquet # - config_name: 030_Professionals # data_files: # - split: full # path: data/030_Professionals/all.parquet # - split: lite # path: data/030_Professionals/sample.parquet # - config_name: 031_Trustpilot # data_files: # - split: full # path: data/031_Trustpilot/all.parquet # - split: lite # path: data/031_Trustpilot/sample.parquet # - config_name: 032_Delicatessen # data_files: # - split: full # path: data/032_Delicatessen/all.parquet # - split: lite # path: data/032_Delicatessen/sample.parquet # - config_name: 033_Employee # data_files: # - split: full # path: data/033_Employee/all.parquet # - split: lite # path: data/033_Employee/sample.parquet # - config_name: 034_World # data_files: # - split: full # path: data/034_World/all.parquet # - split: lite # path: data/034_World/sample.parquet # - config_name: 035_Billboard # data_files: # - split: full # path: data/035_Billboard/all.parquet # - split: lite # path: data/035_Billboard/sample.parquet # - config_name: 036_US # data_files: # - split: full # path: data/036_US/all.parquet # - split: lite # path: data/036_US/sample.parquet # - config_name: 037_Ted # data_files: # - split: full # path: data/037_Ted/all.parquet # - split: lite # path: data/037_Ted/sample.parquet # - config_name: 038_Stroke # data_files: # - split: full # path: data/038_Stroke/all.parquet # - split: lite # path: data/038_Stroke/sample.parquet # - config_name: 039_Happy # data_files: # - split: full # path: data/039_Happy/all.parquet # - split: lite # path: data/039_Happy/sample.parquet # - config_name: 040_Speed # data_files: # - split: full # path: data/040_Speed/all.parquet # - split: lite # path: data/040_Speed/sample.parquet # - config_name: 041_Airline # data_files: # - split: full # path: data/041_Airline/all.parquet # - split: lite # path: data/041_Airline/sample.parquet # - config_name: 042_Predict # data_files: # - split: full # path: data/042_Predict/all.parquet # - split: lite # path: data/042_Predict/sample.parquet # - config_name: 043_Predict # data_files: # - split: full # path: data/043_Predict/all.parquet # - split: lite # path: data/043_Predict/sample.parquet # - config_name: 044_IMDb # data_files: # - split: full # path: data/044_IMDb/all.parquet # - split: lite # path: data/044_IMDb/sample.parquet # - config_name: 045_Predict # data_files: # - split: full # path: data/045_Predict/all.parquet # - split: lite # path: data/045_Predict/sample.parquet # - config_name: "046_120" # data_files: # - split: full # path: data/046_120/all.parquet # - split: lite # path: data/046_120/sample.parquet # - config_name: 047_Bank # data_files: # - split: full # path: data/047_Bank/all.parquet # - split: lite # path: data/047_Bank/sample.parquet # - config_name: 048_Data # data_files: # - split: full # path: data/048_Data/all.parquet # - split: lite # path: data/048_Data/sample.parquet # - config_name: 049_Boris # data_files: # - split: full # path: data/049_Boris/all.parquet # - split: lite # path: data/049_Boris/sample.parquet # - config_name: 050_ING # data_files: # - split: full # path: data/050_ING/all.parquet # - split: lite # path: data/050_ING/sample.parquet # - config_name: 051_Pokemon # data_files: # - split: full # path: data/051_Pokemon/all.parquet # - split: lite # path: data/051_Pokemon/sample.parquet # - config_name: 052_Professional # data_files: # - split: full # path: data/052_Professional/all.parquet # - split: lite # path: data/052_Professional/sample.parquet # - config_name: 053_Patents # data_files: # - split: full # path: data/053_Patents/all.parquet # - split: lite # path: data/053_Patents/sample.parquet # - config_name: 054_Joe # data_files: # - split: full # path: data/054_Joe/all.parquet # - split: lite # path: data/054_Joe/sample.parquet # - config_name: 055_German # data_files: # - split: full # path: data/055_German/all.parquet # - split: lite # path: data/055_German/sample.parquet # - config_name: 056_Emoji # data_files: # - split: full # path: data/056_Emoji/all.parquet # - split: lite # path: data/056_Emoji/sample.parquet # - config_name: 057_Spain # data_files: # - split: full # path: data/057_Spain/all.parquet # - split: lite # path: data/057_Spain/sample.parquet # - config_name: 058_US # data_files: # - split: full # path: data/058_US/all.parquet # - split: lite # path: data/058_US/sample.parquet # - config_name: 059_Second # data_files: # - split: full # path: data/059_Second/all.parquet # - split: lite # path: data/059_Second/sample.parquet # - config_name: 060_Bakery # data_files: # - split: full # path: data/060_Bakery/all.parquet # - split: lite # path: data/060_Bakery/sample.parquet # - config_name: 061_Disneyland # data_files: # - split: full # path: data/061_Disneyland/all.parquet # - split: lite # path: data/061_Disneyland/sample.parquet # - config_name: 062_Trump # data_files: # - split: full # path: data/062_Trump/all.parquet # - split: lite # path: data/062_Trump/sample.parquet # - config_name: 063_Influencers # data_files: # - split: full # path: data/063_Influencers/all.parquet # - split: lite # path: data/063_Influencers/sample.parquet # - config_name: 064_Clustering # data_files: # - split: full # path: data/064_Clustering/all.parquet # - split: lite # path: data/064_Clustering/sample.parquet # - config_name: 065_RFM # data_files: # - split: full # path: data/065_RFM/all.parquet # - split: lite # path: data/065_RFM/sample.parquet - config_name: semeval data_files: - split: train path: - data/001_Forbes/qa.parquet - data/002_Titanic/qa.parquet - data/003_Love/qa.parquet - data/004_Taxi/qa.parquet - data/005_NYC/qa.parquet - data/006_London/qa.parquet - data/007_Fifa/qa.parquet - data/008_Tornados/qa.parquet - data/009_Central/qa.parquet - data/010_ECommerce/qa.parquet - data/011_SF/qa.parquet - data/012_Heart/qa.parquet - data/013_Roller/qa.parquet - data/014_Airbnb/qa.parquet - data/015_Food/qa.parquet - data/016_Holiday/qa.parquet - data/017_Hacker/qa.parquet - data/018_Staff/qa.parquet - data/019_Aircraft/qa.parquet - data/020_Real/qa.parquet - data/021_Telco/qa.parquet - data/022_Airbnbs/qa.parquet - data/023_Climate/qa.parquet - data/024_Salary/qa.parquet - data/025_Data/qa.parquet - data/026_Predicting/qa.parquet - data/027_Supermarket/qa.parquet - data/028_Predict/qa.parquet - data/029_NYTimes/qa.parquet - data/030_Professionals/qa.parquet - data/031_Trustpilot/qa.parquet - data/032_Delicatessen/qa.parquet - data/033_Employee/qa.parquet - data/034_World/qa.parquet - data/035_Billboard/qa.parquet - data/036_US/qa.parquet - data/037_Ted/qa.parquet - data/038_Stroke/qa.parquet - data/039_Happy/qa.parquet - data/040_Speed/qa.parquet - data/041_Airline/qa.parquet - data/042_Predict/qa.parquet - data/043_Predict/qa.parquet - data/044_IMDb/qa.parquet - data/045_Predict/qa.parquet - data/046_120/qa.parquet - data/047_Bank/qa.parquet - data/048_Data/qa.parquet - data/049_Boris/qa.parquet - split: dev path: - data/050_ING/qa.parquet - data/051_Pokemon/qa.parquet - data/052_Professional/qa.parquet - data/053_Patents/qa.parquet - data/054_Joe/qa.parquet - data/055_German/qa.parquet - data/056_Emoji/qa.parquet - data/057_Spain/qa.parquet - data/058_US/qa.parquet - data/059_Second/qa.parquet - data/060_Bakery/qa.parquet - data/061_Disneyland/qa.parquet - data/062_Trump/qa.parquet - data/063_Influencers/qa.parquet - data/064_Clustering/qa.parquet - data/065_RFM/qa.parquet --- # 💾🏋️💾 DataBench 💾🏋️💾 This repository contains the original 65 datasets used for the paper [Question Answering over Tabular Data with DataBench: A Large-Scale Empirical Evaluation of LLMs](https://huggingface.co/datasets/cardiffnlp/databench/resolve/main/Databench-LREC-Coling-2024.pdf) which appeared in LREC-COLING 2024. Large Language Models (LLMs) are showing emerging abilities, and one of the latest recognized ones is tabular reasoning in question answering on tabular data. Although there are some available datasets to assess question answering systems on tabular data, they are not large and diverse enough to evaluate this new ability of LLMs. To this end, we provide a corpus of 65 real world datasets, with 3,269,975 and 1615 columns in total, and 1300 questions to evaluate your models for the task of QA over Tabular Data. ## Usage ```python from datasets import load_dataset # Load all QA pairs all_qa = load_dataset("cardiffnlp/databench", name="qa", split="train") # Load SemEval 2025 task 8 Question-Answer splits semeval_train_qa = load_dataset("cardiffnlp/databench", name="semeval", split="train") semeval_dev_qa = load_dataset("cardiffnlp/databench", name="semeval", split="dev") ``` You can use any of the individual [integrated libraries](https://huggingface.co/docs/hub/datasets-libraries#libraries) to load the actual data where the answer is to be retrieved. For example, using pandas in Python: ```python import pandas as pd # "001_Forbes", the id of the dataset ds_id = all_qa['dataset'][0] # full dataset df = pd.read_parquet(f"hf://datasets/cardiffnlp/databench/data/{ds_id}/all.parquet") # sample dataset df = pd.read_parquet(f"hf://datasets/cardiffnlp/databench/data/{ds_id}/sample.parquet") ``` ## 📚 Datasets By clicking on each name in the table below, you will be able to explore each dataset. | | Name | Rows | Cols | Domain | Source (Reference) | |---:|:-------------------------------|-------:|-------:|:---------------------------|:-----------------------------------------------------------------------------------------------------------------------------------| | 1 | [Forbes](https://public.graphext.com/0b211530c7e213d3/index.html?section=data) | 2668 | 17 | Business | [Forbes](https://www.forbes.com/billionaires/)| | 2 | [Titanic](https://public.graphext.com/8577225c5ffd88fd/index.html) | 887 | 8 | Travel and Locations | [Kaggle](https://www.kaggle.com/competitions/titanic/data)| | 3 | [Love](https://public.graphext.com/be7a566b0c485916/index.html) | 373 | 35 | Social Networks and Surveys | [Graphext](https://public.graphext.com/1de78f6820cfd5ba/index.html) | | 4 | [Taxi](https://public.graphext.com/bcee13c23070f333/index.html) | 100000 | 20 | Travel and Locations | [Kaggle](https://www.kaggle.com/competitions/nyc-taxi-trip-duration/overview) | | 5 | [NYC Calls](https://public.graphext.com/1ce2f5fae408621e/index.html) | 100000 | 46 | Business | [City of New York](https://data.cityofnewyork.us/Social-Services/NYC-311-Data/jrb2-thup) | | 6 | [London Airbnbs](https://public.graphext.com/6bbf4bbd3ff279c0/index.html) | 75241 | 74 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/labdmitriy/airbnb) | | 7 | [Fifa](https://public.graphext.com/37bca51494c10a79/index.html) | 14620 | 59 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/stefanoleone992/fifa-21-complete-player-dataset) | | 8 | [Tornados](https://public.graphext.com/4be9872e031199c3/index.html) | 67558 | 14 | Health | [Kaggle](https://www.kaggle.com/datasets/danbraswell/us-tornado-dataset-1950-2021) | | 9 | [Central Park](https://public.graphext.com/7b3d3a4d7bf1e9b5/index.html) | 56245 | 6 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/danbraswell/new-york-city-weather-18692022) | | 10 | [ECommerce Reviews](https://public.graphext.com/a5b8911b215958ad/index.html) | 23486 | 10 | Business | [Kaggle](https://www.kaggle.com/datasets/nicapotato/womens-ecommerce-clothing-reviews) | | 11 | [SF Police](https://public.graphext.com/ab815ab14f88115c/index.html) | 713107 | 35 | Social Networks and Surveys | [US Gov](https://catalog.data.gov/dataset/police-department-incident-reports-2018-to-present) | | 12 | [Heart Failure](https://public.graphext.com/245cec64075f5542/index.html) | 918 | 12 | Health | [Kaggle](https://www.kaggle.com/datasets/fedesoriano/heart-failure-prediction) | | 13 | [Roller Coasters](https://public.graphext.com/1e550e6c24fc1930/index.html) | 1087 | 56 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/robikscube/rollercoaster-database) | | 14 | [Madrid Airbnbs](https://public.graphext.com/77265ea3a63e650f/index.html) | 20776 | 75 | Travel and Locations | [Inside Airbnb](http://data.insideairbnb.com/spain/comunidad-de-madrid/madrid/2023-09-07/data/listings.parquet.gz) | | 15 | [Food Names](https://public.graphext.com/5aad4c5d6ef140b3/index.html) | 906 | 4 | Business | [Data World](https://data.world/alexandra/generic-food-database) | | 16 | [Holiday Package Sales](https://public.graphext.com/fbc34d3f24282e46/index.html) | 4888 | 20 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/susant4learning/holiday-package-purchase-prediction) | | 17 | [Hacker News](https://public.graphext.com/f20501a9d616b5a5/index.html) | 9429 | 20 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/hacker-news/hacker-news) | | 18 | [Staff Satisfaction](https://public.graphext.com/6822ac1ce6307fec/index.html) | 14999 | 11 | Business | [Kaggle](https://www.kaggle.com/datasets/mohamedharris/employee-satisfaction-index-dataset) | | 19 | [Aircraft Accidents](https://public.graphext.com/1802117b1b14f5c5/index.html) | 23519 | 23 | Health | [Kaggle](https://www.kaggle.com/datasets/ramjasmaurya/aviation-accidents-history1919-april-2022) | | 20 | [Real Estate Madrid](https://public.graphext.com/5f83ec219a7ea84f/index.html) | 26026 | 59 | Business | [Idealista](https://public.graphext.com/5f83ec219a7ea84f/index.html) | | 21 | [Telco Customer Churn](https://public.graphext.com/362cd8e3e96f70d4/index.html) | 7043 | 21 | Business | [Kaggle](https://www.kaggle.com/datasets/blastchar/telco-customer-churn) | | 22 | [Airbnbs Listings NY](https://public.graphext.com/77265ea3a63e650f/index.html) | 37012 | 33 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/dgomonov/new-york-city-airbnb-open-data) | | 23 | [Climate in Madrid](https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data) | 36858 | 26 | Travel and Locations | [AEMET](https://public.graphext.com/83a75b4f1cea8df4/index.html?section=data) | | 24 | [Salary Survey Spain 2018](https://public.graphext.com/24d1e717ba01aa3d/index.html) | 216726 | 29 | Business | [INE](ine.es) | | 25 | [Data Driven SEO ](https://public.graphext.com/4e5b1cac9ebdfa44/index.html) | 62 | 5 | Business | [Graphext](https://www.graphext.com/post/data-driven-seo-a-keyword-optimization-guide-using-web-scraping-co-occurrence-analysis-graphext-deepnote-adwords) | | 26 | [Predicting Wine Quality](https://public.graphext.com/de04acf5d18a9aea/index.html) | 1599 | 12 | Business | [Kaggle](https://www.kaggle.com/datasets/yasserh/wine-quality-dataset) | | 27 | [Supermarket Sales](https://public.graphext.com/9a6742da6a8d8f7f/index.html) | 1000 | 17 | Business | [Kaggle](https://www.kaggle.com/datasets/aungpyaeap/supermarket-sales) | | 28 | [Predict Diabetes](https://public.graphext.com/def4bada27af324c/index.html) | 768 | 9 | Health | [Kaggle](https://www.kaggle.com/datasets/iammustafatz/diabetes-prediction-dataset) | | 29 | [NYTimes World In 2021](https://public.graphext.com/af4c8eef1757973c/index.html?section=data) | 52588 | 5 | Travel and Locations | [New York Times](https://public.graphext.com/af4c8eef1757973c/index.html) | | 30 | [Professionals Kaggle Survey](https://public.graphext.com/3a2e87f90363a85d/index.html) | 19169 | 64 | Business | [Kaggle](https://www.kaggle.com/c/kaggle-survey-2021/data) | | 31 | [Trustpilot Reviews](https://public.graphext.com/367e29432331fbfd/index.html?section=data) | 8020 | 6 | Business | [TrustPilot](https://public.graphext.com/367e29432331fbfd/index.html?section=data) | | 32 | [Delicatessen Customers](https://public.graphext.com/a1687589fbde07bc/index.html) | 2240 | 29 | Business | [Kaggle](https://www.kaggle.com/datasets/rodsaldanha/arketing-campaign) | | 33 | [Employee Attrition](https://public.graphext.com/07a91a15ecf2b8f6/index.html) | 14999 | 11 | Business | [Kaggle(modified)](https://www.kaggle.com/datasets/pavan9065/predicting-employee-attrition) | | 34 | [World Happiness Report 2020](https://public.graphext.com/754c83ff0a7ba087/index.html) | 153 | 20 | Social Networks and Surveys | [World Happiness](https://worldhappiness.report/data/) | | 35 | [Billboard Lyrics](https://public.graphext.com/7e0b009e8d0af719/index.html) | 5100 | 6 | Sports and Entertainment | [Brown University](https://cs.brown.edu/courses/cs100/students/project11/) | | 36 | [US Migrations 2012-2016](https://public.graphext.com/dbdadf87a5c21695/index.html) | 288300 | 9 | Social Networks and Surveys | [US Census](https://www.census.gov/topics/population/migration/guidance/county-to-county-migration-flows.html) | | 37 | [Ted Talks](https://public.graphext.com/07e48466fb670904/index.html) | 4005 | 19 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ashishjangra27/ted-talks) | | 38 | [Stroke Likelihood](https://public.graphext.com/20ccfee9e84948e3/index.html) | 5110 | 12 | Health | [Kaggle](https://www.kaggle.com/datasets/kamilpytlak/personal-key-indicators-of-heart-disease) | | 39 | [Happy Moments](https://public.graphext.com/9b86efff48989701/index.html) | 100535 | 11 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ritresearch/happydb) | | 40 | [Speed Dating](https://public.graphext.com/f1912daad7870be0/index.html) | 8378 | 123 | Social Networks and Surveys | [Kaggle](https://www.kaggle.com/datasets/ulrikthygepedersen/speed-dating) | | 41 | [Airline Mentions X (former Twitter)](https://public.graphext.com/29cb7f73f6e17a38/index.html) | 14640 | 15 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/7e6999327d1f83fd/index.html) | | 42 | [Predict Student Performance](https://public.graphext.com/def4bada27af324c/index.html) | 395 | 33 | Business | [Kaggle](https://www.kaggle.com/datasets/impapan/student-performance-data-set) | | 43 | [Loan Defaults](https://public.graphext.com/0c7fb68ab8071a1f/index.html) | 83656 | 20 | Business | [SBA](https://www.kaggle.com/datasets/mirbektoktogaraev/should-this-loan-be-approved-or-denied) | | 44 | [IMDb Movies](https://public.graphext.com/e23e33774872c496/index.html) | 85855 | 22 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/harshitshankhdhar/imdb-dataset-of-top-1000-movies-and-tv-shows) | | 45 | [Spotify Song Popularity](https://public.graphext.com/def4bada27af324c/index.html) | 21000 | 19 | Sports and Entertainment | [Spotify](https://www.kaggle.com/datasets/tomigelo/spotify-audio-features) | | 46 | [120 Years Olympics](https://public.graphext.com/e57d5e2f172c9a99/index.html) | 271116 | 15 | Sports and Entertainment | [Kaggle](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results) | | 47 | [Bank Customer Churn](https://public.graphext.com/e8f7aeacd209f74a/index.html) | 7088 | 15 | Business | [Kaggle](https://www.kaggle.com/datasets/mathchi/churn-for-bank-customers) | | 48 | [Data Science Salary Data](https://public.graphext.com/4e5b1cac9ebdfa44/index.html) | 742 | 28 | Business | [Kaggle](https://www.kaggle.com/datasets/ruchi798/data-science-job-salaries) | | 49 | [Boris Johnson UK PM Tweets](https://public.graphext.com/f6623a1ca0f41c8e/index.html) | 3220 | 34 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/f6623a1ca0f41c8e/index.html) | | 50 | [ING 2019 X Mentions](https://public.graphext.com/075030310aa702c6/index.html) | 7244 | 22 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/075030310aa702c6/index.html) | | 51 | [Pokemon Features](https://public.graphext.com/f30d4d863a2e6b01/index.html) | 1072 | 13 | Business | [Kaggle](https://www.kaggle.com/datasets/rounakbanik/pokemon) | | 52 | [Professional Map](https://public.graphext.com/70af2240cb751968/index.html) | 1227 | 12 | Business | [Kern et al, PNAS'20](https://github.com/behavioral-ds/VocationMap) | | 53 | [Google Patents](https://public.graphext.com/a262300e31874716/index.html) | 9999 | 20 | Business | [BigQuery](https://www.kaggle.com/datasets/bigquery/patents/data) | | 54 | [Joe Biden Tweets](https://public.graphext.com/33fa2efa41541ab1/index.html) | 491 | 34 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/339cee259f0a9b32/index.html?section=data) | 55 | [German Loans](https://public.graphext.com/d3f5e425e9d4b0a1/index.html) | 1000 | 18 | Business | [Kaggle](https://www.kaggle.com/datasets/uciml/german-credit/data) | | 56 | [Emoji Diet](https://public.graphext.com/e721cc7d790c06d4/index.html) | 58 | 35 | Health | [Kaggle](https://www.kaggle.com/datasets/ofrancisco/emoji-diet-nutritional-data-sr28) | | 57 | [Spain Survey 2015](https://public.graphext.com/90ca7539b160fdfa/index.html?section=data) | 20000 | 45 | Social Networks and Surveys | [CIS](https://public.graphext.com/90ca7539b160fdfa/index.html?section=data) | | 58 | [US Polls 2020](https://public.graphext.com/dbdadf87a5c21695/index.html) | 3523 | 52 | Social Networks and Surveys | [Brandwatch](https://www.brandwatch.com/p/us-election-raw-polling-data/) | | 59 | [Second Hand Cars](https://public.graphext.com/543d0c49d7120ca0/index.html) | 50000 | 21 | Business | [DataMarket](https://www.kaggle.com/datasets/datamarket/venta-de-coches) | | 60 | [Bakery Purchases](https://public.graphext.com/6f2102e80f47a192/index.html) | 20507 | 5 | Business | [Kaggle](https://www.kaggle.com/code/xvivancos/market-basket-analysis/report) | | 61 | [Disneyland Customer Reviews](https://public.graphext.com/b1037bb566b7b316/index.html) | 42656 | 6 | Travel and Locations | [Kaggle](https://www.kaggle.com/datasets/arushchillar/disneyland-reviews) | | 62 | [Trump Tweets](https://public.graphext.com/7aff94c3b7f159fc/index.html) | 15039 | 20 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/be903c098a90e46f/index.html?section=data) | | 63 | [Influencers](https://public.graphext.com/e097f1ea03d761a9/index.html) | 1039 | 14 | Social Networks and Surveys | [X (former Twitter)](https://public.graphext.com/e097f1ea03d761a9/index.html) | | 64 | [Clustering Zoo Animals](https://public.graphext.com/d1b66902e46a712a/index.html) | 101 | 18 | Health | [Kaggle](https://www.kaggle.com/datasets/jirkadaberger/zoo-animals) | | 65 | [RFM Analysis](https://public.graphext.com/4db2e54e29006a21/index.html) | 541909 | 8 | Business | [UCI ML](https://www.kaggle.com/datasets/carrie1/ecommerce-data) | ## 🏗️ Folder structure Each folder represents one dataset. You will find the following files within: * all.parquet: the processed data, with each column tagged with our typing system, in [parquet](https://arrow.apache.org/docs/python/parquet.html). * qa.parquet: contains the human-made set of questions, tagged by type and columns used, for the dataset (sample_answer indicates the answers for DataBench lite) * sample.parquet: sample containing 20 rows of the original dataset (DataBench lite) * info.yml: additional information about the dataset ## 🗂️ Column typing system In an effort to map the stage for later analysis, we have categorized the columns by type. This information allows us to segment different kinds of data so that we can subsequently analyze the model's behavior on each column type separately. All parquet files have been casted to their smallest viable data type using the open source [Lector](https://github.com/graphext/lector) reader. What this means is that in the data types we have more granular information that allows us to know if the column contains NaNs or not (following panda’s convention of Int vs int), as well as whether small numerical values contain negatives (Uint vs int) and their range. We also have dates with potential timezone information (although for now they’re all UTC), as well as information about categories’ cardinality coming from the arrow types. In the table below you can see all the data types assigned to each column, as well as the number of columns for each type. The most common data types are numbers and categories with 1336 columns of the total of 1615 included in DataBench. These are followed by some other more rare types as urls, booleans, dates or lists of elements. | Type | Columns | Example | | -------------- | ------- | ----------------------- | | number | 788 | 55 | | category | 548 | apple | | date | 50 | 1970-01-01 | | text | 46 | A red fox ran... | | url | 31 | google.com | | boolean | 18 | True | | list[number] | 14 | [1,2,3] | | list[category] | 112 | [apple, orange, banana] | | list[url] | 8 | [google.com, apple.com] | ## 🔗 Reference You can download the paper [here](https://huggingface.co/datasets/cardiffnlp/databench/resolve/main/Databench-LREC-Coling-2024.pdf). If you use this resource, please use the following reference: ``` @inproceedings{oses-etal-2024-databench, title = "Question Answering over Tabular Data with DataBench: A Large-Scale Empirical Evaluation of LLMs", author = "Jorge Osés Grijalba and Luis Alfonso Ureña-López and Eugenio Martínez Cámara and Jose Camacho-Collados", booktitle = "Proceedings of LREC-COLING 2024", year = "2024", address = "Turin, Italy" } ```

asahi417/seamless-align-enA-esA.speaker-embedding.w2vbert-600m

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9399288470 num_examples: 2178 download_size: 9425104182 dataset_size: 9399288470 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - 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name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7153706314 num_examples: 2129 download_size: 7176384873 dataset_size: 7153706314 - config_name: subset_106 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7040645251 num_examples: 2085 download_size: 7063107129 dataset_size: 7040645251 - config_name: subset_107 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7015460332 num_examples: 2102 download_size: 7037561444 dataset_size: 7015460332 - config_name: subset_108 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 7198938657 num_examples: 2143 download_size: 7221561752 dataset_size: 7198938657 - config_name: subset_109 features: - 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split: train path: subset_187/train-* - config_name: subset_188 data_files: - split: train path: subset_188/train-* - config_name: subset_189 data_files: - split: train path: subset_189/train-* - config_name: subset_19 data_files: - split: train path: subset_19/train-* - config_name: subset_190 data_files: - split: train path: subset_190/train-* - config_name: subset_191 data_files: - split: train path: subset_191/train-* - config_name: subset_192 data_files: - split: train path: subset_192/train-* - config_name: subset_193 data_files: - split: train path: subset_193/train-* - config_name: subset_194 data_files: - split: train path: subset_194/train-* - config_name: subset_195 data_files: - split: train path: subset_195/train-* - config_name: subset_196 data_files: - split: train path: subset_196/train-* - config_name: subset_197 data_files: - split: train path: subset_197/train-* - config_name: subset_198 data_files: - split: train path: subset_198/train-* - config_name: subset_199 data_files: - split: train path: subset_199/train-* - config_name: subset_2 data_files: - split: train path: subset_2/train-* - config_name: subset_20 data_files: - split: train path: subset_20/train-* - config_name: subset_200 data_files: - split: train path: subset_200/train-* - config_name: subset_201 data_files: - split: train path: subset_201/train-* - config_name: subset_202 data_files: - split: train path: subset_202/train-* - config_name: subset_203 data_files: - split: train path: subset_203/train-* - config_name: subset_204 data_files: - split: train path: subset_204/train-* - config_name: subset_205 data_files: - split: train path: subset_205/train-* - config_name: subset_206 data_files: - split: train path: subset_206/train-* - config_name: subset_207 data_files: - split: train path: subset_207/train-* - config_name: subset_208 data_files: - split: train path: subset_208/train-* - config_name: subset_209 data_files: - split: train path: subset_209/train-* - config_name: subset_21 data_files: - split: train path: subset_21/train-* - config_name: subset_210 data_files: - split: train path: subset_210/train-* - config_name: subset_211 data_files: - split: train path: subset_211/train-* - config_name: subset_212 data_files: - split: train path: subset_212/train-* - config_name: subset_213 data_files: - split: train path: subset_213/train-* - config_name: subset_214 data_files: - split: train path: subset_214/train-* - config_name: subset_215 data_files: - split: train path: subset_215/train-* - config_name: subset_216 data_files: - split: train path: subset_216/train-* - config_name: subset_217 data_files: - split: train path: subset_217/train-* - config_name: subset_218 data_files: - split: train path: subset_218/train-* - config_name: subset_219 data_files: - split: train path: subset_219/train-* - config_name: subset_22 data_files: - split: train path: subset_22/train-* - config_name: subset_220 data_files: - split: train path: subset_220/train-* - config_name: subset_221 data_files: - split: train path: subset_221/train-* - config_name: subset_222 data_files: - split: train path: subset_222/train-* - config_name: subset_223 data_files: - split: train path: subset_223/train-* - config_name: subset_224 data_files: - split: train path: subset_224/train-* - config_name: subset_225 data_files: - split: train path: subset_225/train-* - config_name: subset_226 data_files: - split: train path: subset_226/train-* - config_name: subset_227 data_files: - split: train path: subset_227/train-* - config_name: subset_228 data_files: - split: train path: subset_228/train-* - config_name: subset_229 data_files: - split: train path: subset_229/train-* - config_name: subset_23 data_files: - split: train path: subset_23/train-* - config_name: subset_230 data_files: - split: train path: subset_230/train-* - config_name: subset_231 data_files: - split: train path: subset_231/train-* - config_name: subset_232 data_files: - split: train path: subset_232/train-* - config_name: subset_233 data_files: - split: train path: subset_233/train-* - config_name: subset_234 data_files: - split: train path: subset_234/train-* - config_name: subset_235 data_files: - split: train path: subset_235/train-* - config_name: subset_236 data_files: - split: train path: subset_236/train-* - config_name: subset_237 data_files: - split: train path: subset_237/train-* - config_name: subset_238 data_files: - split: train path: subset_238/train-* - config_name: subset_239 data_files: - split: train path: subset_239/train-* - config_name: subset_24 data_files: - split: train path: subset_24/train-* - config_name: subset_240 data_files: - split: train path: subset_240/train-* - config_name: subset_241 data_files: - split: train path: subset_241/train-* - config_name: subset_242 data_files: - split: train path: subset_242/train-* - config_name: subset_243 data_files: - split: train path: subset_243/train-* - config_name: subset_244 data_files: - split: train path: subset_244/train-* - config_name: subset_245 data_files: - split: train path: subset_245/train-* - config_name: subset_246 data_files: - split: train path: subset_246/train-* - config_name: subset_247 data_files: - split: train path: subset_247/train-* - config_name: subset_248 data_files: - split: train path: subset_248/train-* - config_name: subset_249 data_files: - split: train path: subset_249/train-* - config_name: subset_25 data_files: - split: train path: subset_25/train-* - config_name: subset_250 data_files: - split: train path: subset_250/train-* - config_name: subset_251 data_files: - split: train path: subset_251/train-* - config_name: subset_252 data_files: - split: train path: subset_252/train-* - config_name: subset_253 data_files: - split: train path: subset_253/train-* - config_name: subset_254 data_files: - split: train path: subset_254/train-* - config_name: subset_255 data_files: - split: train path: subset_255/train-* - config_name: subset_256 data_files: - split: train path: subset_256/train-* - config_name: subset_257 data_files: - split: train path: subset_257/train-* - config_name: subset_258 data_files: - split: train path: subset_258/train-* - config_name: subset_259 data_files: - split: train path: subset_259/train-* - config_name: subset_26 data_files: - split: train path: subset_26/train-* - config_name: subset_260 data_files: - split: train path: subset_260/train-* - config_name: subset_261 data_files: - split: train path: subset_261/train-* - config_name: subset_262 data_files: - split: train path: subset_262/train-* - config_name: subset_263 data_files: - split: train path: subset_263/train-* - config_name: subset_264 data_files: - split: train path: subset_264/train-* - config_name: subset_265 data_files: - split: train path: subset_265/train-* - config_name: subset_266 data_files: - split: train path: subset_266/train-* - config_name: subset_267 data_files: - split: train path: subset_267/train-* - config_name: subset_268 data_files: - split: train path: subset_268/train-* - config_name: subset_269 data_files: - split: train path: subset_269/train-* - config_name: subset_27 data_files: - split: train path: subset_27/train-* - config_name: subset_270 data_files: - split: train path: subset_270/train-* - config_name: subset_271 data_files: - split: train path: subset_271/train-* - config_name: subset_272 data_files: - split: train path: subset_272/train-* - config_name: subset_273 data_files: - split: train path: subset_273/train-* - config_name: subset_274 data_files: - split: train path: subset_274/train-* - config_name: subset_275 data_files: - split: train path: subset_275/train-* - config_name: subset_276 data_files: - split: train path: subset_276/train-* - config_name: subset_277 data_files: - split: train path: subset_277/train-* - config_name: subset_278 data_files: - split: train path: subset_278/train-* - config_name: subset_279 data_files: - split: train path: subset_279/train-* - config_name: subset_28 data_files: - split: train path: subset_28/train-* - config_name: subset_280 data_files: - split: train path: subset_280/train-* - config_name: subset_281 data_files: - split: train path: subset_281/train-* - config_name: subset_282 data_files: - split: train path: subset_282/train-* - config_name: subset_283 data_files: - split: train path: subset_283/train-* - config_name: subset_284 data_files: - split: train path: subset_284/train-* - config_name: subset_285 data_files: - split: train path: subset_285/train-* - config_name: subset_286 data_files: - split: train path: subset_286/train-* - config_name: subset_287 data_files: - split: train path: subset_287/train-* - config_name: subset_288 data_files: - split: train path: subset_288/train-* - config_name: subset_289 data_files: - split: train path: subset_289/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_290 data_files: - split: train path: subset_290/train-* - config_name: subset_291 data_files: - split: train path: subset_291/train-* - config_name: subset_292 data_files: - split: train path: subset_292/train-* - config_name: subset_293 data_files: - split: train path: subset_293/train-* - config_name: subset_294 data_files: - split: train path: subset_294/train-* - config_name: subset_295 data_files: - split: train path: subset_295/train-* - config_name: subset_296 data_files: - split: train path: subset_296/train-* - config_name: subset_297 data_files: - split: train path: subset_297/train-* - config_name: subset_298 data_files: - split: train path: subset_298/train-* - config_name: subset_299 data_files: - split: train path: subset_299/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_300 data_files: - split: train path: subset_300/train-* - config_name: subset_301 data_files: - split: train path: subset_301/train-* - config_name: subset_302 data_files: - split: train path: subset_302/train-* - config_name: subset_303 data_files: - split: train path: subset_303/train-* - config_name: subset_304 data_files: - split: train path: subset_304/train-* - config_name: subset_305 data_files: - split: train path: subset_305/train-* - config_name: subset_306 data_files: - split: train path: subset_306/train-* - config_name: subset_307 data_files: - split: train path: subset_307/train-* - config_name: subset_308 data_files: - split: train path: subset_308/train-* - config_name: subset_309 data_files: - split: train path: subset_309/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_310 data_files: - split: train path: subset_310/train-* - config_name: subset_311 data_files: - split: train path: subset_311/train-* - config_name: subset_312 data_files: - split: train path: subset_312/train-* - config_name: subset_313 data_files: - split: train path: subset_313/train-* - config_name: subset_314 data_files: - split: train path: subset_314/train-* - config_name: subset_315 data_files: - split: train path: subset_315/train-* - config_name: subset_316 data_files: - split: train path: subset_316/train-* - config_name: subset_317 data_files: - split: train path: subset_317/train-* - config_name: subset_318 data_files: - split: train path: subset_318/train-* - config_name: subset_319 data_files: - split: train path: subset_319/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_320 data_files: - split: train path: subset_320/train-* - config_name: subset_321 data_files: - split: train path: subset_321/train-* - config_name: subset_322 data_files: - split: train path: subset_322/train-* - config_name: subset_323 data_files: - split: train path: subset_323/train-* - config_name: subset_324 data_files: - split: train path: subset_324/train-* - config_name: subset_325 data_files: - split: train path: subset_325/train-* - config_name: subset_326 data_files: - split: train path: subset_326/train-* - config_name: subset_327 data_files: - split: train path: subset_327/train-* - config_name: subset_328 data_files: - split: train path: subset_328/train-* - config_name: subset_329 data_files: - split: train path: subset_329/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_330 data_files: - split: train path: subset_330/train-* - config_name: subset_331 data_files: - split: train path: subset_331/train-* - config_name: subset_332 data_files: - split: train path: subset_332/train-* - config_name: subset_333 data_files: - split: train path: subset_333/train-* - config_name: subset_334 data_files: - split: train path: subset_334/train-* - config_name: subset_335 data_files: - split: train path: subset_335/train-* - config_name: subset_336 data_files: - split: train path: subset_336/train-* - config_name: subset_337 data_files: - split: train path: subset_337/train-* - config_name: subset_338 data_files: - split: train path: subset_338/train-* - config_name: subset_339 data_files: - split: train path: subset_339/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_340 data_files: - split: train path: subset_340/train-* - config_name: subset_341 data_files: - split: train path: subset_341/train-* - config_name: subset_342 data_files: - split: train path: subset_342/train-* - config_name: subset_343 data_files: - split: train path: subset_343/train-* - config_name: subset_344 data_files: - split: train path: subset_344/train-* - config_name: subset_345 data_files: - split: train path: subset_345/train-* - config_name: subset_346 data_files: - split: train path: subset_346/train-* - config_name: subset_347 data_files: - split: train path: subset_347/train-* - config_name: subset_348 data_files: - split: train path: subset_348/train-* - config_name: subset_349 data_files: - split: train path: subset_349/train-* - config_name: subset_35 data_files: - split: train path: subset_35/train-* - config_name: subset_350 data_files: - split: train path: subset_350/train-* - config_name: subset_351 data_files: - split: train path: subset_351/train-* - config_name: subset_352 data_files: - split: train path: subset_352/train-* - config_name: subset_353 data_files: - split: train path: subset_353/train-* - config_name: subset_354 data_files: - split: train path: subset_354/train-* - config_name: subset_355 data_files: - split: train path: subset_355/train-* - config_name: subset_356 data_files: - split: train path: subset_356/train-* - config_name: subset_357 data_files: - split: train path: subset_357/train-* - config_name: subset_358 data_files: - split: train path: subset_358/train-* - config_name: subset_359 data_files: - split: train path: subset_359/train-* - config_name: subset_36 data_files: - split: train path: subset_36/train-* - config_name: subset_360 data_files: - split: train path: subset_360/train-* - config_name: subset_361 data_files: - split: train path: subset_361/train-* - config_name: subset_362 data_files: - split: train path: subset_362/train-* - config_name: subset_363 data_files: - split: train path: subset_363/train-* - config_name: subset_364 data_files: - split: train path: subset_364/train-* - config_name: subset_365 data_files: - split: train path: subset_365/train-* - config_name: subset_366 data_files: - split: train path: subset_366/train-* - config_name: subset_367 data_files: - split: train path: subset_367/train-* - config_name: subset_368 data_files: - split: train path: subset_368/train-* - config_name: subset_369 data_files: - split: train path: subset_369/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_370 data_files: - split: train path: subset_370/train-* - config_name: subset_371 data_files: - split: train path: subset_371/train-* - config_name: subset_372 data_files: - split: train path: subset_372/train-* - config_name: subset_373 data_files: - split: train path: subset_373/train-* - config_name: subset_374 data_files: - split: train path: subset_374/train-* - config_name: subset_375 data_files: - split: train path: subset_375/train-* - config_name: subset_376 data_files: - split: train path: subset_376/train-* - config_name: subset_377 data_files: - split: train path: subset_377/train-* - config_name: subset_378 data_files: - split: train path: subset_378/train-* - config_name: subset_379 data_files: - split: train path: subset_379/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_380 data_files: - split: train path: subset_380/train-* - config_name: subset_381 data_files: - split: train path: subset_381/train-* - config_name: subset_382 data_files: - split: train path: subset_382/train-* - config_name: subset_383 data_files: - split: train path: subset_383/train-* - config_name: subset_384 data_files: - split: train path: subset_384/train-* - config_name: subset_385 data_files: - split: train path: subset_385/train-* - config_name: subset_386 data_files: - split: train path: subset_386/train-* - config_name: subset_387 data_files: - split: train path: subset_387/train-* - config_name: subset_388 data_files: - split: train path: subset_388/train-* - config_name: subset_389 data_files: - split: train path: subset_389/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_390 data_files: - split: train path: subset_390/train-* - config_name: subset_391 data_files: - split: train path: subset_391/train-* - config_name: subset_392 data_files: - split: train path: subset_392/train-* - config_name: subset_393 data_files: - split: train path: subset_393/train-* - config_name: subset_394 data_files: - split: train path: subset_394/train-* - config_name: subset_395 data_files: - split: train path: subset_395/train-* - config_name: subset_396 data_files: - split: train path: subset_396/train-* - config_name: subset_397 data_files: - split: train path: subset_397/train-* - config_name: subset_398 data_files: - split: train path: subset_398/train-* - config_name: subset_399 data_files: - split: train path: subset_399/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_400 data_files: - split: train path: subset_400/train-* - config_name: subset_401 data_files: - split: train path: subset_401/train-* - config_name: subset_402 data_files: - split: train path: subset_402/train-* - config_name: subset_403 data_files: - split: train path: subset_403/train-* - config_name: subset_404 data_files: - split: train path: subset_404/train-* - config_name: subset_405 data_files: - split: train path: subset_405/train-* - config_name: subset_406 data_files: - split: train path: subset_406/train-* - config_name: subset_407 data_files: - split: train path: subset_407/train-* - config_name: subset_408 data_files: - split: train path: subset_408/train-* - config_name: subset_409 data_files: - split: train path: subset_409/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_410 data_files: - split: train path: subset_410/train-* - config_name: subset_411 data_files: - split: train path: subset_411/train-* - config_name: subset_412 data_files: - split: train path: subset_412/train-* - config_name: subset_413 data_files: - split: train path: subset_413/train-* - config_name: subset_414 data_files: - split: train path: subset_414/train-* - config_name: subset_415 data_files: - split: train path: subset_415/train-* - config_name: subset_416 data_files: - split: train path: subset_416/train-* - config_name: subset_417 data_files: - split: train path: subset_417/train-* - config_name: subset_418 data_files: - split: train path: subset_418/train-* - config_name: subset_419 data_files: - split: train path: subset_419/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_420 data_files: - split: train path: subset_420/train-* - config_name: subset_421 data_files: - split: train path: subset_421/train-* - config_name: subset_422 data_files: - split: train path: subset_422/train-* - config_name: subset_423 data_files: - split: train path: subset_423/train-* - config_name: subset_424 data_files: - split: train path: subset_424/train-* - config_name: subset_425 data_files: - split: train path: subset_425/train-* - config_name: subset_426 data_files: - split: train path: subset_426/train-* - config_name: subset_427 data_files: - split: train path: subset_427/train-* - config_name: subset_428 data_files: - split: train path: subset_428/train-* - config_name: subset_429 data_files: - split: train path: subset_429/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_430 data_files: - split: train path: subset_430/train-* - config_name: subset_431 data_files: - split: train path: subset_431/train-* - config_name: subset_432 data_files: - split: train path: subset_432/train-* - config_name: subset_433 data_files: - split: train path: subset_433/train-* - config_name: subset_434 data_files: - split: train path: subset_434/train-* - config_name: subset_435 data_files: - split: train path: subset_435/train-* - config_name: subset_436 data_files: - split: train path: subset_436/train-* - config_name: subset_437 data_files: - split: train path: subset_437/train-* - config_name: subset_438 data_files: - split: train path: subset_438/train-* - config_name: subset_439 data_files: - split: train path: subset_439/train-* - config_name: subset_44 data_files: - split: train path: subset_44/train-* - config_name: subset_440 data_files: - split: train path: subset_440/train-* - config_name: subset_441 data_files: - split: train path: subset_441/train-* - config_name: subset_442 data_files: - split: train path: subset_442/train-* - config_name: subset_443 data_files: - split: train path: subset_443/train-* - config_name: subset_444 data_files: - split: train path: subset_444/train-* - config_name: subset_445 data_files: - split: train path: subset_445/train-* - config_name: subset_446 data_files: - split: train path: subset_446/train-* - config_name: subset_447 data_files: - split: train path: subset_447/train-* - config_name: subset_448 data_files: - split: train path: subset_448/train-* - config_name: subset_449 data_files: - split: train path: subset_449/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_450 data_files: - split: train path: subset_450/train-* - config_name: subset_451 data_files: - split: train path: subset_451/train-* - config_name: subset_452 data_files: - split: train path: subset_452/train-* - config_name: subset_453 data_files: - split: train path: subset_453/train-* - config_name: subset_454 data_files: - split: train path: subset_454/train-* - config_name: subset_455 data_files: - split: train path: subset_455/train-* - config_name: subset_456 data_files: - 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config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

Samsung/samsum

Samsung

--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: - cc-by-nc-nd-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - summarization task_ids: [] paperswithcode_id: samsum-corpus pretty_name: SAMSum Corpus tags: - conversations-summarization dataset_info: features: - name: id dtype: string - name: dialogue dtype: string - name: summary dtype: string config_name: samsum splits: - name: train num_bytes: 9479141 num_examples: 14732 - name: test num_bytes: 534492 num_examples: 819 - name: validation num_bytes: 516431 num_examples: 818 download_size: 2944100 dataset_size: 10530064 train-eval-index: - config: samsum task: summarization task_id: summarization splits: eval_split: test col_mapping: dialogue: text summary: target --- # Dataset Card for SAMSum Corpus ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://arxiv.org/abs/1911.12237v2 - **Repository:** [Needs More Information] - **Paper:** https://arxiv.org/abs/1911.12237v2 - **Leaderboard:** [Needs More Information] - **Point of Contact:** [Needs More Information] ### Dataset Summary The SAMSum dataset contains about 16k messenger-like conversations with summaries. Conversations were created and written down by linguists fluent in English. Linguists were asked to create conversations similar to those they write on a daily basis, reflecting the proportion of topics of their real-life messenger convesations. The style and register are diversified - conversations could be informal, semi-formal or formal, they may contain slang words, emoticons and typos. Then, the conversations were annotated with summaries. It was assumed that summaries should be a concise brief of what people talked about in the conversation in third person. The SAMSum dataset was prepared by Samsung R&D Institute Poland and is distributed for research purposes (non-commercial licence: CC BY-NC-ND 4.0). ### Supported Tasks and Leaderboards [Needs More Information] ### Languages English ## Dataset Structure ### Data Instances The created dataset is made of 16369 conversations distributed uniformly into 4 groups based on the number of utterances in con- versations: 3-6, 7-12, 13-18 and 19-30. Each utterance contains the name of the speaker. Most conversations consist of dialogues between two interlocutors (about 75% of all conversations), the rest is between three or more people The first instance in the training set: {'id': '13818513', 'summary': 'Amanda baked cookies and will bring Jerry some tomorrow.', 'dialogue': "Amanda: I baked cookies. Do you want some?\r\nJerry: Sure!\r\nAmanda: I'll bring you tomorrow :-)"} ### Data Fields - dialogue: text of dialogue. - summary: human written summary of the dialogue. - id: unique id of an example. ### Data Splits - train: 14732 - val: 818 - test: 819 ## Dataset Creation ### Curation Rationale In paper: > In the first approach, we reviewed datasets from the following categories: chatbot dialogues, SMS corpora, IRC/chat data, movie dialogues, tweets, comments data (conversations formed by replies to comments), transcription of meetings, written discussions, phone dialogues and daily communication data. Unfortunately, they all differed in some respect from the conversations that are typ- ically written in messenger apps, e.g. they were too technical (IRC data), too long (comments data, transcription of meetings), lacked context (movie dialogues) or they were more of a spoken type, such as a dialogue between a petrol station assis- tant and a client buying petrol. As a consequence, we decided to create a chat dialogue dataset by constructing such conversa- tions that would epitomize the style of a messenger app. ### Source Data #### Initial Data Collection and Normalization In paper: > We asked linguists to create conversations similar to those they write on a daily basis, reflecting the proportion of topics of their real-life messenger conversations. It includes chit-chats, gossiping about friends, arranging meetings, discussing politics, consulting university assignments with colleagues, etc. Therefore, this dataset does not contain any sensitive data or fragments of other corpora. #### Who are the source language producers? linguists ### Annotations #### Annotation process In paper: > Each dialogue was created by one person. After collecting all of the conversations, we asked language experts to annotate them with summaries, assuming that they should (1) be rather short, (2) extract important pieces of information, (3) include names of interlocutors, (4) be written in the third person. Each dialogue contains only one ref- erence summary. #### Who are the annotators? language experts ### Personal and Sensitive Information None, see above: Initial Data Collection and Normalization ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information non-commercial licence: CC BY-NC-ND 4.0 ### Citation Information ``` @inproceedings{gliwa-etal-2019-samsum, title = "{SAMS}um Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization", author = "Gliwa, Bogdan and Mochol, Iwona and Biesek, Maciej and Wawer, Aleksander", booktitle = "Proceedings of the 2nd Workshop on New Frontiers in Summarization", month = nov, year = "2019", address = "Hong Kong, China", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/D19-5409", doi = "10.18653/v1/D19-5409", pages = "70--79" } ``` ### Contributions Thanks to [@cccntu](https://github.com/cccntu) for adding this dataset.

OpenDILabCommunity/LMDrive

OpenDILabCommunity

--- configs: - config_name: default data_files: - split: train path: navigation_instruction_list.txt sep: " " default: true license: apache-2.0 language: - en size_categories: - n>1T --- # LMDrive 64K Dataset Card LMDrive Dataset consists of 64K instruction-sensor-control data clips collected in the CARLA simulator， where each clip includes one navigation instruction, several notice instructions, a sequence of multi-modal multi-view sensor data, and control signals. The duration of the clip spans from 2 to 20 seconds. ## Dataset details - `data/`: dataset folder, the entire dataset contains about 2T of data. - `data/Town01`: sub dataset folder, which only consists of the data folder for the Town01 - `data/Town02`: sub dataset folder, which only consists of the data folder for the Town02 - ... - `dataset_index.txt`: the data list for pretraining the vision encoder - `navigation_instruction_list.txt`: the data list for instruction finetuning - `notice_instruction_list.json`: the data list for instruction finetuning (optional if the notice instruction data is not engaged in the training) **Dataset date:** LMDrive-1.0 Dataset was collected in September 2023. **Paper or resources for more information:** Github: https://github.com/opendilab/LMDrive/README.md Paper: https://arxiv.org/abs/2312.07488 **License:** Attribution-NonCommercial 4.0 International **Where to send questions or comments about the model:** https://github.com/opendilab/LMDrive/issues ## Intended use **Primary intended uses:** The primary use of LMDrive is research on large multimodal models for autonomous driving. **Primary intended users:** The primary intended users of the model are researchers and hobbyists in computer vision, large multimodal model, autonomous driving, and artificial intelligence.

Forceless/Zenodo10K

Forceless

--- dataset_info: features: - name: filename dtype: string - name: size dtype: int64 - name: url dtype: string - name: license dtype: string - name: title dtype: string - name: created dtype: string - name: updated dtype: string - name: doi dtype: string - name: checksum dtype: string splits: - name: pptx num_bytes: 3925161 num_examples: 10448 download_size: 2028492 dataset_size: 3925161 configs: - config_name: default data_files: - split: pptx path: data/pptx-* --- # PPTAgent/Zenodo10K This is the dataset used in [PPTAgent](https://arxiv.org/abs/2501.03936), crawled from [zenodo](http://zenodo.org). To the best of our knowledge, it is the **largest presentation dataset** currently available, comprising over 10,000 **PowerPoint (.pptx)** files, all distributed under a clear and compliant license. For more information, please visit our [github repo](https://github.com/icip-cas/PPTAgent). ```python dirname = f"zenodo-pptx/pptx/{task['license']}/{task['created'][:4]}/" basename = f"{task['checksum'][4:]}-{task['filename']}" filepath = dirname + basename try: open('/tmp/'+basename,'wb').close() except: filepath = dirname + basename[:240] + ".pptx" ``` ## Citation If you find this project helpful, please use the following to cite it: ```bibtex @misc{zheng2025pptagentgeneratingevaluatingpresentations, title={PPTAgent: Generating and Evaluating Presentations Beyond Text-to-Slides}, author={Hao Zheng and Xinyan Guan and Hao Kong and Jia Zheng and Hongyu Lin and Yaojie Lu and Ben He and Xianpei Han and Le Sun}, year={2025}, eprint={2501.03936}, archivePrefix={arXiv}, primaryClass={cs.AI}, url={https://arxiv.org/abs/2501.03936}, } ```

BleachNick/UltraEdit

BleachNick

--- language: - en license: cc-by-4.0 task_categories: - text-to-image dataset_info: features: - name: clip_sim_source dtype: float64 - name: clip_sim_target dtype: float64 - name: clip_sim_dir dtype: float64 - name: clip_sim_image dtype: float64 - name: dinov2_sim dtype: float64 - name: ssim dtype: float64 - name: source_caption dtype: string - name: target_caption dtype: string - name: idx dtype: int64 - name: edit_prompt dtype: string - name: edit_object dtype: 'null' - name: source_image dtype: image - name: edited_image dtype: image - name: mask_image dtype: 'null' splits: - name: FreeForm_0 num_bytes: 759385792 num_examples: 2000 - name: FreeForm_1 num_bytes: 756874067 num_examples: 2000 - name: FreeForm_2 num_bytes: 759183069 num_examples: 2000 - name: FreeForm_3 num_bytes: 755508440 num_examples: 2000 - name: FreeForm_4 num_bytes: 756540442 num_examples: 2000 - name: FreeForm_5 num_bytes: 758622320 num_examples: 2000 - name: FreeForm_6 num_bytes: 761524774 num_examples: 2000 - name: FreeForm_7 num_bytes: 758775293 num_examples: 2000 - name: FreeForm_8 num_bytes: 760200313 num_examples: 2000 - name: FreeForm_9 num_bytes: 768448051 num_examples: 2000 - name: FreeForm_10 num_bytes: 773489315 num_examples: 2000 - name: FreeForm_11 num_bytes: 778109354 num_examples: 2000 - name: FreeForm_12 num_bytes: 778512114 num_examples: 2000 - name: FreeForm_13 num_bytes: 768485969 num_examples: 2000 - name: FreeForm_14 num_bytes: 779712509 num_examples: 2000 - name: FreeForm_15 num_bytes: 765837533 num_examples: 2000 - name: FreeForm_16 num_bytes: 769511714 num_examples: 2000 - name: FreeForm_17 num_bytes: 771149850 num_examples: 2000 - name: FreeForm_18 num_bytes: 771410726 num_examples: 2000 - name: FreeForm_19 num_bytes: 770722184 num_examples: 2000 - name: FreeForm_20 num_bytes: 783276398 num_examples: 2000 - name: FreeForm_21 num_bytes: 776884755 num_examples: 2000 - name: FreeForm_22 num_bytes: 783258028 num_examples: 2000 - name: FreeForm_23 num_bytes: 781541694 num_examples: 2000 - 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name: FreeForm_1563 num_bytes: 774817952 num_examples: 2000 - name: FreeForm_1675 num_bytes: 773030944 num_examples: 2000 - name: FreeForm_1962 num_bytes: 786053209 num_examples: 2000 - name: FreeForm_1792 num_bytes: 774700008 num_examples: 2000 - name: FreeForm_1615 num_bytes: 774380131 num_examples: 2000 - name: FreeForm_1846 num_bytes: 774658032 num_examples: 2000 - name: FreeForm_1616 num_bytes: 782429195 num_examples: 2000 - name: FreeForm_1850 num_bytes: 775140091 num_examples: 2000 - name: FreeForm_1964 num_bytes: 780393901 num_examples: 2000 - name: FreeForm_1801 num_bytes: 768773753 num_examples: 2000 - name: FreeForm_1851 num_bytes: 775091817 num_examples: 2000 - name: FreeForm_1965 num_bytes: 774710107 num_examples: 2000 - name: FreeForm_1626 num_bytes: 776500055 num_examples: 2000 - name: FreeForm_1853 num_bytes: 774376334 num_examples: 2000 - name: FreeForm_1967 num_bytes: 767462102 num_examples: 2000 - name: FreeForm_1692 num_bytes: 766343506 num_examples: 2000 - name: FreeForm_1854 num_bytes: 768674186 num_examples: 2000 - name: FreeForm_1975 num_bytes: 765777279 num_examples: 2000 - name: FreeForm_1699 num_bytes: 778883501 num_examples: 2000 - name: FreeForm_1755 num_bytes: 783000185 num_examples: 2000 - name: FreeForm_1757 num_bytes: 769193034 num_examples: 2000 - name: FreeForm_1763 num_bytes: 772044823 num_examples: 2000 - name: FreeForm_1814 num_bytes: 777568635 num_examples: 2000 - name: FreeForm_1816 num_bytes: 776191715 num_examples: 2000 - name: FreeForm_1821 num_bytes: 777857890 num_examples: 2000 - name: FreeForm_1856 num_bytes: 769967566 num_examples: 2000 - name: FreeForm_1862 num_bytes: 767341817 num_examples: 2000 - name: FreeForm_1873 num_bytes: 772574070 num_examples: 2000 - name: FreeForm_1875 num_bytes: 770945433 num_examples: 2000 - name: FreeForm_1877 num_bytes: 772618224 num_examples: 2000 - name: FreeForm_1935 num_bytes: 780171644 num_examples: 2000 - name: FreeForm_1936 num_bytes: 780368989 num_examples: 2000 - name: FreeForm_1938 num_bytes: 775192638 num_examples: 2000 - name: FreeForm_1939 num_bytes: 768517191 num_examples: 2000 - name: FreeForm_1941 num_bytes: 767928606 num_examples: 2000 - name: FreeForm_1977 num_bytes: 780736929 num_examples: 2000 - name: FreeForm_1981 num_bytes: 775615890 num_examples: 2000 - name: FreeForm_1984 num_bytes: 769609649 num_examples: 2000 - name: FreeForm_1985 num_bytes: 770730441 num_examples: 2000 - name: FreeForm_1987 num_bytes: 768263066 num_examples: 2000 - name: FreeForm_1989 num_bytes: 780388977 num_examples: 2000 - name: FreeForm_1990 num_bytes: 772863509 num_examples: 2000 - name: FreeForm_1993 num_bytes: 773757340 num_examples: 2000 - name: FreeForm_1996 num_bytes: 770872885 num_examples: 2000 - name: FreeForm_2000 num_bytes: 32585530 num_examples: 83 - name: FreeForm_1205 num_bytes: 776134960.0 num_examples: 2000 download_size: 1182151585538 dataset_size: 1177371972678.0 configs: - config_name: default data_files: - split: FreeForm_0 path: data/FreeForm_0-* - split: FreeForm_1 path: data/FreeForm_1-* - split: FreeForm_2 path: data/FreeForm_2-* - split: FreeForm_3 path: data/FreeForm_3-* - split: FreeForm_4 path: data/FreeForm_4-* - split: FreeForm_5 path: data/FreeForm_5-* - split: FreeForm_6 path: data/FreeForm_6-* - split: FreeForm_7 path: data/FreeForm_7-* - split: FreeForm_8 path: data/FreeForm_8-* - split: FreeForm_9 path: data/FreeForm_9-* - split: FreeForm_10 path: data/FreeForm_10-* - split: FreeForm_11 path: data/FreeForm_11-* - split: FreeForm_12 path: data/FreeForm_12-* - split: FreeForm_13 path: data/FreeForm_13-* - split: FreeForm_14 path: data/FreeForm_14-* - split: FreeForm_15 path: data/FreeForm_15-* - split: FreeForm_16 path: data/FreeForm_16-* - split: FreeForm_17 path: data/FreeForm_17-* - split: FreeForm_18 path: data/FreeForm_18-* - split: FreeForm_19 path: data/FreeForm_19-* - split: FreeForm_20 path: data/FreeForm_20-* - split: FreeForm_21 path: data/FreeForm_21-* - split: FreeForm_22 path: data/FreeForm_22-* - split: FreeForm_23 path: data/FreeForm_23-* - split: FreeForm_24 path: data/FreeForm_24-* - split: FreeForm_25 path: data/FreeForm_25-* - split: FreeForm_26 path: data/FreeForm_26-* - split: FreeForm_27 path: data/FreeForm_27-* - split: FreeForm_28 path: data/FreeForm_28-* - split: FreeForm_29 path: data/FreeForm_29-* - split: FreeForm_30 path: data/FreeForm_30-* - split: FreeForm_31 path: data/FreeForm_31-* - split: FreeForm_32 path: data/FreeForm_32-* - split: FreeForm_33 path: data/FreeForm_33-* - split: FreeForm_34 path: data/FreeForm_34-* - split: FreeForm_35 path: data/FreeForm_35-* - split: FreeForm_36 path: data/FreeForm_36-* - split: FreeForm_37 path: data/FreeForm_37-* - split: FreeForm_38 path: data/FreeForm_38-* - split: FreeForm_39 path: data/FreeForm_39-* - split: FreeForm_40 path: data/FreeForm_40-* - split: FreeForm_41 path: data/FreeForm_41-* - split: FreeForm_42 path: data/FreeForm_42-* - split: FreeForm_43 path: data/FreeForm_43-* - split: FreeForm_44 path: data/FreeForm_44-* - split: FreeForm_45 path: data/FreeForm_45-* - split: FreeForm_46 path: data/FreeForm_46-* - split: FreeForm_47 path: data/FreeForm_47-* - split: FreeForm_48 path: data/FreeForm_48-* - split: FreeForm_49 path: data/FreeForm_49-* - split: FreeForm_50 path: data/FreeForm_50-* - split: FreeForm_51 path: data/FreeForm_51-* - split: FreeForm_52 path: data/FreeForm_52-* - split: FreeForm_53 path: data/FreeForm_53-* - split: FreeForm_54 path: data/FreeForm_54-* - split: FreeForm_55 path: data/FreeForm_55-* - split: FreeForm_56 path: data/FreeForm_56-* - split: FreeForm_57 path: data/FreeForm_57-* - split: FreeForm_58 path: data/FreeForm_58-* - split: FreeForm_59 path: data/FreeForm_59-* - split: FreeForm_60 path: data/FreeForm_60-* - split: FreeForm_61 path: data/FreeForm_61-* - split: FreeForm_62 path: data/FreeForm_62-* - split: FreeForm_63 path: data/FreeForm_63-* - split: FreeForm_64 path: data/FreeForm_64-* - split: FreeForm_65 path: data/FreeForm_65-* - split: FreeForm_66 path: data/FreeForm_66-* - split: FreeForm_67 path: data/FreeForm_67-* - split: FreeForm_68 path: data/FreeForm_68-* - split: FreeForm_69 path: data/FreeForm_69-* - split: FreeForm_70 path: data/FreeForm_70-* - split: FreeForm_71 path: data/FreeForm_71-* - split: FreeForm_72 path: data/FreeForm_72-* - split: FreeForm_73 path: data/FreeForm_73-* - split: FreeForm_74 path: data/FreeForm_74-* - split: FreeForm_75 path: data/FreeForm_75-* - split: FreeForm_76 path: data/FreeForm_76-* - split: FreeForm_77 path: data/FreeForm_77-* - split: FreeForm_78 path: data/FreeForm_78-* - split: FreeForm_79 path: data/FreeForm_79-* - split: FreeForm_80 path: data/FreeForm_80-* - split: FreeForm_81 path: data/FreeForm_81-* - split: FreeForm_82 path: data/FreeForm_82-* - split: FreeForm_83 path: data/FreeForm_83-* - split: FreeForm_84 path: data/FreeForm_84-* - split: FreeForm_85 path: data/FreeForm_85-* - split: FreeForm_86 path: data/FreeForm_86-* - split: FreeForm_87 path: data/FreeForm_87-* - split: FreeForm_88 path: data/FreeForm_88-* - split: FreeForm_89 path: data/FreeForm_89-* - split: FreeForm_90 path: data/FreeForm_90-* - split: FreeForm_91 path: data/FreeForm_91-* - split: FreeForm_92 path: data/FreeForm_92-* - split: FreeForm_93 path: data/FreeForm_93-* - split: FreeForm_94 path: data/FreeForm_94-* - split: FreeForm_95 path: data/FreeForm_95-* - split: FreeForm_96 path: data/FreeForm_96-* - split: FreeForm_97 path: data/FreeForm_97-* - split: FreeForm_98 path: data/FreeForm_98-* - split: FreeForm_99 path: data/FreeForm_99-* - split: FreeForm_100 path: data/FreeForm_100-* - split: FreeForm_101 path: data/FreeForm_101-* - split: FreeForm_102 path: data/FreeForm_102-* - split: FreeForm_103 path: data/FreeForm_103-* - split: FreeForm_104 path: data/FreeForm_104-* - split: FreeForm_105 path: data/FreeForm_105-* - split: FreeForm_106 path: data/FreeForm_106-* - split: FreeForm_107 path: data/FreeForm_107-* - split: FreeForm_108 path: data/FreeForm_108-* - split: FreeForm_109 path: data/FreeForm_109-* - split: FreeForm_110 path: data/FreeForm_110-* - split: FreeForm_111 path: data/FreeForm_111-* - split: FreeForm_112 path: data/FreeForm_112-* - split: FreeForm_113 path: data/FreeForm_113-* - split: FreeForm_114 path: data/FreeForm_114-* - split: FreeForm_115 path: data/FreeForm_115-* - split: FreeForm_116 path: data/FreeForm_116-* - split: FreeForm_117 path: data/FreeForm_117-* - split: FreeForm_118 path: data/FreeForm_118-* - split: FreeForm_119 path: data/FreeForm_119-* - split: FreeForm_120 path: data/FreeForm_120-* - split: FreeForm_121 path: data/FreeForm_121-* - split: FreeForm_122 path: data/FreeForm_122-* - split: FreeForm_123 path: data/FreeForm_123-* - split: FreeForm_124 path: data/FreeForm_124-* - split: FreeForm_125 path: data/FreeForm_125-* - split: FreeForm_126 path: data/FreeForm_126-* - split: FreeForm_127 path: data/FreeForm_127-* - split: FreeForm_128 path: data/FreeForm_128-* - split: FreeForm_129 path: data/FreeForm_129-* - split: FreeForm_130 path: data/FreeForm_130-* - split: FreeForm_131 path: data/FreeForm_131-* - split: FreeForm_132 path: data/FreeForm_132-* - split: FreeForm_133 path: data/FreeForm_133-* - split: FreeForm_134 path: data/FreeForm_134-* - split: FreeForm_135 path: data/FreeForm_135-* - split: FreeForm_136 path: data/FreeForm_136-* - split: FreeForm_137 path: data/FreeForm_137-* - split: FreeForm_138 path: data/FreeForm_138-* - split: FreeForm_139 path: data/FreeForm_139-* - split: FreeForm_140 path: data/FreeForm_140-* - split: FreeForm_141 path: data/FreeForm_141-* - split: FreeForm_142 path: data/FreeForm_142-* - split: FreeForm_143 path: data/FreeForm_143-* - split: FreeForm_144 path: data/FreeForm_144-* - split: FreeForm_145 path: data/FreeForm_145-* - split: FreeForm_146 path: data/FreeForm_146-* - split: FreeForm_147 path: data/FreeForm_147-* - split: FreeForm_148 path: data/FreeForm_148-* - split: FreeForm_149 path: data/FreeForm_149-* - split: FreeForm_150 path: data/FreeForm_150-* - split: FreeForm_151 path: data/FreeForm_151-* - split: FreeForm_152 path: data/FreeForm_152-* - split: FreeForm_153 path: data/FreeForm_153-* - split: FreeForm_154 path: data/FreeForm_154-* - split: FreeForm_155 path: data/FreeForm_155-* - split: FreeForm_156 path: data/FreeForm_156-* - split: FreeForm_157 path: data/FreeForm_157-* - split: FreeForm_158 path: data/FreeForm_158-* - split: FreeForm_159 path: data/FreeForm_159-* - split: FreeForm_160 path: data/FreeForm_160-* - split: FreeForm_161 path: data/FreeForm_161-* - split: FreeForm_162 path: data/FreeForm_162-* - split: FreeForm_163 path: data/FreeForm_163-* - split: FreeForm_164 path: data/FreeForm_164-* - split: FreeForm_165 path: data/FreeForm_165-* - split: FreeForm_166 path: data/FreeForm_166-* - split: FreeForm_167 path: data/FreeForm_167-* - split: FreeForm_168 path: data/FreeForm_168-* - split: FreeForm_169 path: data/FreeForm_169-* - split: FreeForm_170 path: data/FreeForm_170-* - split: FreeForm_171 path: data/FreeForm_171-* - split: FreeForm_172 path: data/FreeForm_172-* - split: FreeForm_173 path: data/FreeForm_173-* - split: FreeForm_174 path: data/FreeForm_174-* - split: FreeForm_175 path: data/FreeForm_175-* - split: FreeForm_176 path: data/FreeForm_176-* - split: FreeForm_177 path: data/FreeForm_177-* - split: FreeForm_178 path: data/FreeForm_178-* - split: FreeForm_179 path: data/FreeForm_179-* - split: FreeForm_180 path: data/FreeForm_180-* - split: FreeForm_181 path: data/FreeForm_181-* - split: FreeForm_182 path: data/FreeForm_182-* - split: FreeForm_183 path: data/FreeForm_183-* - split: FreeForm_184 path: data/FreeForm_184-* - split: FreeForm_185 path: data/FreeForm_185-* - split: FreeForm_186 path: data/FreeForm_186-* - split: FreeForm_187 path: data/FreeForm_187-* - split: FreeForm_188 path: data/FreeForm_188-* - split: FreeForm_189 path: data/FreeForm_189-* - split: FreeForm_190 path: data/FreeForm_190-* - split: FreeForm_191 path: data/FreeForm_191-* - split: FreeForm_192 path: data/FreeForm_192-* - split: FreeForm_193 path: data/FreeForm_193-* - split: FreeForm_194 path: data/FreeForm_194-* - split: FreeForm_195 path: data/FreeForm_195-* - split: FreeForm_196 path: data/FreeForm_196-* - split: FreeForm_197 path: data/FreeForm_197-* - split: FreeForm_198 path: data/FreeForm_198-* - split: FreeForm_199 path: data/FreeForm_199-* - split: FreeForm_200 path: data/FreeForm_200-* - split: FreeForm_201 path: data/FreeForm_201-* - split: FreeForm_202 path: data/FreeForm_202-* - split: FreeForm_203 path: data/FreeForm_203-* - split: FreeForm_204 path: data/FreeForm_204-* - split: FreeForm_205 path: data/FreeForm_205-* - split: FreeForm_206 path: data/FreeForm_206-* - split: FreeForm_207 path: data/FreeForm_207-* - split: FreeForm_208 path: data/FreeForm_208-* - split: FreeForm_209 path: data/FreeForm_209-* - split: FreeForm_210 path: data/FreeForm_210-* - split: FreeForm_211 path: data/FreeForm_211-* - split: FreeForm_212 path: data/FreeForm_212-* - split: FreeForm_213 path: data/FreeForm_213-* - split: FreeForm_214 path: data/FreeForm_214-* - split: FreeForm_215 path: data/FreeForm_215-* - split: FreeForm_216 path: data/FreeForm_216-* - split: FreeForm_217 path: data/FreeForm_217-* - split: FreeForm_218 path: data/FreeForm_218-* - split: FreeForm_219 path: data/FreeForm_219-* - split: FreeForm_220 path: data/FreeForm_220-* - split: FreeForm_221 path: data/FreeForm_221-* - split: FreeForm_222 path: data/FreeForm_222-* - split: FreeForm_223 path: data/FreeForm_223-* - split: FreeForm_224 path: data/FreeForm_224-* - split: FreeForm_225 path: data/FreeForm_225-* - split: FreeForm_226 path: data/FreeForm_226-* - split: FreeForm_227 path: data/FreeForm_227-* - split: FreeForm_228 path: data/FreeForm_228-* - split: FreeForm_229 path: data/FreeForm_229-* - split: FreeForm_230 path: data/FreeForm_230-* - split: FreeForm_231 path: data/FreeForm_231-* - split: FreeForm_232 path: data/FreeForm_232-* - split: FreeForm_233 path: data/FreeForm_233-* - split: FreeForm_234 path: data/FreeForm_234-* - split: FreeForm_235 path: data/FreeForm_235-* - split: FreeForm_236 path: data/FreeForm_236-* - split: FreeForm_237 path: data/FreeForm_237-* - split: FreeForm_238 path: data/FreeForm_238-* - split: FreeForm_239 path: data/FreeForm_239-* - split: FreeForm_240 path: data/FreeForm_240-* - split: FreeForm_241 path: data/FreeForm_241-* - split: FreeForm_242 path: data/FreeForm_242-* - split: FreeForm_243 path: data/FreeForm_243-* - split: FreeForm_244 path: data/FreeForm_244-* - split: FreeForm_245 path: data/FreeForm_245-* - split: FreeForm_246 path: data/FreeForm_246-* - split: FreeForm_247 path: data/FreeForm_247-* - split: FreeForm_248 path: data/FreeForm_248-* - split: FreeForm_249 path: data/FreeForm_249-* - split: FreeForm_250 path: data/FreeForm_250-* - split: FreeForm_251 path: data/FreeForm_251-* - split: FreeForm_252 path: data/FreeForm_252-* - split: FreeForm_253 path: data/FreeForm_253-* - split: FreeForm_254 path: data/FreeForm_254-* - split: FreeForm_255 path: data/FreeForm_255-* - split: FreeForm_256 path: data/FreeForm_256-* - split: FreeForm_257 path: data/FreeForm_257-* - split: FreeForm_258 path: data/FreeForm_258-* - split: FreeForm_259 path: data/FreeForm_259-* - split: FreeForm_260 path: data/FreeForm_260-* - split: FreeForm_261 path: data/FreeForm_261-* - split: FreeForm_262 path: data/FreeForm_262-* - split: FreeForm_263 path: data/FreeForm_263-* - split: FreeForm_264 path: data/FreeForm_264-* - split: FreeForm_265 path: data/FreeForm_265-* - split: FreeForm_266 path: data/FreeForm_266-* - split: FreeForm_267 path: data/FreeForm_267-* - split: FreeForm_268 path: data/FreeForm_268-* - split: FreeForm_269 path: data/FreeForm_269-* - split: FreeForm_270 path: data/FreeForm_270-* - split: FreeForm_271 path: data/FreeForm_271-* - split: FreeForm_272 path: data/FreeForm_272-* - split: FreeForm_273 path: data/FreeForm_273-* - split: FreeForm_274 path: data/FreeForm_274-* - split: FreeForm_275 path: data/FreeForm_275-* - split: FreeForm_276 path: data/FreeForm_276-* - split: FreeForm_277 path: data/FreeForm_277-* - split: FreeForm_278 path: data/FreeForm_278-* - split: FreeForm_279 path: data/FreeForm_279-* - split: FreeForm_280 path: data/FreeForm_280-* - split: FreeForm_281 path: data/FreeForm_281-* - split: FreeForm_282 path: data/FreeForm_282-* - split: FreeForm_283 path: data/FreeForm_283-* - split: FreeForm_284 path: data/FreeForm_284-* - split: FreeForm_285 path: data/FreeForm_285-* - split: FreeForm_286 path: data/FreeForm_286-* - split: FreeForm_287 path: data/FreeForm_287-* - split: FreeForm_288 path: data/FreeForm_288-* - split: FreeForm_289 path: data/FreeForm_289-* - split: FreeForm_290 path: data/FreeForm_290-* - split: FreeForm_291 path: data/FreeForm_291-* - split: FreeForm_292 path: data/FreeForm_292-* - split: FreeForm_293 path: data/FreeForm_293-* - split: FreeForm_294 path: data/FreeForm_294-* - split: FreeForm_295 path: data/FreeForm_295-* - split: FreeForm_296 path: data/FreeForm_296-* - split: FreeForm_297 path: data/FreeForm_297-* - split: FreeForm_298 path: data/FreeForm_298-* - split: FreeForm_299 path: data/FreeForm_299-* - split: FreeForm_300 path: data/FreeForm_300-* - split: FreeForm_301 path: data/FreeForm_301-* - split: FreeForm_302 path: data/FreeForm_302-* - split: FreeForm_303 path: data/FreeForm_303-* - split: FreeForm_304 path: data/FreeForm_304-* - split: FreeForm_305 path: data/FreeForm_305-* - split: FreeForm_306 path: data/FreeForm_306-* - split: FreeForm_307 path: data/FreeForm_307-* - split: FreeForm_308 path: data/FreeForm_308-* - split: FreeForm_309 path: data/FreeForm_309-* - split: FreeForm_310 path: data/FreeForm_310-* - split: FreeForm_311 path: data/FreeForm_311-* - split: FreeForm_312 path: data/FreeForm_312-* - split: FreeForm_313 path: data/FreeForm_313-* - split: FreeForm_314 path: data/FreeForm_314-* - split: FreeForm_315 path: data/FreeForm_315-* - split: FreeForm_316 path: data/FreeForm_316-* - split: FreeForm_317 path: data/FreeForm_317-* - split: FreeForm_318 path: data/FreeForm_318-* - split: FreeForm_319 path: data/FreeForm_319-* - split: FreeForm_320 path: data/FreeForm_320-* - split: FreeForm_321 path: data/FreeForm_321-* - split: FreeForm_322 path: data/FreeForm_322-* - split: FreeForm_323 path: data/FreeForm_323-* - split: FreeForm_324 path: data/FreeForm_324-* - split: FreeForm_325 path: data/FreeForm_325-* - split: FreeForm_326 path: data/FreeForm_326-* - split: FreeForm_327 path: data/FreeForm_327-* - split: FreeForm_328 path: data/FreeForm_328-* - split: FreeForm_329 path: data/FreeForm_329-* - split: FreeForm_330 path: data/FreeForm_330-* - split: FreeForm_331 path: data/FreeForm_331-* - split: FreeForm_332 path: data/FreeForm_332-* - split: FreeForm_333 path: data/FreeForm_333-* - split: FreeForm_334 path: data/FreeForm_334-* - split: FreeForm_335 path: data/FreeForm_335-* - split: FreeForm_336 path: data/FreeForm_336-* - split: FreeForm_337 path: data/FreeForm_337-* - split: FreeForm_338 path: data/FreeForm_338-* - split: FreeForm_339 path: data/FreeForm_339-* - split: FreeForm_340 path: data/FreeForm_340-* - split: FreeForm_341 path: data/FreeForm_341-* - split: FreeForm_342 path: data/FreeForm_342-* - split: FreeForm_343 path: data/FreeForm_343-* - split: FreeForm_344 path: data/FreeForm_344-* - 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split: FreeForm_1990 path: data/FreeForm_1990-* - split: FreeForm_1993 path: data/FreeForm_1993-* - split: FreeForm_1996 path: data/FreeForm_1996-* - split: FreeForm_2000 path: data/FreeForm_2000-* tags: - art --- # Dataset Card for Dataset Name <!-- Provide a quick summary of the dataset. --> This dataset card aims to be a base template for new datasets. It has been generated using [this raw template](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/templates/datasetcard_template.md?plain=1). ## Dataset Details ### Dataset Description <!-- Provide a longer summary of what this dataset is. --> - **Curated by:** [More Information Needed] - **Funded by [optional]:** [More Information Needed] - **Shared by [optional]:** [More Information Needed] - **Language(s) (NLP):** [More Information Needed] - **License:** [More Information Needed] ### Dataset Sources [optional] <!-- Provide the basic links for the dataset. --> - **Repository:** [More Information Needed] - **Paper [optional]:** [More Information Needed] - **Demo [optional]:** [More Information Needed] ## Uses <!-- Address questions around how the dataset is intended to be used. --> ### Direct Use <!-- This section describes suitable use cases for the dataset. --> [More Information Needed] ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> [More Information Needed] ## Dataset Structure <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. --> [More Information Needed] ## Dataset Creation ### Curation Rationale <!-- Motivation for the creation of this dataset. --> [More Information Needed] ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> [More Information Needed] #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> [More Information Needed] ### Annotations [optional] <!-- If the dataset contains annotations which are not part of the initial data collection, use this section to describe them. --> #### Annotation process <!-- This section describes the annotation process such as annotation tools used in the process, the amount of data annotated, annotation guidelines provided to the annotators, interannotator statistics, annotation validation, etc. --> [More Information Needed] #### Who are the annotators? <!-- This section describes the people or systems who created the annotations. --> [More Information Needed] #### Personal and Sensitive Information <!-- State whether the dataset contains data that might be considered personal, sensitive, or private (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.). If efforts were made to anonymize the data, describe the anonymization process. --> [More Information Needed] ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> [More Information Needed] ### Recommendations <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. --> Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] <!-- If relevant, include terms and calculations in this section that can help readers understand the dataset or dataset card. --> [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed] ## Bibtex citation ```bibtex @misc{zhao2024ultraeditinstructionbasedfinegrainedimage, title={UltraEdit: Instruction-based Fine-Grained Image Editing at Scale}, author={Haozhe Zhao and Xiaojian Ma and Liang Chen and Shuzheng Si and Rujie Wu and Kaikai An and Peiyu Yu and Minjia Zhang and Qing Li and Baobao Chang}, year={2024}, eprint={2407.05282}, archivePrefix={arXiv}, primaryClass={cs.CV}, url={https://arxiv.org/abs/2407.05282}, } ```

allenai/sciq

allenai

--- annotations_creators: - no-annotation language_creators: - crowdsourced language: - en license: - cc-by-nc-3.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - question-answering task_ids: - closed-domain-qa paperswithcode_id: sciq pretty_name: SciQ dataset_info: features: - name: question dtype: string - name: distractor3 dtype: string - name: distractor1 dtype: string - name: distractor2 dtype: string - name: correct_answer dtype: string - name: support dtype: string splits: - name: train num_bytes: 6546183 num_examples: 11679 - name: validation num_bytes: 554120 num_examples: 1000 - name: test num_bytes: 563927 num_examples: 1000 download_size: 4674410 dataset_size: 7664230 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* --- # Dataset Card for "sciq" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [https://allenai.org/data/sciq](https://allenai.org/data/sciq) - **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Paper:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) - **Size of downloaded dataset files:** 2.82 MB - **Size of the generated dataset:** 7.68 MB - **Total amount of disk used:** 10.50 MB ### Dataset Summary The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### default - **Size of downloaded dataset files:** 2.82 MB - **Size of the generated dataset:** 7.68 MB - **Total amount of disk used:** 10.50 MB An example of 'train' looks as follows. ``` This example was too long and was cropped: { "correct_answer": "coriolis effect", "distractor1": "muon effect", "distractor2": "centrifugal effect", "distractor3": "tropical effect", "question": "What phenomenon makes global winds blow northeast to southwest or the reverse in the northern hemisphere and northwest to southeast or the reverse in the southern hemisphere?", "support": "\"Without Coriolis Effect the global winds would blow north to south or south to north. But Coriolis makes them blow northeast to..." } ``` ### Data Fields The data fields are the same among all splits. #### default - `question`: a `string` feature. - `distractor3`: a `string` feature. - `distractor1`: a `string` feature. - `distractor2`: a `string` feature. - `correct_answer`: a `string` feature. - `support`: a `string` feature. ### Data Splits | name |train|validation|test| |-------|----:|---------:|---:| |default|11679| 1000|1000| ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information The dataset is licensed under the [Creative Commons Attribution-NonCommercial 3.0 Unported License](http://creativecommons.org/licenses/by-nc/3.0/). ### Citation Information ``` @inproceedings{SciQ, title={Crowdsourcing Multiple Choice Science Questions}, author={Johannes Welbl, Nelson F. Liu, Matt Gardner}, year={2017}, journal={arXiv:1707.06209v1} } ``` ### Contributions Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten), [@lewtun](https://github.com/lewtun), [@thomwolf](https://github.com/thomwolf) for adding this dataset.

hails/bigbench

hails

--- dataset_info: - config_name: abstract_narrative_understanding_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 6560069 num_examples: 3000 - name: train num_bytes: 5249819 num_examples: 2400 - name: validation num_bytes: 1310250 num_examples: 600 download_size: 0 dataset_size: 13120138 - config_name: anachronisms_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 48826 num_examples: 230 - name: train num_bytes: 39116 num_examples: 184 - name: validation num_bytes: 9710 num_examples: 46 download_size: 0 dataset_size: 97652 - config_name: analogical_similarity_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1373815 num_examples: 323 - name: train num_bytes: 1101512 num_examples: 259 - name: validation num_bytes: 272303 num_examples: 64 download_size: 0 dataset_size: 2747630 - config_name: analytic_entailment_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 17316 num_examples: 70 - name: train num_bytes: 13368 num_examples: 54 - name: validation num_bytes: 3948 num_examples: 16 download_size: 0 dataset_size: 34632 - config_name: arithmetic_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 3833272 num_examples: 15023 - name: train num_bytes: 3066775 num_examples: 12019 - name: validation num_bytes: 766497 num_examples: 3004 download_size: 0 dataset_size: 7666544 - config_name: ascii_word_recognition_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 4984662 num_examples: 5000 - name: train num_bytes: 3997273 num_examples: 4000 - name: validation num_bytes: 987389 num_examples: 1000 download_size: 0 dataset_size: 9969324 - config_name: authorship_verification_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 14118592 num_examples: 880 - name: train num_bytes: 11288481 num_examples: 704 - name: validation num_bytes: 2830111 num_examples: 176 download_size: 0 dataset_size: 28237184 - config_name: auto_categorization_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 40549 num_examples: 328 - name: train num_bytes: 32992 num_examples: 263 - name: validation num_bytes: 7557 num_examples: 65 download_size: 0 dataset_size: 81098 - config_name: auto_debugging_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 5112 num_examples: 34 - name: train num_bytes: 2651 num_examples: 18 - name: validation num_bytes: 2461 num_examples: 16 download_size: 0 dataset_size: 10224 - config_name: bbq_lite_json_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 6890493 num_examples: 16076 - name: train num_bytes: 5508584 num_examples: 12866 - name: validation num_bytes: 1381909 num_examples: 3210 download_size: 0 dataset_size: 13780986 - config_name: bridging_anaphora_resolution_barqa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1971015 num_examples: 648 - name: train num_bytes: 1537264 num_examples: 519 - name: validation num_bytes: 433751 num_examples: 129 download_size: 0 dataset_size: 3942030 - config_name: causal_judgment_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 204878 num_examples: 190 - name: train num_bytes: 164940 num_examples: 152 - name: validation num_bytes: 39938 num_examples: 38 download_size: 0 dataset_size: 409756 - config_name: cause_and_effect_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 49314 num_examples: 153 - name: train num_bytes: 39620 num_examples: 123 - name: validation num_bytes: 9694 num_examples: 30 download_size: 0 dataset_size: 98628 - config_name: checkmate_in_one_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 3123256 num_examples: 3498 - name: train num_bytes: 2502314 num_examples: 2799 - name: validation num_bytes: 620942 num_examples: 699 download_size: 0 dataset_size: 6246512 - config_name: chess_state_tracking_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 3269932 num_examples: 6000 - name: train num_bytes: 2616294 num_examples: 4800 - name: validation num_bytes: 653638 num_examples: 1200 download_size: 0 dataset_size: 6539864 - config_name: chinese_remainder_theorem_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 153222 num_examples: 500 - name: train num_bytes: 122601 num_examples: 400 - name: validation num_bytes: 30621 num_examples: 100 download_size: 0 dataset_size: 306444 - config_name: cifar10_classification_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 111022200 num_examples: 20000 - name: train num_bytes: 88782724 num_examples: 16000 - name: validation num_bytes: 22239476 num_examples: 4000 download_size: 0 dataset_size: 222044400 - config_name: code_line_description_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 33670 num_examples: 60 - name: train num_bytes: 25530 num_examples: 44 - name: validation num_bytes: 8140 num_examples: 16 download_size: 0 dataset_size: 67340 - config_name: codenames_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 25195 num_examples: 85 - name: train num_bytes: 19964 num_examples: 68 - name: validation num_bytes: 5231 num_examples: 17 download_size: 0 dataset_size: 50390 - config_name: color_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1633263 num_examples: 4000 - name: train num_bytes: 1306663 num_examples: 3200 - name: validation num_bytes: 326600 num_examples: 800 download_size: 0 dataset_size: 3266526 - config_name: common_morpheme_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 12388 num_examples: 50 - name: train num_bytes: 8444 num_examples: 34 - name: validation num_bytes: 3944 num_examples: 16 download_size: 0 dataset_size: 24776 - config_name: conceptual_combinations_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 58859 num_examples: 103 - name: train num_bytes: 48010 num_examples: 84 - name: validation num_bytes: 10849 num_examples: 19 download_size: 0 dataset_size: 117718 - config_name: conlang_translation_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 215190 num_examples: 164 - name: train num_bytes: 173024 num_examples: 132 - name: validation num_bytes: 42166 num_examples: 32 download_size: 0 dataset_size: 430380 - config_name: contextual_parametric_knowledge_conflicts_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 14587554 num_examples: 17528 - name: train num_bytes: 11666236 num_examples: 14023 - name: validation num_bytes: 2921318 num_examples: 3505 download_size: 0 dataset_size: 29175108 - config_name: crash_blossom_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 12194 num_examples: 38 - name: train num_bytes: 6999 num_examples: 22 - name: validation num_bytes: 5195 num_examples: 16 download_size: 0 dataset_size: 24388 - config_name: crass_ai_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 22870 num_examples: 44 - name: train num_bytes: 14130 num_examples: 28 - name: validation num_bytes: 8740 num_examples: 16 download_size: 0 dataset_size: 45740 - config_name: cryobiology_spanish_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 38674 num_examples: 146 - name: train num_bytes: 31129 num_examples: 117 - name: validation num_bytes: 7545 num_examples: 29 download_size: 0 dataset_size: 77348 - config_name: cryptonite_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 2844402 num_examples: 26157 - name: train num_bytes: 2275724 num_examples: 20926 - name: validation num_bytes: 568678 num_examples: 5231 download_size: 0 dataset_size: 5688804 - config_name: cs_algorithms_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 272435 num_examples: 1320 - name: train num_bytes: 218192 num_examples: 1056 - name: validation num_bytes: 54243 num_examples: 264 download_size: 0 dataset_size: 544870 - config_name: dark_humor_detection_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 26556 num_examples: 80 - name: train num_bytes: 21267 num_examples: 64 - name: validation num_bytes: 5289 num_examples: 16 download_size: 0 dataset_size: 53112 - config_name: date_understanding_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 94908 num_examples: 369 - name: train num_bytes: 76165 num_examples: 296 - name: validation num_bytes: 18743 num_examples: 73 download_size: 0 dataset_size: 189816 - config_name: disambiguation_qa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 122471 num_examples: 258 - name: train num_bytes: 98687 num_examples: 207 - name: validation num_bytes: 23784 num_examples: 51 download_size: 0 dataset_size: 244942 - config_name: discourse_marker_prediction_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 2090684 num_examples: 857 - name: train num_bytes: 1666052 num_examples: 686 - name: validation num_bytes: 424632 num_examples: 171 download_size: 0 dataset_size: 4181368 - config_name: disfl_qa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 7964775 num_examples: 8000 - name: train num_bytes: 6376511 num_examples: 6400 - name: validation num_bytes: 1588264 num_examples: 1600 download_size: 0 dataset_size: 15929550 - config_name: dyck_languages_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1227916 num_examples: 1000 - name: train num_bytes: 982680 num_examples: 800 - name: validation num_bytes: 245236 num_examples: 200 download_size: 0 dataset_size: 2455832 - config_name: elementary_math_qa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 13442550 num_examples: 38160 - name: train num_bytes: 10766969 num_examples: 30531 - name: validation num_bytes: 2675581 num_examples: 7629 download_size: 0 dataset_size: 26885100 - config_name: emoji_movie_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 33667 num_examples: 100 - name: train num_bytes: 26987 num_examples: 80 - name: validation num_bytes: 6680 num_examples: 20 download_size: 0 dataset_size: 67334 - config_name: emojis_emotion_prediction_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 47983 num_examples: 131 - name: train num_bytes: 38458 num_examples: 105 - name: validation num_bytes: 9525 num_examples: 26 download_size: 0 dataset_size: 95966 - config_name: empirical_judgments_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 47499 num_examples: 99 - name: train num_bytes: 38346 num_examples: 80 - name: validation num_bytes: 9153 num_examples: 19 download_size: 0 dataset_size: 94998 - config_name: english_proverbs_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 22530 num_examples: 34 - name: train num_bytes: 12066 num_examples: 18 - name: validation num_bytes: 10464 num_examples: 16 download_size: 0 dataset_size: 45060 - config_name: english_russian_proverbs_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 59900 num_examples: 80 - name: train num_bytes: 48051 num_examples: 64 - name: validation num_bytes: 11849 num_examples: 16 download_size: 0 dataset_size: 119800 - config_name: entailed_polarity_hindi_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 57052 num_examples: 138 - name: train num_bytes: 45829 num_examples: 111 - name: validation num_bytes: 11223 num_examples: 27 download_size: 0 dataset_size: 114104 - config_name: entailed_polarity_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 25421 num_examples: 148 - name: train num_bytes: 20350 num_examples: 119 - name: validation num_bytes: 5071 num_examples: 29 download_size: 0 dataset_size: 50842 - config_name: epistemic_reasoning_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 887158 num_examples: 2000 - name: train num_bytes: 710107 num_examples: 1600 - name: validation num_bytes: 177051 num_examples: 400 download_size: 0 dataset_size: 1774316 - config_name: evaluating_information_essentiality_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 77488 num_examples: 68 - name: train num_bytes: 59596 num_examples: 52 - name: validation num_bytes: 17892 num_examples: 16 download_size: 0 dataset_size: 154976 - config_name: fact_checker_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1337384 num_examples: 7154 - name: train num_bytes: 1070750 num_examples: 5724 - name: validation num_bytes: 266634 num_examples: 1430 download_size: 0 dataset_size: 2674768 - config_name: fantasy_reasoning_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 75886 num_examples: 201 - name: train num_bytes: 61398 num_examples: 161 - name: validation num_bytes: 14488 num_examples: 40 download_size: 0 dataset_size: 151772 - config_name: few_shot_nlg_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 75937 num_examples: 153 - name: train num_bytes: 61862 num_examples: 123 - name: validation num_bytes: 14075 num_examples: 30 download_size: 0 dataset_size: 151874 - config_name: figure_of_speech_detection_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 21717 num_examples: 59 - name: train num_bytes: 15962 num_examples: 43 - name: validation num_bytes: 5755 num_examples: 16 download_size: 0 dataset_size: 43434 - config_name: formal_fallacies_syllogisms_negation_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 8314653 num_examples: 14200 - name: train num_bytes: 6652955 num_examples: 11360 - name: validation num_bytes: 1661698 num_examples: 2840 download_size: 0 dataset_size: 16629306 - config_name: gem_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 36065281 num_examples: 14802 - name: train num_bytes: 28819497 num_examples: 11845 - name: validation num_bytes: 7245784 num_examples: 2957 download_size: 0 dataset_size: 72130562 - config_name: gender_inclusive_sentences_german_zero_shot features: - 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config_name: real_or_fake_text_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 53663318 num_examples: 15088 - name: train num_bytes: 42879846 num_examples: 12072 - name: validation num_bytes: 10783472 num_examples: 3016 download_size: 47399045 dataset_size: 107326636 - config_name: reasoning_about_colored_objects_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 907474 num_examples: 2000 - name: train num_bytes: 729609 num_examples: 1600 - name: validation num_bytes: 177865 num_examples: 400 download_size: 273263 dataset_size: 1814948 - config_name: repeat_copy_logic_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 6678 num_examples: 32 - name: train num_bytes: 3327 num_examples: 16 - name: validation num_bytes: 3351 num_examples: 16 download_size: 18315 dataset_size: 13356 - config_name: rephrase_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 34222 num_examples: 78 - name: train num_bytes: 27360 num_examples: 62 - name: validation num_bytes: 6862 num_examples: 16 download_size: 41102 dataset_size: 68444 - config_name: riddle_sense_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 15507 num_examples: 49 - name: train num_bytes: 10741 num_examples: 33 - name: validation num_bytes: 4766 num_examples: 16 download_size: 32496 dataset_size: 31014 - config_name: ruin_names_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 144087 num_examples: 448 - name: train num_bytes: 115171 num_examples: 359 - name: validation num_bytes: 28916 num_examples: 89 download_size: 118193 dataset_size: 288174 - config_name: salient_translation_error_detection_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1141626 num_examples: 998 - name: train num_bytes: 912819 num_examples: 799 - name: validation num_bytes: 228807 num_examples: 199 download_size: 413634 dataset_size: 2283252 - config_name: scientific_press_release_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 13690 num_examples: 50 - name: train num_bytes: 9254 num_examples: 34 - name: validation num_bytes: 4436 num_examples: 16 download_size: 27293 dataset_size: 27380 - config_name: semantic_parsing_in_context_sparc_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1524852 num_examples: 1155 - name: train num_bytes: 1248391 num_examples: 924 - name: validation num_bytes: 276461 num_examples: 231 download_size: 440326 dataset_size: 3049704 - config_name: semantic_parsing_spider_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1265744 num_examples: 1034 - name: train num_bytes: 973864 num_examples: 828 - name: validation num_bytes: 291880 num_examples: 206 download_size: 358276 dataset_size: 2531488 - config_name: sentence_ambiguity_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 8168 num_examples: 60 - name: train num_bytes: 5976 num_examples: 44 - name: validation num_bytes: 2192 num_examples: 16 download_size: 18275 dataset_size: 16336 - config_name: similarities_abstraction_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 23416 num_examples: 76 - name: train num_bytes: 18545 num_examples: 60 - name: validation num_bytes: 4871 num_examples: 16 download_size: 31521 dataset_size: 46832 - config_name: simp_turing_concept_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1017646 num_examples: 6390 - name: train num_bytes: 813220 num_examples: 5112 - name: validation num_bytes: 204426 num_examples: 1278 download_size: 402574 dataset_size: 2035292 - config_name: simple_arithmetic_json_multiple_choice_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 924 num_examples: 8 - name: train num_bytes: 0 num_examples: 0 - name: validation num_bytes: 0 num_examples: 0 download_size: 7777 dataset_size: 924 - config_name: simple_arithmetic_json_subtasks_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1145 num_examples: 30 - name: train num_bytes: 571 num_examples: 15 - name: validation num_bytes: 574 num_examples: 15 download_size: 10460 dataset_size: 2290 - config_name: simple_arithmetic_json_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1145 num_examples: 30 - name: train num_bytes: 540 num_examples: 14 - name: validation num_bytes: 605 num_examples: 16 download_size: 10645 dataset_size: 2290 - config_name: simple_arithmetic_multiple_targets_json_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 414 num_examples: 10 - name: train num_bytes: 0 num_examples: 0 - name: validation num_bytes: 0 num_examples: 0 download_size: 7352 dataset_size: 414 - config_name: simple_ethical_questions_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 76518 num_examples: 115 - name: train num_bytes: 60275 num_examples: 92 - name: validation num_bytes: 16243 num_examples: 23 download_size: 81285 dataset_size: 153036 - config_name: simple_text_editing_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 27865 num_examples: 47 - name: train num_bytes: 18469 num_examples: 31 - name: validation num_bytes: 9396 num_examples: 16 download_size: 27100 dataset_size: 55730 - config_name: snarks_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 45717 num_examples: 181 - name: train num_bytes: 36989 num_examples: 145 - name: validation num_bytes: 8728 num_examples: 36 download_size: 45434 dataset_size: 91434 - config_name: social_iqa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 643162 num_examples: 1935 - name: train num_bytes: 515686 num_examples: 1548 - name: validation num_bytes: 127476 num_examples: 387 download_size: 684043 dataset_size: 1286324 - config_name: social_support_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 366705 num_examples: 897 - name: train num_bytes: 294793 num_examples: 718 - name: validation num_bytes: 71912 num_examples: 179 download_size: 288867 dataset_size: 733410 - config_name: sports_understanding_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 226654 num_examples: 986 - name: train num_bytes: 181328 num_examples: 789 - name: validation num_bytes: 45326 num_examples: 197 download_size: 82415 dataset_size: 453308 - config_name: strange_stories_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 120500 num_examples: 174 - name: train num_bytes: 98055 num_examples: 140 - name: validation num_bytes: 22445 num_examples: 34 download_size: 106428 dataset_size: 241000 - config_name: strategyqa_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 659967 num_examples: 2289 - name: train num_bytes: 527670 num_examples: 1832 - name: validation num_bytes: 132297 num_examples: 457 download_size: 814405 dataset_size: 1319934 - config_name: sufficient_information_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 9425 num_examples: 39 - name: train num_bytes: 5594 num_examples: 23 - name: validation num_bytes: 3831 num_examples: 16 download_size: 17766 dataset_size: 18850 - config_name: suicide_risk_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 37952 num_examples: 40 - name: train num_bytes: 23067 num_examples: 24 - name: validation num_bytes: 14885 num_examples: 16 download_size: 60518 dataset_size: 75904 - config_name: swahili_english_proverbs_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 90246 num_examples: 153 - name: train num_bytes: 72467 num_examples: 123 - name: validation num_bytes: 17779 num_examples: 30 download_size: 95186 dataset_size: 180492 - config_name: swedish_to_german_proverbs_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 35204 num_examples: 72 - name: train num_bytes: 27266 num_examples: 56 - name: validation num_bytes: 7938 num_examples: 16 download_size: 55102 dataset_size: 70408 - config_name: symbol_interpretation_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1148958 num_examples: 990 - name: train num_bytes: 927326 num_examples: 795 - name: validation num_bytes: 221632 num_examples: 195 download_size: 320412 dataset_size: 2297916 - config_name: temporal_sequences_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 687086 num_examples: 1000 - name: train num_bytes: 549808 num_examples: 800 - name: validation num_bytes: 137278 num_examples: 200 download_size: 295316 dataset_size: 1374172 - config_name: tense_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 43882 num_examples: 286 - name: train num_bytes: 35466 num_examples: 229 - name: validation num_bytes: 8416 num_examples: 57 download_size: 51466 dataset_size: 87764 - config_name: timedial_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 2763178 num_examples: 2550 - name: train num_bytes: 2217190 num_examples: 2040 - name: validation num_bytes: 545988 num_examples: 510 download_size: 2444115 dataset_size: 5526356 - config_name: topical_chat_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 30927758 num_examples: 22295 - name: train num_bytes: 24827254 num_examples: 17836 - name: validation num_bytes: 6100504 num_examples: 4459 download_size: 23505731 dataset_size: 61855516 - config_name: tracking_shuffled_objects_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 2775972 num_examples: 3750 - name: train num_bytes: 2224037 num_examples: 3000 - name: validation num_bytes: 551935 num_examples: 750 download_size: 738413 dataset_size: 5551944 - config_name: understanding_fables_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 227748 num_examples: 189 - name: train num_bytes: 181000 num_examples: 152 - name: validation num_bytes: 46748 num_examples: 37 download_size: 237036 dataset_size: 455496 - config_name: undo_permutation_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 196118 num_examples: 300 - name: train num_bytes: 158562 num_examples: 240 - name: validation num_bytes: 37556 num_examples: 60 download_size: 137204 dataset_size: 392236 - config_name: unit_conversion_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 4028628 num_examples: 23936 - name: train num_bytes: 3230357 num_examples: 19151 - name: validation num_bytes: 798271 num_examples: 4785 download_size: 3208622 dataset_size: 8057256 - config_name: unit_interpretation_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 37363 num_examples: 100 - name: train num_bytes: 29939 num_examples: 80 - name: validation num_bytes: 7424 num_examples: 20 download_size: 34926 dataset_size: 74726 - config_name: unnatural_in_context_learning_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 4599760 num_examples: 73420 - name: train num_bytes: 3679822 num_examples: 58736 - name: validation num_bytes: 919938 num_examples: 14684 download_size: 3840657 dataset_size: 9199520 - config_name: vitaminc_fact_verification_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 32361818 num_examples: 54668 - name: train num_bytes: 25889850 num_examples: 43735 - name: validation num_bytes: 6471968 num_examples: 10933 download_size: 14264790 dataset_size: 64723636 - config_name: what_is_the_tao_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 13268 num_examples: 36 - name: train num_bytes: 7435 num_examples: 20 - name: validation num_bytes: 5833 num_examples: 16 download_size: 27585 dataset_size: 26536 - config_name: which_wiki_edit_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 6331683 num_examples: 571 - name: train num_bytes: 5233870 num_examples: 457 - name: validation num_bytes: 1097813 num_examples: 114 download_size: 3914574 dataset_size: 12663366 - config_name: winowhy_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 1002434 num_examples: 2862 - name: train num_bytes: 800520 num_examples: 2290 - name: validation num_bytes: 201914 num_examples: 572 download_size: 449218 dataset_size: 2004868 - config_name: word_sorting_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 491054 num_examples: 1900 - name: train num_bytes: 392738 num_examples: 1520 - name: validation num_bytes: 98316 num_examples: 380 download_size: 641536 dataset_size: 982108 - config_name: word_unscrambling_zero_shot features: - name: idx dtype: int32 - name: inputs dtype: string - name: targets sequence: string - name: multiple_choice_targets sequence: string - name: multiple_choice_scores sequence: int32 splits: - name: default num_bytes: 882364 num_examples: 8917 - name: train num_bytes: 705755 num_examples: 7134 - name: validation num_bytes: 176609 num_examples: 1783 download_size: 563799 dataset_size: 1764728 configs: - config_name: abstract_narrative_understanding_zero_shot data_files: - split: default path: abstract_narrative_understanding_zero_shot/default-* - split: train path: abstract_narrative_understanding_zero_shot/train-* - split: validation path: abstract_narrative_understanding_zero_shot/validation-* - config_name: anachronisms_zero_shot data_files: - split: default path: anachronisms_zero_shot/default-* - split: train path: anachronisms_zero_shot/train-* - split: validation path: anachronisms_zero_shot/validation-* - config_name: analogical_similarity_zero_shot data_files: - split: default path: analogical_similarity_zero_shot/default-* - split: train path: analogical_similarity_zero_shot/train-* - split: validation path: analogical_similarity_zero_shot/validation-* - config_name: analytic_entailment_zero_shot data_files: - split: default path: analytic_entailment_zero_shot/default-* - split: train path: analytic_entailment_zero_shot/train-* - split: validation path: analytic_entailment_zero_shot/validation-* - config_name: arithmetic_zero_shot data_files: - split: default path: arithmetic_zero_shot/default-* - split: train path: arithmetic_zero_shot/train-* - split: validation path: arithmetic_zero_shot/validation-* - config_name: ascii_word_recognition_zero_shot data_files: - split: default path: ascii_word_recognition_zero_shot/default-* - split: train path: ascii_word_recognition_zero_shot/train-* - split: validation path: ascii_word_recognition_zero_shot/validation-* - config_name: authorship_verification_zero_shot data_files: - split: default path: authorship_verification_zero_shot/default-* - split: train path: authorship_verification_zero_shot/train-* - split: validation path: authorship_verification_zero_shot/validation-* - config_name: auto_categorization_zero_shot data_files: - split: default path: auto_categorization_zero_shot/default-* - split: train path: auto_categorization_zero_shot/train-* - split: validation path: auto_categorization_zero_shot/validation-* - config_name: auto_debugging_zero_shot data_files: - split: default path: auto_debugging_zero_shot/default-* - split: train path: auto_debugging_zero_shot/train-* - split: validation path: auto_debugging_zero_shot/validation-* - config_name: bbq_lite_json_zero_shot data_files: - split: default path: bbq_lite_json_zero_shot/default-* - split: train path: bbq_lite_json_zero_shot/train-* - split: validation path: bbq_lite_json_zero_shot/validation-* - config_name: bridging_anaphora_resolution_barqa_zero_shot data_files: - split: default path: bridging_anaphora_resolution_barqa_zero_shot/default-* - split: train path: bridging_anaphora_resolution_barqa_zero_shot/train-* - split: validation path: bridging_anaphora_resolution_barqa_zero_shot/validation-* - config_name: causal_judgment_zero_shot data_files: - split: default path: causal_judgment_zero_shot/default-* - split: train path: causal_judgment_zero_shot/train-* - split: validation path: causal_judgment_zero_shot/validation-* - config_name: cause_and_effect_zero_shot data_files: - split: default path: cause_and_effect_zero_shot/default-* - split: train path: cause_and_effect_zero_shot/train-* - split: validation path: cause_and_effect_zero_shot/validation-* - config_name: checkmate_in_one_zero_shot data_files: - split: default path: checkmate_in_one_zero_shot/default-* - split: train path: checkmate_in_one_zero_shot/train-* - split: validation path: checkmate_in_one_zero_shot/validation-* - config_name: chess_state_tracking_zero_shot data_files: - split: default path: chess_state_tracking_zero_shot/default-* - split: train path: chess_state_tracking_zero_shot/train-* - split: validation path: chess_state_tracking_zero_shot/validation-* - config_name: chinese_remainder_theorem_zero_shot data_files: - split: default path: chinese_remainder_theorem_zero_shot/default-* - split: train path: chinese_remainder_theorem_zero_shot/train-* - split: validation path: chinese_remainder_theorem_zero_shot/validation-* - config_name: cifar10_classification_zero_shot data_files: - split: default path: cifar10_classification_zero_shot/default-* - split: train path: cifar10_classification_zero_shot/train-* - split: validation path: cifar10_classification_zero_shot/validation-* - config_name: code_line_description_zero_shot data_files: - split: default path: code_line_description_zero_shot/default-* - split: train path: code_line_description_zero_shot/train-* - split: validation path: code_line_description_zero_shot/validation-* - config_name: codenames_zero_shot data_files: - split: default path: codenames_zero_shot/default-* - split: train path: codenames_zero_shot/train-* - split: validation path: codenames_zero_shot/validation-* - config_name: color_zero_shot data_files: - split: default path: color_zero_shot/default-* - split: train path: color_zero_shot/train-* - split: validation path: color_zero_shot/validation-* - config_name: common_morpheme_zero_shot data_files: - split: default path: common_morpheme_zero_shot/default-* - split: train path: common_morpheme_zero_shot/train-* - split: validation path: common_morpheme_zero_shot/validation-* - config_name: conceptual_combinations_zero_shot data_files: - split: default path: conceptual_combinations_zero_shot/default-* - split: train path: conceptual_combinations_zero_shot/train-* - split: validation path: conceptual_combinations_zero_shot/validation-* - config_name: conlang_translation_zero_shot data_files: - split: default path: conlang_translation_zero_shot/default-* - split: train path: conlang_translation_zero_shot/train-* - split: validation path: conlang_translation_zero_shot/validation-* - config_name: contextual_parametric_knowledge_conflicts_zero_shot data_files: - split: default path: contextual_parametric_knowledge_conflicts_zero_shot/default-* - split: train path: contextual_parametric_knowledge_conflicts_zero_shot/train-* - split: validation path: contextual_parametric_knowledge_conflicts_zero_shot/validation-* - config_name: crash_blossom_zero_shot data_files: - split: default path: crash_blossom_zero_shot/default-* - split: train path: crash_blossom_zero_shot/train-* - split: validation path: crash_blossom_zero_shot/validation-* - config_name: crass_ai_zero_shot data_files: - split: default path: crass_ai_zero_shot/default-* - split: train path: crass_ai_zero_shot/train-* - split: validation path: crass_ai_zero_shot/validation-* - config_name: cryobiology_spanish_zero_shot data_files: - split: default path: cryobiology_spanish_zero_shot/default-* - split: train path: cryobiology_spanish_zero_shot/train-* - split: validation path: cryobiology_spanish_zero_shot/validation-* - config_name: cryptonite_zero_shot data_files: - split: default path: cryptonite_zero_shot/default-* - split: train path: cryptonite_zero_shot/train-* - split: validation path: cryptonite_zero_shot/validation-* - config_name: cs_algorithms_zero_shot data_files: - split: default path: cs_algorithms_zero_shot/default-* - split: train path: cs_algorithms_zero_shot/train-* - split: validation path: cs_algorithms_zero_shot/validation-* - config_name: dark_humor_detection_zero_shot data_files: - split: default path: dark_humor_detection_zero_shot/default-* - split: train path: dark_humor_detection_zero_shot/train-* - split: validation path: dark_humor_detection_zero_shot/validation-* - config_name: date_understanding_zero_shot data_files: - split: default path: date_understanding_zero_shot/default-* - split: train path: date_understanding_zero_shot/train-* - split: validation path: date_understanding_zero_shot/validation-* - config_name: disambiguation_qa_zero_shot data_files: - split: default path: disambiguation_qa_zero_shot/default-* - split: train path: disambiguation_qa_zero_shot/train-* - split: validation path: disambiguation_qa_zero_shot/validation-* - config_name: discourse_marker_prediction_zero_shot data_files: - split: default path: discourse_marker_prediction_zero_shot/default-* - split: train path: discourse_marker_prediction_zero_shot/train-* - split: validation path: discourse_marker_prediction_zero_shot/validation-* - config_name: disfl_qa_zero_shot data_files: - split: default path: disfl_qa_zero_shot/default-* - split: train path: disfl_qa_zero_shot/train-* - split: validation path: disfl_qa_zero_shot/validation-* - config_name: dyck_languages_zero_shot data_files: - split: default path: dyck_languages_zero_shot/default-* - split: train path: dyck_languages_zero_shot/train-* - split: validation path: dyck_languages_zero_shot/validation-* - config_name: elementary_math_qa_zero_shot data_files: - split: default path: elementary_math_qa_zero_shot/default-* - split: train path: elementary_math_qa_zero_shot/train-* - split: validation path: elementary_math_qa_zero_shot/validation-* - config_name: emoji_movie_zero_shot data_files: - split: default path: emoji_movie_zero_shot/default-* - split: train path: emoji_movie_zero_shot/train-* - split: validation path: emoji_movie_zero_shot/validation-* - config_name: emojis_emotion_prediction_zero_shot data_files: - split: default path: emojis_emotion_prediction_zero_shot/default-* - split: train path: emojis_emotion_prediction_zero_shot/train-* - split: validation path: emojis_emotion_prediction_zero_shot/validation-* - config_name: empirical_judgments_zero_shot data_files: - split: default path: empirical_judgments_zero_shot/default-* - split: train path: empirical_judgments_zero_shot/train-* - split: validation path: empirical_judgments_zero_shot/validation-* - config_name: english_proverbs_zero_shot data_files: - split: default path: english_proverbs_zero_shot/default-* - split: train path: english_proverbs_zero_shot/train-* - split: validation path: english_proverbs_zero_shot/validation-* - config_name: english_russian_proverbs_zero_shot data_files: - split: default path: english_russian_proverbs_zero_shot/default-* - split: train path: english_russian_proverbs_zero_shot/train-* - split: validation path: english_russian_proverbs_zero_shot/validation-* - config_name: entailed_polarity_hindi_zero_shot data_files: - split: default path: entailed_polarity_hindi_zero_shot/default-* - split: train path: entailed_polarity_hindi_zero_shot/train-* - split: validation path: entailed_polarity_hindi_zero_shot/validation-* - config_name: entailed_polarity_zero_shot data_files: - split: default path: entailed_polarity_zero_shot/default-* - split: train path: entailed_polarity_zero_shot/train-* - split: validation path: entailed_polarity_zero_shot/validation-* - config_name: epistemic_reasoning_zero_shot data_files: - split: default path: epistemic_reasoning_zero_shot/default-* - split: train path: epistemic_reasoning_zero_shot/train-* - split: validation path: epistemic_reasoning_zero_shot/validation-* - config_name: evaluating_information_essentiality_zero_shot data_files: - split: default path: evaluating_information_essentiality_zero_shot/default-* - split: train path: evaluating_information_essentiality_zero_shot/train-* - split: validation path: evaluating_information_essentiality_zero_shot/validation-* - config_name: fact_checker_zero_shot data_files: - split: default path: fact_checker_zero_shot/default-* - split: train path: fact_checker_zero_shot/train-* - split: validation path: fact_checker_zero_shot/validation-* - config_name: fantasy_reasoning_zero_shot data_files: - split: default path: fantasy_reasoning_zero_shot/default-* - split: train path: fantasy_reasoning_zero_shot/train-* - split: validation path: fantasy_reasoning_zero_shot/validation-* - config_name: few_shot_nlg_zero_shot data_files: - split: default path: few_shot_nlg_zero_shot/default-* - split: train path: few_shot_nlg_zero_shot/train-* - split: validation path: few_shot_nlg_zero_shot/validation-* - config_name: figure_of_speech_detection_zero_shot data_files: - split: default path: figure_of_speech_detection_zero_shot/default-* - split: train path: figure_of_speech_detection_zero_shot/train-* - split: validation path: figure_of_speech_detection_zero_shot/validation-* - config_name: formal_fallacies_syllogisms_negation_zero_shot data_files: - split: default path: formal_fallacies_syllogisms_negation_zero_shot/default-* - split: train path: formal_fallacies_syllogisms_negation_zero_shot/train-* - split: validation path: formal_fallacies_syllogisms_negation_zero_shot/validation-* - config_name: gem_zero_shot data_files: - split: default path: gem_zero_shot/default-* - split: train path: gem_zero_shot/train-* - split: validation path: gem_zero_shot/validation-* - config_name: gender_inclusive_sentences_german_zero_shot data_files: - split: default path: gender_inclusive_sentences_german_zero_shot/default-* - split: train path: gender_inclusive_sentences_german_zero_shot/train-* - split: validation path: gender_inclusive_sentences_german_zero_shot/validation-* - config_name: general_knowledge_zero_shot data_files: - split: default path: general_knowledge_zero_shot/default-* - split: train path: general_knowledge_zero_shot/train-* - split: validation path: general_knowledge_zero_shot/validation-* - config_name: geometric_shapes_zero_shot data_files: - split: default path: geometric_shapes_zero_shot/default-* - split: train path: geometric_shapes_zero_shot/train-* - split: validation path: geometric_shapes_zero_shot/validation-* - config_name: goal_step_wikihow_zero_shot data_files: - split: default path: goal_step_wikihow_zero_shot/default-* - split: train path: goal_step_wikihow_zero_shot/train-* - split: validation path: goal_step_wikihow_zero_shot/validation-* - config_name: gre_reading_comprehension_zero_shot data_files: - split: default path: gre_reading_comprehension_zero_shot/default-* - split: train path: gre_reading_comprehension_zero_shot/train-* - split: validation path: gre_reading_comprehension_zero_shot/validation-* - config_name: hhh_alignment_zero_shot data_files: - split: default path: hhh_alignment_zero_shot/default-* - split: train path: hhh_alignment_zero_shot/train-* - split: validation path: hhh_alignment_zero_shot/validation-* - config_name: hindi_question_answering_zero_shot data_files: - split: default path: hindi_question_answering_zero_shot/default-* - split: train path: hindi_question_answering_zero_shot/train-* - split: validation path: hindi_question_answering_zero_shot/validation-* - config_name: hindu_knowledge_zero_shot data_files: - split: default path: hindu_knowledge_zero_shot/default-* - split: train path: hindu_knowledge_zero_shot/train-* - split: validation path: hindu_knowledge_zero_shot/validation-* - config_name: hinglish_toxicity_zero_shot data_files: - split: default path: hinglish_toxicity_zero_shot/default-* - split: train path: hinglish_toxicity_zero_shot/train-* - split: validation path: hinglish_toxicity_zero_shot/validation-* - config_name: human_organs_senses_zero_shot data_files: - split: default path: human_organs_senses_zero_shot/default-* - split: train path: human_organs_senses_zero_shot/train-* - split: validation path: human_organs_senses_zero_shot/validation-* - config_name: hyperbaton_zero_shot data_files: - split: default path: hyperbaton_zero_shot/default-* - split: train path: hyperbaton_zero_shot/train-* - split: validation path: hyperbaton_zero_shot/validation-* - config_name: identify_math_theorems_zero_shot data_files: - split: default path: identify_math_theorems_zero_shot/default-* - split: train path: identify_math_theorems_zero_shot/train-* - split: validation path: identify_math_theorems_zero_shot/validation-* - config_name: identify_odd_metaphor_zero_shot data_files: - split: default path: identify_odd_metaphor_zero_shot/default-* - split: train path: identify_odd_metaphor_zero_shot/train-* - split: validation path: identify_odd_metaphor_zero_shot/validation-* - config_name: implicatures_zero_shot data_files: - split: default path: implicatures_zero_shot/default-* - split: train path: implicatures_zero_shot/train-* - split: validation path: implicatures_zero_shot/validation-* - config_name: implicit_relations_zero_shot data_files: - split: default path: implicit_relations_zero_shot/default-* - split: train path: implicit_relations_zero_shot/train-* - split: validation path: implicit_relations_zero_shot/validation-* - config_name: intent_recognition_zero_shot data_files: - split: default path: intent_recognition_zero_shot/default-* - split: train path: intent_recognition_zero_shot/train-* - split: validation path: intent_recognition_zero_shot/validation-* - config_name: international_phonetic_alphabet_nli_zero_shot data_files: - split: default path: international_phonetic_alphabet_nli_zero_shot/default-* - split: train path: international_phonetic_alphabet_nli_zero_shot/train-* - split: validation path: international_phonetic_alphabet_nli_zero_shot/validation-* - config_name: international_phonetic_alphabet_transliterate_zero_shot data_files: - split: default path: international_phonetic_alphabet_transliterate_zero_shot/default-* - split: train path: international_phonetic_alphabet_transliterate_zero_shot/train-* - split: validation path: international_phonetic_alphabet_transliterate_zero_shot/validation-* - config_name: intersect_geometry_zero_shot data_files: - split: default path: intersect_geometry_zero_shot/default-* - split: train path: intersect_geometry_zero_shot/train-* - split: validation path: intersect_geometry_zero_shot/validation-* - config_name: irony_identification_zero_shot data_files: - split: default path: irony_identification_zero_shot/default-* - split: train path: irony_identification_zero_shot/train-* - split: validation path: irony_identification_zero_shot/validation-* - config_name: kanji_ascii_zero_shot data_files: - split: default path: kanji_ascii_zero_shot/default-* - split: train path: kanji_ascii_zero_shot/train-* - split: validation path: kanji_ascii_zero_shot/validation-* - config_name: kannada_zero_shot data_files: - split: default path: kannada_zero_shot/default-* - split: train path: kannada_zero_shot/train-* - split: validation path: kannada_zero_shot/validation-* - config_name: key_value_maps_zero_shot data_files: - split: default path: key_value_maps_zero_shot/default-* - split: train path: key_value_maps_zero_shot/train-* - split: validation path: key_value_maps_zero_shot/validation-* - config_name: known_unknowns_zero_shot data_files: - split: default path: known_unknowns_zero_shot/default-* - split: train path: known_unknowns_zero_shot/train-* - split: validation path: known_unknowns_zero_shot/validation-* - config_name: language_games_zero_shot data_files: - split: default path: language_games_zero_shot/default-* - split: train path: language_games_zero_shot/train-* - split: validation path: language_games_zero_shot/validation-* - config_name: language_identification_zero_shot data_files: - split: default path: language_identification_zero_shot/default-* - split: train path: language_identification_zero_shot/train-* - split: validation path: language_identification_zero_shot/validation-* - config_name: linguistic_mappings_zero_shot data_files: - split: default path: linguistic_mappings_zero_shot/default-* - split: train path: linguistic_mappings_zero_shot/train-* - split: validation path: linguistic_mappings_zero_shot/validation-* - config_name: linguistics_puzzles_zero_shot data_files: - split: default path: linguistics_puzzles_zero_shot/default-* - split: train path: linguistics_puzzles_zero_shot/train-* - split: validation path: linguistics_puzzles_zero_shot/validation-* - config_name: list_functions_zero_shot data_files: - split: default path: list_functions_zero_shot/default-* - split: train path: list_functions_zero_shot/train-* - split: validation path: list_functions_zero_shot/validation-* - config_name: logic_grid_puzzle_zero_shot data_files: - split: default path: logic_grid_puzzle_zero_shot/default-* - split: train path: logic_grid_puzzle_zero_shot/train-* - split: validation path: logic_grid_puzzle_zero_shot/validation-* - config_name: logical_args_zero_shot data_files: - split: default path: logical_args_zero_shot/default-* - split: train path: logical_args_zero_shot/train-* - split: validation path: logical_args_zero_shot/validation-* - config_name: logical_deduction_zero_shot data_files: - split: default path: logical_deduction_zero_shot/default-* - split: train path: logical_deduction_zero_shot/train-* - split: validation path: logical_deduction_zero_shot/validation-* - config_name: logical_fallacy_detection_zero_shot data_files: - split: default path: logical_fallacy_detection_zero_shot/default-* - split: train path: logical_fallacy_detection_zero_shot/train-* - split: validation path: logical_fallacy_detection_zero_shot/validation-* - config_name: logical_sequence_zero_shot data_files: - split: default path: logical_sequence_zero_shot/default-* - split: train path: logical_sequence_zero_shot/train-* - split: validation path: logical_sequence_zero_shot/validation-* - config_name: mathematical_induction_zero_shot data_files: - split: default path: mathematical_induction_zero_shot/default-* - split: train path: mathematical_induction_zero_shot/train-* - split: validation path: mathematical_induction_zero_shot/validation-* - config_name: matrixshapes_zero_shot data_files: - split: default path: matrixshapes_zero_shot/default-* - split: train path: matrixshapes_zero_shot/train-* - split: validation path: matrixshapes_zero_shot/validation-* - config_name: metaphor_boolean_zero_shot data_files: - split: default path: metaphor_boolean_zero_shot/default-* - split: train path: metaphor_boolean_zero_shot/train-* - split: validation path: metaphor_boolean_zero_shot/validation-* - config_name: metaphor_understanding_zero_shot data_files: - split: default path: metaphor_understanding_zero_shot/default-* - split: train path: metaphor_understanding_zero_shot/train-* - split: validation path: metaphor_understanding_zero_shot/validation-* - config_name: minute_mysteries_qa_zero_shot data_files: - split: default path: minute_mysteries_qa_zero_shot/default-* - split: train path: minute_mysteries_qa_zero_shot/train-* - split: validation path: minute_mysteries_qa_zero_shot/validation-* - config_name: misconceptions_russian_zero_shot data_files: - split: default path: misconceptions_russian_zero_shot/default-* - split: train path: misconceptions_russian_zero_shot/train-* - split: validation path: misconceptions_russian_zero_shot/validation-* - config_name: misconceptions_zero_shot data_files: - split: default path: misconceptions_zero_shot/default-* - split: train path: misconceptions_zero_shot/train-* - split: validation path: misconceptions_zero_shot/validation-* - config_name: mnist_ascii_zero_shot data_files: - split: default path: mnist_ascii_zero_shot/default-* - split: train path: mnist_ascii_zero_shot/train-* - split: validation path: mnist_ascii_zero_shot/validation-* - config_name: modified_arithmetic_zero_shot data_files: - split: default path: modified_arithmetic_zero_shot/default-* - split: train path: modified_arithmetic_zero_shot/train-* - split: validation path: modified_arithmetic_zero_shot/validation-* - config_name: moral_permissibility_zero_shot data_files: - split: default path: moral_permissibility_zero_shot/default-* - split: train path: moral_permissibility_zero_shot/train-* - split: validation path: moral_permissibility_zero_shot/validation-* - config_name: movie_dialog_same_or_different_zero_shot data_files: - split: default path: movie_dialog_same_or_different_zero_shot/default-* - split: train path: movie_dialog_same_or_different_zero_shot/train-* - split: validation path: movie_dialog_same_or_different_zero_shot/validation-* - config_name: movie_recommendation_zero_shot data_files: - split: default path: movie_recommendation_zero_shot/default-* - split: train path: movie_recommendation_zero_shot/train-* - split: validation path: movie_recommendation_zero_shot/validation-* - config_name: mult_data_wrangling_zero_shot data_files: - split: default path: mult_data_wrangling_zero_shot/default-* - split: train path: mult_data_wrangling_zero_shot/train-* - split: validation path: mult_data_wrangling_zero_shot/validation-* - config_name: multiemo_zero_shot data_files: - split: default path: multiemo_zero_shot/default-* - split: train path: multiemo_zero_shot/train-* - split: validation path: multiemo_zero_shot/validation-* - config_name: natural_instructions_zero_shot data_files: - split: default path: natural_instructions_zero_shot/default-* - split: train path: natural_instructions_zero_shot/train-* - split: validation path: natural_instructions_zero_shot/validation-* - config_name: navigate_zero_shot data_files: - split: default path: navigate_zero_shot/default-* - split: train path: navigate_zero_shot/train-* - split: validation path: navigate_zero_shot/validation-* - config_name: nonsense_words_grammar_zero_shot data_files: - split: default path: nonsense_words_grammar_zero_shot/default-* - split: train path: nonsense_words_grammar_zero_shot/train-* - split: validation path: nonsense_words_grammar_zero_shot/validation-* - config_name: novel_concepts_zero_shot data_files: - split: default path: novel_concepts_zero_shot/default-* - split: train path: novel_concepts_zero_shot/train-* - split: validation path: novel_concepts_zero_shot/validation-* - config_name: object_counting_zero_shot data_files: - split: default path: object_counting_zero_shot/default-* - split: train path: object_counting_zero_shot/train-* - split: validation path: object_counting_zero_shot/validation-* - config_name: odd_one_out_zero_shot data_files: - split: default path: odd_one_out_zero_shot/default-* - split: train path: odd_one_out_zero_shot/train-* - split: validation path: odd_one_out_zero_shot/validation-* - config_name: operators_zero_shot data_files: - split: default path: operators_zero_shot/default-* - split: train path: operators_zero_shot/train-* - split: validation path: operators_zero_shot/validation-* - config_name: paragraph_segmentation_zero_shot data_files: - split: default path: paragraph_segmentation_zero_shot/default-* - split: train path: paragraph_segmentation_zero_shot/train-* - split: validation path: paragraph_segmentation_zero_shot/validation-* - config_name: parsinlu_qa_zero_shot data_files: - split: default path: parsinlu_qa_zero_shot/default-* - split: train path: parsinlu_qa_zero_shot/train-* - split: validation path: parsinlu_qa_zero_shot/validation-* - config_name: parsinlu_reading_comprehension_zero_shot data_files: - split: default path: parsinlu_reading_comprehension_zero_shot/default-* - split: train path: parsinlu_reading_comprehension_zero_shot/train-* - split: validation path: parsinlu_reading_comprehension_zero_shot/validation-* - config_name: penguins_in_a_table_zero_shot data_files: - split: default path: penguins_in_a_table_zero_shot/default-* - split: train path: penguins_in_a_table_zero_shot/train-* - split: validation path: penguins_in_a_table_zero_shot/validation-* - config_name: periodic_elements_zero_shot data_files: - split: default path: periodic_elements_zero_shot/default-* - split: train path: periodic_elements_zero_shot/train-* - split: validation path: periodic_elements_zero_shot/validation-* - config_name: persian_idioms_zero_shot data_files: - split: default path: persian_idioms_zero_shot/default-* - split: train path: persian_idioms_zero_shot/train-* - split: validation path: persian_idioms_zero_shot/validation-* - config_name: phrase_relatedness_zero_shot data_files: - split: default path: phrase_relatedness_zero_shot/default-* - split: train path: phrase_relatedness_zero_shot/train-* - split: validation path: phrase_relatedness_zero_shot/validation-* - config_name: physical_intuition_zero_shot data_files: - split: default path: physical_intuition_zero_shot/default-* - split: train path: physical_intuition_zero_shot/train-* - split: validation path: physical_intuition_zero_shot/validation-* - config_name: physics_questions_zero_shot data_files: - split: default path: physics_questions_zero_shot/default-* - split: train path: physics_questions_zero_shot/train-* - split: validation path: physics_questions_zero_shot/validation-* - config_name: physics_zero_shot data_files: - split: default path: physics_zero_shot/default-* - split: train path: physics_zero_shot/train-* - split: validation path: physics_zero_shot/validation-* - config_name: play_dialog_same_or_different_zero_shot data_files: - split: default path: play_dialog_same_or_different_zero_shot/default-* - split: train path: play_dialog_same_or_different_zero_shot/train-* - split: validation path: play_dialog_same_or_different_zero_shot/validation-* - config_name: polish_sequence_labeling_zero_shot data_files: - split: default path: polish_sequence_labeling_zero_shot/default-* - split: train path: polish_sequence_labeling_zero_shot/train-* - split: validation path: polish_sequence_labeling_zero_shot/validation-* - config_name: presuppositions_as_nli_zero_shot data_files: - split: default path: presuppositions_as_nli_zero_shot/default-* - split: train path: presuppositions_as_nli_zero_shot/train-* - split: validation path: presuppositions_as_nli_zero_shot/validation-* - config_name: qa_wikidata_zero_shot data_files: - split: default path: qa_wikidata_zero_shot/default-* - split: train path: qa_wikidata_zero_shot/train-* - split: validation path: qa_wikidata_zero_shot/validation-* - config_name: question_selection_zero_shot data_files: - split: default path: question_selection_zero_shot/default-* - split: train path: question_selection_zero_shot/train-* - split: validation path: question_selection_zero_shot/validation-* - config_name: real_or_fake_text_zero_shot data_files: - split: default path: real_or_fake_text_zero_shot/default-* - split: train path: real_or_fake_text_zero_shot/train-* - split: validation path: real_or_fake_text_zero_shot/validation-* - config_name: reasoning_about_colored_objects_zero_shot data_files: - split: default path: reasoning_about_colored_objects_zero_shot/default-* - split: train path: reasoning_about_colored_objects_zero_shot/train-* - split: validation path: reasoning_about_colored_objects_zero_shot/validation-* - config_name: repeat_copy_logic_zero_shot data_files: - split: default path: repeat_copy_logic_zero_shot/default-* - split: train path: repeat_copy_logic_zero_shot/train-* - split: validation path: repeat_copy_logic_zero_shot/validation-* - config_name: rephrase_zero_shot data_files: - split: default path: rephrase_zero_shot/default-* - split: train path: rephrase_zero_shot/train-* - split: validation path: rephrase_zero_shot/validation-* - config_name: riddle_sense_zero_shot data_files: - split: default path: riddle_sense_zero_shot/default-* - split: train path: riddle_sense_zero_shot/train-* - split: validation path: riddle_sense_zero_shot/validation-* - config_name: ruin_names_zero_shot data_files: - split: default path: ruin_names_zero_shot/default-* - split: train path: ruin_names_zero_shot/train-* - split: validation path: ruin_names_zero_shot/validation-* - config_name: salient_translation_error_detection_zero_shot data_files: - split: default path: salient_translation_error_detection_zero_shot/default-* - split: train path: salient_translation_error_detection_zero_shot/train-* - split: validation path: salient_translation_error_detection_zero_shot/validation-* - config_name: scientific_press_release_zero_shot data_files: - split: default path: scientific_press_release_zero_shot/default-* - split: train path: scientific_press_release_zero_shot/train-* - split: validation path: scientific_press_release_zero_shot/validation-* - config_name: semantic_parsing_in_context_sparc_zero_shot data_files: - split: default path: semantic_parsing_in_context_sparc_zero_shot/default-* - split: train path: semantic_parsing_in_context_sparc_zero_shot/train-* - split: validation path: semantic_parsing_in_context_sparc_zero_shot/validation-* - config_name: semantic_parsing_spider_zero_shot data_files: - split: default path: semantic_parsing_spider_zero_shot/default-* - split: train path: semantic_parsing_spider_zero_shot/train-* - split: validation path: semantic_parsing_spider_zero_shot/validation-* - config_name: sentence_ambiguity_zero_shot data_files: - split: default path: sentence_ambiguity_zero_shot/default-* - split: train path: sentence_ambiguity_zero_shot/train-* - split: validation path: sentence_ambiguity_zero_shot/validation-* - config_name: similarities_abstraction_zero_shot data_files: - split: default path: similarities_abstraction_zero_shot/default-* - split: train path: similarities_abstraction_zero_shot/train-* - split: validation path: similarities_abstraction_zero_shot/validation-* - config_name: simp_turing_concept_zero_shot data_files: - split: default path: simp_turing_concept_zero_shot/default-* - split: train path: simp_turing_concept_zero_shot/train-* - split: validation path: simp_turing_concept_zero_shot/validation-* - config_name: simple_arithmetic_json_multiple_choice_zero_shot data_files: - split: default path: simple_arithmetic_json_multiple_choice_zero_shot/default-* - split: train path: simple_arithmetic_json_multiple_choice_zero_shot/train-* - split: validation path: simple_arithmetic_json_multiple_choice_zero_shot/validation-* - config_name: simple_arithmetic_json_subtasks_zero_shot data_files: - split: default path: simple_arithmetic_json_subtasks_zero_shot/default-* - split: train path: simple_arithmetic_json_subtasks_zero_shot/train-* - split: validation path: simple_arithmetic_json_subtasks_zero_shot/validation-* - config_name: simple_arithmetic_json_zero_shot data_files: - split: default path: simple_arithmetic_json_zero_shot/default-* - split: train path: simple_arithmetic_json_zero_shot/train-* - split: validation path: simple_arithmetic_json_zero_shot/validation-* - config_name: simple_arithmetic_multiple_targets_json_zero_shot data_files: - split: default path: simple_arithmetic_multiple_targets_json_zero_shot/default-* - split: train path: simple_arithmetic_multiple_targets_json_zero_shot/train-* - split: validation path: simple_arithmetic_multiple_targets_json_zero_shot/validation-* - config_name: simple_ethical_questions_zero_shot data_files: - split: default path: simple_ethical_questions_zero_shot/default-* - split: train path: simple_ethical_questions_zero_shot/train-* - split: validation path: simple_ethical_questions_zero_shot/validation-* - config_name: simple_text_editing_zero_shot data_files: - split: default path: simple_text_editing_zero_shot/default-* - split: train path: simple_text_editing_zero_shot/train-* - split: validation path: simple_text_editing_zero_shot/validation-* - config_name: snarks_zero_shot data_files: - split: default path: snarks_zero_shot/default-* - split: train path: snarks_zero_shot/train-* - split: validation path: snarks_zero_shot/validation-* - config_name: social_iqa_zero_shot data_files: - split: default path: social_iqa_zero_shot/default-* - split: train path: social_iqa_zero_shot/train-* - split: validation path: social_iqa_zero_shot/validation-* - config_name: social_support_zero_shot data_files: - split: default path: social_support_zero_shot/default-* - split: train path: social_support_zero_shot/train-* - split: validation path: social_support_zero_shot/validation-* - config_name: sports_understanding_zero_shot data_files: - split: default path: sports_understanding_zero_shot/default-* - split: train path: sports_understanding_zero_shot/train-* - split: validation path: sports_understanding_zero_shot/validation-* - config_name: strange_stories_zero_shot data_files: - split: default path: strange_stories_zero_shot/default-* - split: train path: strange_stories_zero_shot/train-* - split: validation path: strange_stories_zero_shot/validation-* - config_name: strategyqa_zero_shot data_files: - split: default path: strategyqa_zero_shot/default-* - split: train path: strategyqa_zero_shot/train-* - split: validation path: strategyqa_zero_shot/validation-* - config_name: sufficient_information_zero_shot data_files: - split: default path: sufficient_information_zero_shot/default-* - split: train path: sufficient_information_zero_shot/train-* - split: validation path: sufficient_information_zero_shot/validation-* - config_name: suicide_risk_zero_shot data_files: - split: default path: suicide_risk_zero_shot/default-* - split: train path: suicide_risk_zero_shot/train-* - split: validation path: suicide_risk_zero_shot/validation-* - config_name: swahili_english_proverbs_zero_shot data_files: - split: default path: swahili_english_proverbs_zero_shot/default-* - split: train path: swahili_english_proverbs_zero_shot/train-* - split: validation path: swahili_english_proverbs_zero_shot/validation-* - config_name: swedish_to_german_proverbs_zero_shot data_files: - split: default path: swedish_to_german_proverbs_zero_shot/default-* - split: train path: swedish_to_german_proverbs_zero_shot/train-* - split: validation path: swedish_to_german_proverbs_zero_shot/validation-* - config_name: symbol_interpretation_zero_shot data_files: - split: default path: symbol_interpretation_zero_shot/default-* - split: train path: symbol_interpretation_zero_shot/train-* - split: validation path: symbol_interpretation_zero_shot/validation-* - config_name: temporal_sequences_zero_shot data_files: - split: default path: temporal_sequences_zero_shot/default-* - split: train path: temporal_sequences_zero_shot/train-* - split: validation path: temporal_sequences_zero_shot/validation-* - config_name: tense_zero_shot data_files: - split: default path: tense_zero_shot/default-* - split: train path: tense_zero_shot/train-* - split: validation path: tense_zero_shot/validation-* - config_name: timedial_zero_shot data_files: - split: default path: timedial_zero_shot/default-* - split: train path: timedial_zero_shot/train-* - split: validation path: timedial_zero_shot/validation-* - config_name: topical_chat_zero_shot data_files: - split: default path: topical_chat_zero_shot/default-* - split: train path: topical_chat_zero_shot/train-* - split: validation path: topical_chat_zero_shot/validation-* - config_name: tracking_shuffled_objects_zero_shot data_files: - split: default path: tracking_shuffled_objects_zero_shot/default-* - split: train path: tracking_shuffled_objects_zero_shot/train-* - split: validation path: tracking_shuffled_objects_zero_shot/validation-* - config_name: understanding_fables_zero_shot data_files: - split: default path: understanding_fables_zero_shot/default-* - split: train path: understanding_fables_zero_shot/train-* - split: validation path: understanding_fables_zero_shot/validation-* - config_name: undo_permutation_zero_shot data_files: - split: default path: undo_permutation_zero_shot/default-* - split: train path: undo_permutation_zero_shot/train-* - split: validation path: undo_permutation_zero_shot/validation-* - config_name: unit_conversion_zero_shot data_files: - split: default path: unit_conversion_zero_shot/default-* - split: train path: unit_conversion_zero_shot/train-* - split: validation path: unit_conversion_zero_shot/validation-* - config_name: unit_interpretation_zero_shot data_files: - split: default path: unit_interpretation_zero_shot/default-* - split: train path: unit_interpretation_zero_shot/train-* - split: validation path: unit_interpretation_zero_shot/validation-* - config_name: unnatural_in_context_learning_zero_shot data_files: - split: default path: unnatural_in_context_learning_zero_shot/default-* - split: train path: unnatural_in_context_learning_zero_shot/train-* - split: validation path: unnatural_in_context_learning_zero_shot/validation-* - config_name: vitaminc_fact_verification_zero_shot data_files: - split: default path: vitaminc_fact_verification_zero_shot/default-* - split: train path: vitaminc_fact_verification_zero_shot/train-* - split: validation path: vitaminc_fact_verification_zero_shot/validation-* - config_name: what_is_the_tao_zero_shot data_files: - split: default path: what_is_the_tao_zero_shot/default-* - split: train path: what_is_the_tao_zero_shot/train-* - split: validation path: what_is_the_tao_zero_shot/validation-* - config_name: which_wiki_edit_zero_shot data_files: - split: default path: which_wiki_edit_zero_shot/default-* - split: train path: which_wiki_edit_zero_shot/train-* - split: validation path: which_wiki_edit_zero_shot/validation-* - config_name: winowhy_zero_shot data_files: - split: default path: winowhy_zero_shot/default-* - split: train path: winowhy_zero_shot/train-* - split: validation path: winowhy_zero_shot/validation-* - config_name: word_sorting_zero_shot data_files: - split: default path: word_sorting_zero_shot/default-* - split: train path: word_sorting_zero_shot/train-* - split: validation path: word_sorting_zero_shot/validation-* - config_name: word_unscrambling_zero_shot data_files: - split: default path: word_unscrambling_zero_shot/default-* - split: train path: word_unscrambling_zero_shot/train-* - split: validation path: word_unscrambling_zero_shot/validation-* --- # Dataset Card for "bigbench" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

lmms-lab/egoschema

lmms-lab

--- license: mit dataset_info: - config_name: GENERATION features: - name: question_idx dtype: string - name: question dtype: string - name: video_idx dtype: string - name: option sequence: string - name: answer dtype: string splits: - name: test num_bytes: 4023963 num_examples: 5031 download_size: 2016753 dataset_size: 4023963 - config_name: MC features: - name: question_idx dtype: string - name: question dtype: string - name: video_idx dtype: string - name: option sequence: string - name: answer dtype: string splits: - name: test num_bytes: 4023963 num_examples: 5031 download_size: 2016753 dataset_size: 4023963 - config_name: MC_PPL features: - name: question_idx dtype: string - name: question dtype: string - name: video_idx dtype: string - name: option sequence: string - name: answer dtype: string splits: - name: test num_bytes: 4023963 num_examples: 5031 download_size: 2016753 dataset_size: 4023963 - config_name: Subset features: - name: question_idx dtype: string - name: question dtype: string - name: video_idx dtype: string - name: option sequence: string - name: answer dtype: string splits: - name: test num_bytes: 424910 num_examples: 500 download_size: 186199 dataset_size: 424910 configs: - config_name: GENERATION data_files: - split: test path: GENERATION/test-* - config_name: MC data_files: - split: test path: MC/test-* - config_name: MC_PPL data_files: - split: test path: MC_PPL/test-* - config_name: Subset data_files: - split: test path: Subset/test-* ---

michaelauli/wiki_bio

michaelauli

--- annotations_creators: - found language_creators: - found language: - en license: - cc-by-sa-3.0 multilinguality: - monolingual size_categories: - 100K<n<1M source_datasets: - original task_categories: - table-to-text task_ids: [] paperswithcode_id: wikibio pretty_name: WikiBio dataset_info: features: - name: input_text struct: - name: table sequence: - name: column_header dtype: string - name: row_number dtype: int16 - name: content dtype: string - name: context dtype: string - name: target_text dtype: string splits: - name: train num_bytes: 619269257 num_examples: 582659 - name: test num_bytes: 77264695 num_examples: 72831 - name: val num_bytes: 77335069 num_examples: 72831 download_size: 333998704 dataset_size: 773869021 --- # Dataset Card for [Dataset Name] ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Repository:** https://github.com/DavidGrangier/wikipedia-biography-dataset - **Paper:** https://arxiv.org/pdf/1603.07771.pdf - **GitHub:** https://github.com/DavidGrangier/wikipedia-biography-dataset ### Dataset Summary This Dataset contains 728321 biographies extracted from Wikipedia containing the first paragraph of the biography and the tabular infobox. ### Supported Tasks and Leaderboards The main purpose of this dataset is developing text generation models. ### Languages English. ## Dataset Structure ### Data Instances More Information Needed ### Data Fields The structure of a single sample is the following: ```json { "input_text":{ "context":"pope michael iii of alexandria\n", "table":{ "column_header":[ "type", "ended", "death_date", "title", "enthroned", "name", "buried", "religion", "predecessor", "nationality", "article_title", "feast_day", "birth_place", "residence", "successor" ], "content":[ "pope", "16 march 907", "16 march 907", "56th of st. mark pope of alexandria & patriarch of the see", "25 april 880", "michael iii of alexandria", "monastery of saint macarius the great", "coptic orthodox christian", "shenouda i", "egyptian", "pope michael iii of alexandria\n", "16 -rrb- march -lrb- 20 baramhat in the coptic calendar", "egypt", "saint mark 's church", "gabriel i" ], "row_number":[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1] } }, "target_text":"pope michael iii of alexandria -lrb- also known as khail iii -rrb- was the coptic pope of alexandria and patriarch of the see of st. mark -lrb- 880 -- 907 -rrb- .\nin 882 , the governor of egypt , ahmad ibn tulun , forced khail to pay heavy contributions , forcing him to sell a church and some attached properties to the local jewish community .\nthis building was at one time believed to have later become the site of the cairo geniza .\n" } ``` where, in the `"table"` field, all the information of the Wikpedia infobox is stored (the header of the infobox is stored in `"column_header"` and the information in the `"content"` field). ### Data Splits - Train: 582659 samples. - Test: 72831 samples. - Validation: 72831 samples. ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data This dataset was announced in the paper <em>Neural Text Generation from Structured Data with Application to the Biography Domain</em> [(arxiv link)](https://arxiv.org/pdf/1603.07771.pdf) and is stored in [this](https://github.com/DavidGrangier/wikipedia-biography-dataset) repo (owned by DavidGrangier). #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information This dataset is ditributed under Creative Comons CC BY-SA 3.0 License. ### Citation Information For refering the original paper in BibTex format: ``` @article{DBLP:journals/corr/LebretGA16, author = {R{\'{e}}mi Lebret and David Grangier and Michael Auli}, title = {Generating Text from Structured Data with Application to the Biography Domain}, journal = {CoRR}, volume = {abs/1603.07771}, year = {2016}, url = {http://arxiv.org/abs/1603.07771}, archivePrefix = {arXiv}, eprint = {1603.07771}, timestamp = {Mon, 13 Aug 2018 16:48:30 +0200}, biburl = {https://dblp.org/rec/journals/corr/LebretGA16.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } ``` ### Contributions Thanks to [@alejandrocros](https://github.com/alejandrocros) for adding this dataset.

nguha/legalbench

nguha

--- language: - en license: other size_categories: - 10K<n<100K task_categories: - text-classification - question-answering - text-generation tags: - legal - law - finance dataset_info: - config_name: abercrombie features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 307 num_examples: 5 - name: test num_bytes: 6240 num_examples: 95 download_size: 19558988 dataset_size: 6547 - config_name: canada_tax_court_outcomes features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2975 num_examples: 6 - name: test num_bytes: 157411 num_examples: 244 download_size: 19558988 dataset_size: 160386 - config_name: citation_prediction_classification features: - name: answer dtype: string - name: citation dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 660 num_examples: 2 - name: test num_bytes: 26112 num_examples: 108 download_size: 19558988 dataset_size: 26772 - config_name: citation_prediction_open features: - name: answer dtype: string - name: circuit dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 555 num_examples: 2 - name: test num_bytes: 13460 num_examples: 53 download_size: 19558988 dataset_size: 14015 - config_name: consumer_contracts_qa features: - name: answer dtype: string - name: contract dtype: string - name: index dtype: string - name: question dtype: string splits: - name: train num_bytes: 9941 num_examples: 4 - name: test num_bytes: 1221320 num_examples: 396 download_size: 19558988 dataset_size: 1231261 - config_name: contract_nli_confidentiality_of_agreement features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4070 num_examples: 8 - name: test num_bytes: 43818 num_examples: 82 download_size: 19558988 dataset_size: 47888 - config_name: contract_nli_explicit_identification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3615 num_examples: 8 - name: test num_bytes: 62133 num_examples: 109 download_size: 19558988 dataset_size: 65748 - config_name: contract_nli_inclusion_of_verbally_conveyed_information features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3817 num_examples: 8 - name: test num_bytes: 81933 num_examples: 139 download_size: 19558988 dataset_size: 85750 - config_name: contract_nli_limited_use features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4855 num_examples: 8 - name: test num_bytes: 98534 num_examples: 208 download_size: 19558988 dataset_size: 103389 - config_name: contract_nli_no_licensing features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2591 num_examples: 8 - name: test num_bytes: 78173 num_examples: 162 download_size: 19558988 dataset_size: 80764 - config_name: contract_nli_notice_on_compelled_disclosure features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3907 num_examples: 8 - name: test num_bytes: 80470 num_examples: 142 download_size: 19558988 dataset_size: 84377 - config_name: contract_nli_permissible_acquirement_of_similar_information features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2736 num_examples: 8 - name: test num_bytes: 87469 num_examples: 178 download_size: 19558988 dataset_size: 90205 - config_name: contract_nli_permissible_copy features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3480 num_examples: 8 - name: test num_bytes: 39015 num_examples: 87 download_size: 19558988 dataset_size: 42495 - config_name: contract_nli_permissible_development_of_similar_information features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3921 num_examples: 8 - name: test num_bytes: 62603 num_examples: 136 download_size: 19558988 dataset_size: 66524 - config_name: contract_nli_permissible_post-agreement_possession features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4608 num_examples: 8 - name: test num_bytes: 65932 num_examples: 111 download_size: 19558988 dataset_size: 70540 - config_name: contract_nli_return_of_confidential_information features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3499 num_examples: 8 - name: test num_bytes: 35672 num_examples: 66 download_size: 19558988 dataset_size: 39171 - config_name: contract_nli_sharing_with_employees features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3173 num_examples: 8 - name: test num_bytes: 104240 num_examples: 170 download_size: 19558988 dataset_size: 107413 - config_name: contract_nli_sharing_with_third-parties features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3249 num_examples: 8 - name: test num_bytes: 104822 num_examples: 180 download_size: 19558988 dataset_size: 108071 - config_name: contract_nli_survival_of_obligations features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2272 num_examples: 8 - name: test num_bytes: 75450 num_examples: 157 download_size: 19558988 dataset_size: 77722 - config_name: contract_qa features: - name: answer dtype: string - name: index dtype: string - name: question dtype: string - name: text dtype: string splits: - name: train num_bytes: 2408 num_examples: 8 - name: test num_bytes: 26370 num_examples: 80 download_size: 19558988 dataset_size: 28778 - config_name: corporate_lobbying features: - name: answer dtype: string - name: bill_summary dtype: string - name: bill_title dtype: string - name: company_description dtype: string - name: company_name dtype: string - name: index dtype: string splits: - name: train num_bytes: 54334 num_examples: 10 - name: test num_bytes: 2974813 num_examples: 490 download_size: 19558988 dataset_size: 3029147 - config_name: cuad_affiliate_license-licensee features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4067 num_examples: 6 - name: test num_bytes: 115798 num_examples: 198 download_size: 19558988 dataset_size: 119865 - config_name: cuad_affiliate_license-licensor features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4247 num_examples: 6 - name: test num_bytes: 64931 num_examples: 88 download_size: 19558988 dataset_size: 69178 - config_name: cuad_anti-assignment features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2070 num_examples: 6 - name: test num_bytes: 513026 num_examples: 1172 download_size: 19558988 dataset_size: 515096 - config_name: cuad_audit_rights features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2555 num_examples: 6 - name: test num_bytes: 526977 num_examples: 1216 download_size: 19558988 dataset_size: 529532 - config_name: cuad_cap_on_liability features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2621 num_examples: 6 - name: test num_bytes: 587220 num_examples: 1246 download_size: 19558988 dataset_size: 589841 - config_name: cuad_change_of_control features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2231 num_examples: 6 - name: test num_bytes: 203823 num_examples: 416 download_size: 19558988 dataset_size: 206054 - config_name: cuad_competitive_restriction_exception features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2774 num_examples: 6 - name: test num_bytes: 115844 num_examples: 220 download_size: 19558988 dataset_size: 118618 - config_name: cuad_covenant_not_to_sue features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2581 num_examples: 6 - name: test num_bytes: 153799 num_examples: 308 download_size: 19558988 dataset_size: 156380 - config_name: cuad_effective_date features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2080 num_examples: 6 - name: test num_bytes: 87802 num_examples: 236 download_size: 19558988 dataset_size: 89882 - config_name: cuad_exclusivity features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 1897 num_examples: 6 - name: test num_bytes: 355097 num_examples: 762 download_size: 19558988 dataset_size: 356994 - config_name: cuad_expiration_date features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 1638 num_examples: 6 - name: test num_bytes: 354232 num_examples: 876 download_size: 19558988 dataset_size: 355870 - config_name: cuad_governing_law features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2420 num_examples: 6 - name: test num_bytes: 337322 num_examples: 876 download_size: 19558988 dataset_size: 339742 - config_name: cuad_insurance features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2537 num_examples: 6 - name: test num_bytes: 475827 num_examples: 1030 download_size: 19558988 dataset_size: 478364 - config_name: cuad_ip_ownership_assignment features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4756 num_examples: 6 - name: test num_bytes: 294749 num_examples: 576 download_size: 19558988 dataset_size: 299505 - config_name: cuad_irrevocable_or_perpetual_license features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 5328 num_examples: 6 - name: test num_bytes: 160279 num_examples: 280 download_size: 19558988 dataset_size: 165607 - config_name: cuad_joint_ip_ownership features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 5011 num_examples: 6 - name: test num_bytes: 90592 num_examples: 192 download_size: 19558988 dataset_size: 95603 - config_name: cuad_license_grant features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3690 num_examples: 6 - name: test num_bytes: 709331 num_examples: 1396 download_size: 19558988 dataset_size: 713021 - config_name: cuad_liquidated_damages features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3579 num_examples: 6 - name: test num_bytes: 97839 num_examples: 220 download_size: 19558988 dataset_size: 101418 - config_name: cuad_minimum_commitment features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2874 num_examples: 6 - name: test num_bytes: 354078 num_examples: 772 download_size: 19558988 dataset_size: 356952 - config_name: cuad_most_favored_nation features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2103 num_examples: 6 - name: test num_bytes: 32800 num_examples: 64 download_size: 19558988 dataset_size: 34903 - config_name: cuad_no-solicit_of_customers features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3310 num_examples: 6 - name: test num_bytes: 40828 num_examples: 84 download_size: 19558988 dataset_size: 44138 - config_name: cuad_no-solicit_of_employees features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3619 num_examples: 6 - name: test num_bytes: 72661 num_examples: 142 download_size: 19558988 dataset_size: 76280 - config_name: cuad_non-compete features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3675 num_examples: 6 - name: test num_bytes: 211272 num_examples: 442 download_size: 19558988 dataset_size: 214947 - config_name: cuad_non-disparagement features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2168 num_examples: 6 - name: test num_bytes: 49850 num_examples: 100 download_size: 19558988 dataset_size: 52018 - config_name: cuad_non-transferable_license features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3643 num_examples: 6 - name: test num_bytes: 269505 num_examples: 542 download_size: 19558988 dataset_size: 273148 - config_name: cuad_notice_period_to_terminate_renewal features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 4166 num_examples: 6 - name: test num_bytes: 100014 num_examples: 222 download_size: 19558988 dataset_size: 104180 - config_name: cuad_post-termination_services features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 3349 num_examples: 6 - name: test num_bytes: 419477 num_examples: 808 download_size: 19558988 dataset_size: 422826 - config_name: cuad_price_restrictions features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2945 num_examples: 6 - name: test num_bytes: 19430 num_examples: 46 download_size: 19558988 dataset_size: 22375 - config_name: cuad_renewal_term features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2163 num_examples: 6 - name: test num_bytes: 168528 num_examples: 386 download_size: 19558988 dataset_size: 170691 - config_name: cuad_revenue-profit_sharing features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2581 num_examples: 6 - name: test num_bytes: 363594 num_examples: 774 download_size: 19558988 dataset_size: 366175 - config_name: cuad_rofr-rofo-rofn features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2817 num_examples: 6 - name: test num_bytes: 338243 num_examples: 690 download_size: 19558988 dataset_size: 341060 - config_name: cuad_source_code_escrow features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2696 num_examples: 6 - name: test num_bytes: 58125 num_examples: 118 download_size: 19558988 dataset_size: 60821 - config_name: cuad_termination_for_convenience features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 1506 num_examples: 6 - name: test num_bytes: 181164 num_examples: 430 download_size: 19558988 dataset_size: 182670 - config_name: cuad_third_party_beneficiary features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2378 num_examples: 6 - name: test num_bytes: 24106 num_examples: 68 download_size: 19558988 dataset_size: 26484 - config_name: cuad_uncapped_liability features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2570 num_examples: 6 - name: test num_bytes: 158009 num_examples: 294 download_size: 19558988 dataset_size: 160579 - config_name: cuad_unlimited-all-you-can-eat-license features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 2414 num_examples: 6 - name: test num_bytes: 22347 num_examples: 48 download_size: 19558988 dataset_size: 24761 - config_name: cuad_volume_restriction features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 1397 num_examples: 6 - name: test num_bytes: 129456 num_examples: 322 download_size: 19558988 dataset_size: 130853 - config_name: cuad_warranty_duration features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string - name: document_name dtype: string splits: - name: train num_bytes: 1815 num_examples: 6 - name: test num_bytes: 142580 num_examples: 320 download_size: 19558988 dataset_size: 144395 - config_name: definition_classification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1826 num_examples: 8 - name: test num_bytes: 371743 num_examples: 1337 download_size: 19558988 dataset_size: 373569 - config_name: definition_extraction features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2731 num_examples: 8 - name: test num_bytes: 254689 num_examples: 687 download_size: 19558988 dataset_size: 257420 - config_name: diversity_1 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 803 num_examples: 6 - name: test num_bytes: 41135 num_examples: 300 download_size: 19558988 dataset_size: 41938 - config_name: diversity_2 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 1041 num_examples: 6 - name: test num_bytes: 53537 num_examples: 300 download_size: 19558988 dataset_size: 54578 - config_name: diversity_3 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 992 num_examples: 6 - name: test num_bytes: 50744 num_examples: 300 download_size: 19558988 dataset_size: 51736 - config_name: diversity_4 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 1070 num_examples: 6 - name: test num_bytes: 53464 num_examples: 300 download_size: 19558988 dataset_size: 54534 - config_name: diversity_5 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 1232 num_examples: 6 - name: test num_bytes: 62550 num_examples: 300 download_size: 19558988 dataset_size: 63782 - config_name: diversity_6 features: - name: aic_is_met dtype: string - name: answer dtype: string - name: index dtype: string - name: parties_are_diverse dtype: string - name: text dtype: string splits: - name: train num_bytes: 2016 num_examples: 6 - name: test num_bytes: 100411 num_examples: 300 download_size: 19558988 dataset_size: 102427 - config_name: function_of_decision_section features: - name: Citation dtype: string - name: Paragraph dtype: string - name: answer dtype: string - name: index dtype: string splits: - name: train num_bytes: 1547 num_examples: 7 - name: test num_bytes: 210419 num_examples: 367 download_size: 19558988 dataset_size: 211966 - config_name: hearsay features: - name: answer dtype: string - name: index dtype: string - name: slice dtype: string - name: text dtype: string splits: - name: train num_bytes: 788 num_examples: 5 - name: test num_bytes: 17150 num_examples: 94 download_size: 19558988 dataset_size: 17938 - config_name: insurance_policy_interpretation features: - name: answer dtype: string - name: claim dtype: string - name: index dtype: string - name: policy dtype: string splits: - name: train num_bytes: 3119 num_examples: 5 - name: test num_bytes: 70764 num_examples: 133 download_size: 19558988 dataset_size: 73883 - config_name: international_citizenship_questions features: - name: answer dtype: string - name: index dtype: string - name: question dtype: string splits: - name: train num_bytes: 832 num_examples: 4 - name: test num_bytes: 2089107 num_examples: 9306 download_size: 19558988 dataset_size: 2089939 - config_name: jcrew_blocker features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 7352 num_examples: 6 - name: test num_bytes: 59879 num_examples: 54 download_size: 19558988 dataset_size: 67231 - config_name: learned_hands_benefits features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 8267 num_examples: 6 - name: test num_bytes: 87512 num_examples: 66 download_size: 19558988 dataset_size: 95779 - config_name: learned_hands_business features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6075 num_examples: 6 - name: test num_bytes: 202116 num_examples: 174 download_size: 19558988 dataset_size: 208191 - config_name: learned_hands_consumer features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6355 num_examples: 6 - name: test num_bytes: 795463 num_examples: 614 download_size: 19558988 dataset_size: 801818 - config_name: learned_hands_courts features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 10693 num_examples: 6 - name: test num_bytes: 228204 num_examples: 192 download_size: 19558988 dataset_size: 238897 - config_name: learned_hands_crime features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 7322 num_examples: 6 - name: test num_bytes: 846597 num_examples: 688 download_size: 19558988 dataset_size: 853919 - config_name: learned_hands_divorce features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 10651 num_examples: 6 - name: test num_bytes: 189279 num_examples: 150 download_size: 19558988 dataset_size: 199930 - config_name: learned_hands_domestic_violence features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 11170 num_examples: 6 - name: test num_bytes: 239797 num_examples: 174 download_size: 19558988 dataset_size: 250967 - config_name: learned_hands_education features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6992 num_examples: 6 - name: test num_bytes: 79184 num_examples: 56 download_size: 19558988 dataset_size: 86176 - config_name: learned_hands_employment features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 11223 num_examples: 6 - name: test num_bytes: 909220 num_examples: 710 download_size: 19558988 dataset_size: 920443 - config_name: learned_hands_estates features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5970 num_examples: 6 - name: test num_bytes: 216836 num_examples: 178 download_size: 19558988 dataset_size: 222806 - config_name: learned_hands_family features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 8714 num_examples: 6 - name: test num_bytes: 3073508 num_examples: 2265 download_size: 19558988 dataset_size: 3082222 - config_name: learned_hands_health features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6155 num_examples: 6 - name: test num_bytes: 336934 num_examples: 226 download_size: 19558988 dataset_size: 343089 - config_name: learned_hands_housing features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 9726 num_examples: 6 - name: test num_bytes: 6028612 num_examples: 4494 download_size: 19558988 dataset_size: 6038338 - config_name: learned_hands_immigration features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3955 num_examples: 6 - name: test num_bytes: 165352 num_examples: 134 download_size: 19558988 dataset_size: 169307 - config_name: learned_hands_torts features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 4484 num_examples: 6 - name: test num_bytes: 615649 num_examples: 432 download_size: 19558988 dataset_size: 620133 - config_name: learned_hands_traffic features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6250 num_examples: 6 - name: test num_bytes: 667539 num_examples: 556 download_size: 19558988 dataset_size: 673789 - config_name: legal_reasoning_causality features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 4688 num_examples: 4 - name: test num_bytes: 87007 num_examples: 55 download_size: 19558988 dataset_size: 91695 - config_name: maud_ability_to_consummate_concept_is_subject_to_mae_carveouts features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5322 num_examples: 1 - name: test num_bytes: 304051 num_examples: 69 download_size: 19558988 dataset_size: 309373 - config_name: maud_accuracy_of_fundamental_target_rws_bringdown_standard features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 271 num_examples: 1 - name: test num_bytes: 148869 num_examples: 175 download_size: 19558988 dataset_size: 149140 - config_name: maud_accuracy_of_target_capitalization_rw_(outstanding_shares)_bringdown_standard_answer features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1493 num_examples: 1 - name: test num_bytes: 152224 num_examples: 181 download_size: 19558988 dataset_size: 153717 - config_name: maud_accuracy_of_target_general_rw_bringdown_timing_answer features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1000 num_examples: 1 - name: test num_bytes: 152717 num_examples: 181 download_size: 19558988 dataset_size: 153717 - config_name: maud_additional_matching_rights_period_for_modifications_(cor) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2170 num_examples: 1 - name: test num_bytes: 312632 num_examples: 158 download_size: 19558988 dataset_size: 314802 - config_name: maud_application_of_buyer_consent_requirement_(negative_interim_covenant) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 558 num_examples: 1 - name: test num_bytes: 96990 num_examples: 180 download_size: 19558988 dataset_size: 97548 - config_name: maud_buyer_consent_requirement_(ordinary_course) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2620 num_examples: 1 - name: test num_bytes: 138668 num_examples: 181 download_size: 19558988 dataset_size: 141288 - config_name: maud_change_in_law__subject_to_disproportionate_impact_modifier features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6000 num_examples: 1 - name: test num_bytes: 448666 num_examples: 99 download_size: 19558988 dataset_size: 454666 - config_name: maud_changes_in_gaap_or_other_accounting_principles__subject_to_disproportionate_impact_modifier features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5998 num_examples: 1 - name: test num_bytes: 444442 num_examples: 98 download_size: 19558988 dataset_size: 450440 - config_name: maud_cor_permitted_in_response_to_intervening_event features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2631 num_examples: 1 - name: test num_bytes: 195447 num_examples: 100 download_size: 19558988 dataset_size: 198078 - config_name: maud_cor_permitted_with_board_fiduciary_determination_only features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3970 num_examples: 1 - name: test num_bytes: 194108 num_examples: 100 download_size: 19558988 dataset_size: 198078 - config_name: maud_cor_standard_(intervening_event) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 727 num_examples: 1 - name: test num_bytes: 175140 num_examples: 84 download_size: 19558988 dataset_size: 175867 - config_name: maud_cor_standard_(superior_offer) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1173 num_examples: 1 - name: test num_bytes: 196905 num_examples: 100 download_size: 19558988 dataset_size: 198078 - config_name: maud_definition_contains_knowledge_requirement_-_answer features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1899 num_examples: 1 - name: test num_bytes: 231405 num_examples: 147 download_size: 19558988 dataset_size: 233304 - config_name: maud_definition_includes_asset_deals features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 614 num_examples: 1 - name: test num_bytes: 289644 num_examples: 146 download_size: 19558988 dataset_size: 290258 - config_name: maud_definition_includes_stock_deals features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 683 num_examples: 1 - name: test num_bytes: 292466 num_examples: 148 download_size: 19558988 dataset_size: 293149 - config_name: maud_fiduciary_exception__board_determination_standard features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1594 num_examples: 1 - name: test num_bytes: 288180 num_examples: 179 download_size: 19558988 dataset_size: 289774 - config_name: maud_fiduciary_exception_board_determination_trigger_(no_shop) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3538 num_examples: 1 - name: test num_bytes: 286236 num_examples: 179 download_size: 19558988 dataset_size: 289774 - config_name: maud_financial_point_of_view_is_the_sole_consideration features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3290 num_examples: 1 - name: test num_bytes: 217048 num_examples: 112 download_size: 19558988 dataset_size: 220338 - config_name: maud_fls_(mae)_standard features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 4669 num_examples: 1 - name: test num_bytes: 349856 num_examples: 77 download_size: 19558988 dataset_size: 354525 - config_name: maud_general_economic_and_financial_conditions_subject_to_disproportionate_impact_modifier features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5998 num_examples: 1 - name: test num_bytes: 445306 num_examples: 98 download_size: 19558988 dataset_size: 451304 - config_name: maud_includes_consistent_with_past_practice features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1127 num_examples: 1 - name: test num_bytes: 140161 num_examples: 181 download_size: 19558988 dataset_size: 141288 - config_name: maud_initial_matching_rights_period_(cor) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3041 num_examples: 1 - name: test num_bytes: 311761 num_examples: 158 download_size: 19558988 dataset_size: 314802 - config_name: maud_initial_matching_rights_period_(ftr) features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1850 num_examples: 1 - name: test num_bytes: 279202 num_examples: 132 download_size: 19558988 dataset_size: 281052 - config_name: maud_intervening_event_-_required_to_occur_after_signing_-_answer features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3055 num_examples: 1 - name: test num_bytes: 230249 num_examples: 147 download_size: 19558988 dataset_size: 233304 - config_name: maud_knowledge_definition features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 240 num_examples: 1 - name: test num_bytes: 359730 num_examples: 167 download_size: 19558988 dataset_size: 359970 - config_name: maud_liability_standard_for_no-shop_breach_by_target_non-do_representatives features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 154 num_examples: 1 - name: test num_bytes: 40946 num_examples: 156 download_size: 19558988 dataset_size: 41100 - config_name: maud_ordinary_course_efforts_standard features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1037 num_examples: 1 - name: test num_bytes: 140251 num_examples: 181 download_size: 19558988 dataset_size: 141288 - config_name: maud_pandemic_or_other_public_health_event__subject_to_disproportionate_impact_modifier features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3728 num_examples: 1 - name: test num_bytes: 447053 num_examples: 98 download_size: 19558988 dataset_size: 450781 - config_name: maud_pandemic_or_other_public_health_event_specific_reference_to_pandemic-related_governmental_responses_or_measures features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3728 num_examples: 1 - name: test num_bytes: 447053 num_examples: 98 download_size: 19558988 dataset_size: 450781 - config_name: maud_relational_language_(mae)_applies_to features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 4948 num_examples: 1 - name: test num_bytes: 409477 num_examples: 90 download_size: 19558988 dataset_size: 414425 - config_name: maud_specific_performance features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 771 num_examples: 1 - name: test num_bytes: 107392 num_examples: 178 download_size: 19558988 dataset_size: 108163 - config_name: maud_tail_period_length features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 406 num_examples: 1 - name: test num_bytes: 108632 num_examples: 179 download_size: 19558988 dataset_size: 109038 - config_name: maud_type_of_consideration features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 258 num_examples: 1 - name: test num_bytes: 139270 num_examples: 172 download_size: 19558988 dataset_size: 139528 - config_name: nys_judicial_ethics features: - name: answer dtype: string - name: index dtype: string - name: question dtype: string - name: year dtype: string splits: - name: train num_bytes: 1697 num_examples: 8 - name: test num_bytes: 53974 num_examples: 292 download_size: 19558988 dataset_size: 55671 - config_name: opp115_data_retention features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1791 num_examples: 8 - name: test num_bytes: 18620 num_examples: 88 download_size: 19558988 dataset_size: 20411 - config_name: opp115_data_security features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2123 num_examples: 8 - name: test num_bytes: 352667 num_examples: 1334 download_size: 19558988 dataset_size: 354790 - config_name: opp115_do_not_track features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2507 num_examples: 8 - name: test num_bytes: 26363 num_examples: 110 download_size: 19558988 dataset_size: 28870 - config_name: opp115_first_party_collection_use features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 2227 num_examples: 8 - name: test num_bytes: 463566 num_examples: 2086 download_size: 19558988 dataset_size: 465793 - config_name: opp115_international_and_specific_audiences features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1643 num_examples: 8 - name: test num_bytes: 338196 num_examples: 980 download_size: 19558988 dataset_size: 339839 - config_name: opp115_policy_change features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1201 num_examples: 8 - name: test num_bytes: 94060 num_examples: 431 download_size: 19558988 dataset_size: 95261 - config_name: opp115_third_party_sharing_collection features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1217 num_examples: 8 - name: test num_bytes: 383909 num_examples: 1590 download_size: 19558988 dataset_size: 385126 - config_name: opp115_user_access,_edit_and_deletion features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1251 num_examples: 8 - name: test num_bytes: 108969 num_examples: 462 download_size: 19558988 dataset_size: 110220 - config_name: opp115_user_choice_control features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1695 num_examples: 8 - name: test num_bytes: 353113 num_examples: 1546 download_size: 19558988 dataset_size: 354808 - config_name: oral_argument_question_purpose features: - name: Docket No. dtype: string - name: answer dtype: string - name: index dtype: string - name: question dtype: string splits: - name: train num_bytes: 2415 num_examples: 7 - name: test num_bytes: 95262 num_examples: 312 download_size: 19558988 dataset_size: 97677 - config_name: overruling features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 629 num_examples: 6 - name: test num_bytes: 443484 num_examples: 2394 download_size: 19558988 dataset_size: 444113 - config_name: personal_jurisdiction features: - name: answer dtype: string - name: index dtype: string - name: slice dtype: string - name: text dtype: string splits: - name: train num_bytes: 1660 num_examples: 4 - name: test num_bytes: 21089 num_examples: 50 download_size: 19558988 dataset_size: 22749 - config_name: privacy_policy_entailment features: - name: answer dtype: string - name: description dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 6282 num_examples: 8 - name: test num_bytes: 3174950 num_examples: 4335 download_size: 19558988 dataset_size: 3181232 - config_name: privacy_policy_qa features: - name: answer dtype: string - name: index dtype: string - name: question dtype: string - name: text dtype: string splits: - name: train num_bytes: 2231 num_examples: 8 - name: test num_bytes: 2817986 num_examples: 10923 download_size: 19558988 dataset_size: 2820217 - config_name: proa features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1057 num_examples: 5 - name: test num_bytes: 25475 num_examples: 95 download_size: 19558988 dataset_size: 26532 - config_name: rule_qa features: - name: answer dtype: string - name: doctrine dtype: string - name: index dtype: string - name: text dtype: string splits: - name: test num_bytes: 12665 num_examples: 50 download_size: 19558988 dataset_size: 12665 - config_name: sara_entailment features: - name: answer dtype: string - name: case id dtype: string - name: description dtype: string - name: index dtype: string - name: question dtype: string - name: statute dtype: string - name: text dtype: string splits: - name: train num_bytes: 2528 num_examples: 4 - name: test num_bytes: 225560 num_examples: 272 download_size: 19558988 dataset_size: 228088 - config_name: sara_numeric features: - name: answer dtype: string - name: case id dtype: string - name: description dtype: string - name: index dtype: string - name: question dtype: string - name: statute dtype: string - name: text dtype: string splits: - name: train num_bytes: 238363 num_examples: 4 - name: test num_bytes: 5725392 num_examples: 96 download_size: 19558988 dataset_size: 5963755 - config_name: scalr features: - name: answer dtype: string - name: choice_0 dtype: string - name: choice_1 dtype: string - name: choice_2 dtype: string - name: choice_3 dtype: string - name: choice_4 dtype: string - name: index dtype: string - name: question dtype: string splits: - name: test num_bytes: 1026740 num_examples: 571 download_size: 19558988 dataset_size: 1026740 - config_name: ssla_company_defendants features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5847 num_examples: 3 - name: test num_bytes: 2313039 num_examples: 1228 download_size: 19558988 dataset_size: 2318886 - config_name: ssla_individual_defendants features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5962 num_examples: 3 - name: test num_bytes: 2002620 num_examples: 1012 download_size: 19558988 dataset_size: 2008582 - config_name: ssla_plaintiff features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 5831 num_examples: 3 - name: test num_bytes: 1926518 num_examples: 1033 download_size: 19558988 dataset_size: 1932349 - config_name: successor_liability features: - name: answer dtype: string - name: index dtype: string - name: issue dtype: string - name: text dtype: string splits: - name: train num_bytes: 1734 num_examples: 3 - name: test num_bytes: 26490 num_examples: 47 download_size: 19558988 dataset_size: 28224 - config_name: supply_chain_disclosure_best_practice_accountability features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 18987 num_examples: 8 - name: test num_bytes: 1347025 num_examples: 379 download_size: 19558988 dataset_size: 1366012 - config_name: supply_chain_disclosure_best_practice_audits features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 23879 num_examples: 8 - name: test num_bytes: 1342065 num_examples: 379 download_size: 19558988 dataset_size: 1365944 - config_name: supply_chain_disclosure_best_practice_certification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 22058 num_examples: 8 - name: test num_bytes: 1338516 num_examples: 378 download_size: 19558988 dataset_size: 1360574 - config_name: supply_chain_disclosure_best_practice_training features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 24071 num_examples: 8 - name: test num_bytes: 1341885 num_examples: 379 download_size: 19558988 dataset_size: 1365956 - config_name: supply_chain_disclosure_best_practice_verification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 27158 num_examples: 8 - name: test num_bytes: 1338739 num_examples: 379 download_size: 19558988 dataset_size: 1365897 - config_name: supply_chain_disclosure_disclosed_accountability features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 18902 num_examples: 8 - name: test num_bytes: 1344444 num_examples: 378 download_size: 19558988 dataset_size: 1363346 - config_name: supply_chain_disclosure_disclosed_audits features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 24404 num_examples: 8 - name: test num_bytes: 1341624 num_examples: 379 download_size: 19558988 dataset_size: 1366028 - config_name: supply_chain_disclosure_disclosed_certification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 17987 num_examples: 8 - name: test num_bytes: 1342646 num_examples: 378 download_size: 19558988 dataset_size: 1360633 - config_name: supply_chain_disclosure_disclosed_training features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 27093 num_examples: 8 - name: test num_bytes: 1338919 num_examples: 379 download_size: 19558988 dataset_size: 1366012 - config_name: supply_chain_disclosure_disclosed_verification features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 25387 num_examples: 8 - name: test num_bytes: 1340578 num_examples: 379 download_size: 19558988 dataset_size: 1365965 - config_name: telemarketing_sales_rule features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 1230 num_examples: 4 - name: test num_bytes: 17140 num_examples: 47 download_size: 19558988 dataset_size: 18370 - config_name: textualism_tool_dictionaries features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 4842 num_examples: 4 - name: test num_bytes: 102644 num_examples: 107 download_size: 19558988 dataset_size: 107486 - config_name: textualism_tool_plain features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3338 num_examples: 4 - name: test num_bytes: 167428 num_examples: 165 download_size: 19558988 dataset_size: 170766 - config_name: ucc_v_common_law features: - name: answer dtype: string - name: contract dtype: string - name: index dtype: string splits: - name: train num_bytes: 904 num_examples: 6 - name: test num_bytes: 12694 num_examples: 94 download_size: 19558988 dataset_size: 13598 - config_name: unfair_tos features: - name: answer dtype: string - name: index dtype: string - name: text dtype: string splits: - name: train num_bytes: 3308 num_examples: 9 - name: test num_bytes: 787108 num_examples: 3813 download_size: 19558988 dataset_size: 790416 --- # Dataset Card for Dataset Name - **Homepage: https://hazyresearch.stanford.edu/legalbench/** - **Repository: https://github.com/HazyResearch/legalbench/** - **Paper: https://arxiv.org/abs/2308.11462** ## Dataset Description ### Dataset Summary The LegalBench project is an ongoing open science effort to collaboratively curate tasks for evaluating legal reasoning in English large language models (LLMs). The benchmark currently consists of 162 tasks gathered from 40 contributors. Note: Because LegalBench is intended to test zero and few-shot reasoning, the available "train" splits are small. However, if you are interested in finetuning models or studying model performance in a more traditional train/test regime, you can combine and re-partition train and test data. If you have questions about the project or would like to get involved, please see the website for more information. ### Supported Tasks and Leaderboards LegalBench tasks span multiple types (binary classification, multi-class classification, extraction, generation, entailment), multiple types of text (statutes, judicial opinions, contracts, etc.), and multiple areas of law (evidence, contracts, civil procedure, etc.). For more information on tasks, we recommend visiting the website, where you can search through task descriptions, or the Github repository, which contains more granular task descriptions. We also recommend reading the paper, which provides more background on task significance and construction process. ### Languages All LegalBench tasks are in English. ## Dataset Structure ### Data Instances Detailed descriptions of the instances for each task can be found on the Github. An example of an instance, for the `abercrombie` task, is provided below: ``` { "text": "The mark "Ivory" for a product made of elephant tusks.", "label": "generic" "idx": 0 } ``` A substantial number of LegalBench tasks are binary classification tasks, which require the LLM to determine if a piece of text has some legal attribute. Because these are framed as Yes/No questions, the label space is "Yes" or "No". ### Data Fields Detailed descriptions of the instances for each task can be found on the Github. ### Data Splits Each task (except for `rule_qa` and `scalr`) has both a training and evaluation split. Following [RAFT](https://huggingface.co/datasets/ought/raft), train splits only consists of a few-labeled instances, reflecting the few-shot nature of most LLMs. ## Dataset Creation ### Curation Rationale LegalBench was created to enable researchers to better benchmark the legal reasoning capabilities of LLMs. ### Source Data #### Initial Data Collection and Normalization Broadly, LegalBench tasks are drawn from three sources. The first source of tasks are existing available datasets and corpora. Most of these were originally released for non-LLM evaluation settings. In creating tasks for LegalBench from these sources, we often significantly reformatted data and restructured the prediction objective. For instance, the original [CUAD dataset](https://github.com/TheAtticusProject/cuad) contains annotations on long-documents and is intended for evaluating extraction with span-prediction models. We restructure this corpora to generate a binary classification task for each type of contractual clause. While the original corpus emphasized the long-document aspects of contracts, our restructured tasks emphasize whether LLMs can identify the distinguishing features of different types of clauses. The second source of tasks are datasets that were previously constructed by legal professionals but never released. This primarily includes datasets hand-coded by legal scholars as part of prior empirical legal projects. The last category of tasks are those that were developed specifically for \name, by the authors of this paper. Overall, tasks are drawn from 36 distinct corpora. Please see the Appendix of the paper for more details. #### Who are the source language producers? LegalBench data was created by humans. Demographic information for these individuals is not available. ### Annotations #### Annotation process Please see the paper for more information on the annotation process used in the creation of each task. #### Who are the annotators? Please see the paper for more information on the identity of annotators for each task. ### Personal and Sensitive Information Data in this benchmark has either been synthetically generated, or derived from an already public source (e.g., contracts from the EDGAR database). Several tasks have been derived from the LearnedHands corpus, which consists of public posts on /r/LegalAdvice. Some posts may discuss sensitive issues. ## Considerations for Using the Data ### Social Impact of Dataset Please see the original paper for a discussion of social impact. ### Discussion of Biases Please see the original paper for a discussion of social impact. ### Other Known Limitations LegalBench primarily contains tasks corresponding to American law. ## Additional Information ### Dataset Curators Please see the website for a full list of participants in the LegalBench project. ### Licensing Information LegalBench tasks are subject to different licenses. Please see the paper for a description of the licenses. ### Citation Information If you intend to reference LegalBench broadly, please use the citation below. If you are working with a particular task, please use the citation below in addition to the task specific citation (which can be found on the task page on the website or Github). ``` @misc{guha2023legalbench, title={LegalBench: A Collaboratively Built Benchmark for Measuring Legal Reasoning in Large Language Models}, author={Neel Guha and Julian Nyarko and Daniel E. Ho and Christopher Ré and Adam Chilton and Aditya Narayana and Alex Chohlas-Wood and Austin Peters and Brandon Waldon and Daniel N. Rockmore and Diego Zambrano and Dmitry Talisman and Enam Hoque and Faiz Surani and Frank Fagan and Galit Sarfaty and Gregory M. Dickinson and Haggai Porat and Jason Hegland and Jessica Wu and Joe Nudell and Joel Niklaus and John Nay and Jonathan H. Choi and Kevin Tobia and Margaret Hagan and Megan Ma and Michael Livermore and Nikon Rasumov-Rahe and Nils Holzenberger and Noam Kolt and Peter Henderson and Sean Rehaag and Sharad Goel and Shang Gao and Spencer Williams and Sunny Gandhi and Tom Zur and Varun Iyer and Zehua Li}, year={2023}, eprint={2308.11462}, archivePrefix={arXiv}, primaryClass={cs.CL} } @article{koreeda2021contractnli, title={ContractNLI: A dataset for document-level natural language inference for contracts}, author={Koreeda, Yuta and Manning, Christopher D}, journal={arXiv preprint arXiv:2110.01799}, year={2021} } @article{hendrycks2021cuad, title={Cuad: An expert-annotated nlp dataset for legal contract review}, author={Hendrycks, Dan and Burns, Collin and Chen, Anya and Ball, Spencer}, journal={arXiv preprint arXiv:2103.06268}, year={2021} } @article{wang2023maud, title={MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding}, author={Wang, Steven H and Scardigli, Antoine and Tang, Leonard and Chen, Wei and Levkin, Dimitry and Chen, Anya and Ball, Spencer and Woodside, Thomas and Zhang, Oliver and Hendrycks, Dan}, journal={arXiv preprint arXiv:2301.00876}, year={2023} } @inproceedings{wilson2016creation, title={The creation and analysis of a website privacy policy corpus}, author={Wilson, Shomir and Schaub, Florian and Dara, Aswarth Abhilash and Liu, Frederick and Cherivirala, Sushain and Leon, Pedro Giovanni and Andersen, Mads Schaarup and Zimmeck, Sebastian and Sathyendra, Kanthashree Mysore and Russell, N Cameron and others}, booktitle={Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)}, pages={1330--1340}, year={2016} } @inproceedings{zheng2021does, title={When does pretraining help? assessing self-supervised learning for law and the casehold dataset of 53,000+ legal holdings}, author={Zheng, Lucia and Guha, Neel and Anderson, Brandon R and Henderson, Peter and Ho, Daniel E}, booktitle={Proceedings of the eighteenth international conference on artificial intelligence and law}, pages={159--168}, year={2021} } @article{zimmeck2019maps, title={Maps: Scaling privacy compliance analysis to a million apps}, author={Zimmeck, Sebastian and Story, Peter and Smullen, Daniel and Ravichander, Abhilasha and Wang, Ziqi and Reidenberg, Joel R and Russell, N Cameron and Sadeh, Norman}, journal={Proc. Priv. Enhancing Tech.}, volume={2019}, pages={66}, year={2019} } @article{ravichander2019question, title={Question answering for privacy policies: Combining computational and legal perspectives}, author={Ravichander, Abhilasha and Black, Alan W and Wilson, Shomir and Norton, Thomas and Sadeh, Norman}, journal={arXiv preprint arXiv:1911.00841}, year={2019} } @article{holzenberger2021factoring, title={Factoring statutory reasoning as language understanding challenges}, author={Holzenberger, Nils and Van Durme, Benjamin}, journal={arXiv preprint arXiv:2105.07903}, year={2021} } @article{lippi2019claudette, title={CLAUDETTE: an automated detector of potentially unfair clauses in online terms of service}, author={Lippi, Marco and Pa{\l}ka, Przemys{\l}aw and Contissa, Giuseppe and Lagioia, Francesca and Micklitz, Hans-Wolfgang and Sartor, Giovanni and Torroni, Paolo}, journal={Artificial Intelligence and Law}, volume={27}, pages={117--139}, year={2019}, publisher={Springer} } ```

Open-Orca/FLAN

Open-Orca

--- license: cc-by-4.0 language: - en library_name: transformers pipeline_tag: text-generation datasets: - Open-Orca/OpenOrca size_categories: - 1B<n<10B --- <p><h1>🍮 The WHOLE FLAN Collection! 🍮</h1></p>  # Overview This repository includes the full dataset from the [FLAN Collection](https://ai.googleblog.com/2023/02/the-flan-collection-advancing-open.html), totalling ~300GB as parquets. Generated using the official seqio templating from the [Google FLAN Collection GitHub repo](https://github.com/google-research/FLAN/tree/main/flan/v2). The data is subject to all the same licensing of the component datasets. To keep up with our continued work on OpenOrca and other exciting research, find our Discord here: https://AlignmentLab.ai # Motivation This work was done as part of the requirements for the OpenOrca project. There was not a large enough subset of FLAN Collection generated publicly to subsample from to complete the work. So, we opted to process the entire collection ourselves. Generating this requires an understanding of seqio and a Linux server with 512GB of CPU ram, as well as fast drives and custom limits for many parameters beyond what is default on Linux server distributions (e.g., requiring up to 45,000 threads running at once). It takes downloading over 400GB of datasets, working around tfds bugs, and then processing the datasets over the course of several days. We provide this repo as a resource to other ML researchers, as it saves these time consuming and laborious steps to getting the data into a more accessible format for further consumption. # Data ## Organization * JSON files at top level are used for subsampling in OpenOrca * Parquets in subdirectories contain the entire FLAN collection in Dask-sharded folders by submix fractions ## Zero-Shot vs Few-Shot and Options vs No-Options The core sub-collections of FLAN are `CoT`, `Dialog`, `NIv2`, `T0`, and `flan2021`. Within those sub-collections are four "remixes" of the data that are templated differently: * `Zero-Shot` and `Few-Shot` * `Zero-Shot` provides a prompt, question, or challenge without any exemplaries prior * `Few-Shot` provides exemplaries first * `Options` and `No-Options` * `Options` provides a question or challenge with multiple-choice (e.g. A/B/C/D) answer options provided to select from * `No-Options` requires a free-form answer For every sub-collection, only some of the "remixes" may officially be provided. All available have been generated in full without any redaction or sub-sampling. An example: `t0_fsopt_data` folder contains the sub-collection `T0`'s Few-Shot (FS), Options (OPT) remix set. Notably, this is the largest "remix" and the one that necessitates 512GB CPU ram to generate. The raw json output is nearly 200GB. ## Parquet Sizes Each sub-collection's individual remixes are provided as [Parquet](https://huggingface.co/docs/datasets/loading#parquet) files which have been sharded by [Dask](https://huggingface.co/docs/datasets/main/en/filesystems#dask) into ~160MB chunks (starting from 256MB blocks of the source jsonl files). The folder structure along with size sums is provided below. ``` $ du -h --max-depth=1 ./ 9.1G ./niv2_fsopt_data 2.4G ./niv2_zsopt_data 59G ./flan_fsopt_data 984M ./dialog_zsopt_data 11G ./flan_zsopt_data 8.6G ./dialog_fsopt_data 16G ./t0_zsnoopt_data 149M ./cot_fsopt_data 20M ./cot_zsopt_data 17G ./t0_zsopt_data 11G ./flan_zsnoopt_data 101G ./t0_fsopt_data 25G ./flan_fsnoopt_data 39G ./t0_fsnoopt_data 296G ./ ``` # Citations ```bibtex @misc{goodson2023huggyflan title={Fine FLAN: Seqio to Parquet So You Don't Have To}, author={Bleys Goodson}, year={2023}, publisher = {HuggingFace}, journal = {HuggingFace repository}, howpublished = {\url{https://https://huggingface.co/datasets/Open-Orca/FLAN}, } ``` ```bibtex @misc{longpre2023flan, title={The Flan Collection: Designing Data and Methods for Effective Instruction Tuning}, author={Shayne Longpre and Le Hou and Tu Vu and Albert Webson and Hyung Won Chung and Yi Tay and Denny Zhou and Quoc V. Le and Barret Zoph and Jason Wei and Adam Roberts}, year={2023}, eprint={2301.13688}, archivePrefix={arXiv}, primaryClass={cs.AI} } ``` ```bibtex @misc{wei2022finetuned, title={Finetuned Language Models Are Zero-Shot Learners}, author={Jason Wei and Maarten Bosma and Vincent Y. Zhao and Kelvin Guu and Adams Wei Yu and Brian Lester and Nan Du and Andrew M. Dai and Quoc V. Le}, year={2022}, eprint={2109.01652}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ```bibtex @misc{sanh2022multitask, title={Multitask Prompted Training Enables Zero-Shot Task Generalization}, author={Victor Sanh and Albert Webson and Colin Raffel and Stephen H. Bach and Lintang Sutawika and Zaid Alyafeai and Antoine Chaffin and Arnaud Stiegler and Teven Le Scao and Arun Raja and Manan Dey and M Saiful Bari and Canwen Xu and Urmish Thakker and Shanya Sharma Sharma and Eliza Szczechla and Taewoon Kim and Gunjan Chhablani and Nihal Nayak and Debajyoti Datta and Jonathan Chang and Mike Tian-Jian Jiang and Han Wang and Matteo Manica and Sheng Shen and Zheng Xin Yong and Harshit Pandey and Rachel Bawden and Thomas Wang and Trishala Neeraj and Jos Rozen and Abheesht Sharma and Andrea Santilli and Thibault Fevry and Jason Alan Fries and Ryan Teehan and Tali Bers and Stella Biderman and Leo Gao and Thomas Wolf and Alexander M. Rush}, year={2022}, eprint={2110.08207}, archivePrefix={arXiv}, primaryClass={cs.LG} } ``` ```bibtex @misc{wang2022supernaturalinstructions, title={Super-NaturalInstructions: Generalization via Declarative Instructions on 1600+ NLP Tasks}, author={Yizhong Wang and Swaroop Mishra and Pegah Alipoormolabashi and Yeganeh Kordi and Amirreza Mirzaei and Anjana Arunkumar and Arjun Ashok and Arut Selvan Dhanasekaran and Atharva Naik and David Stap and Eshaan Pathak and Giannis Karamanolakis and Haizhi Gary Lai and Ishan Purohit and Ishani Mondal and Jacob Anderson and Kirby Kuznia and Krima Doshi and Maitreya Patel and Kuntal Kumar Pal and Mehrad Moradshahi and Mihir Parmar and Mirali Purohit and Neeraj Varshney and Phani Rohitha Kaza and Pulkit Verma and Ravsehaj Singh Puri and Rushang Karia and Shailaja Keyur Sampat and Savan Doshi and Siddhartha Mishra and Sujan Reddy and Sumanta Patro and Tanay Dixit and Xudong Shen and Chitta Baral and Yejin Choi and Noah A. Smith and Hannaneh Hajishirzi and Daniel Khashabi}, year={2022}, eprint={2204.07705}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```

OpenGVLab/OmniCorpus-CC

OpenGVLab

--- language: - en license: cc-by-4.0 size_categories: - 100M<n<1B task_categories: - image-to-text - visual-question-answering dataset_info: - config_name: CC-MAIN-2013-20 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 19908676196 num_examples: 3878063 download_size: 9303464923 dataset_size: 19908676196 - config_name: CC-MAIN-2013-48 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 15282078925 num_examples: 3091537 download_size: 6965036866 dataset_size: 15282078925 - config_name: CC-MAIN-2014-10 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 7227087609 num_examples: 1390034 download_size: 3259239561 dataset_size: 7227087609 - config_name: CC-MAIN-2014-15 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 10106913108 num_examples: 1968361 download_size: 4567738362 dataset_size: 10106913108 - config_name: CC-MAIN-2014-23 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 7997621043 num_examples: 1455331 download_size: 3468852905 dataset_size: 7997621043 - config_name: CC-MAIN-2014-35 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 6228103779 num_examples: 1219200 download_size: 2849584613 dataset_size: 6228103779 - config_name: CC-MAIN-2014-41 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 8321822952 num_examples: 1573955 download_size: 3775989970 dataset_size: 8321822952 - config_name: CC-MAIN-2014-42 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 7732679416 num_examples: 1511931 download_size: 3505766162 dataset_size: 7732679416 - config_name: CC-MAIN-2014-49 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 4473311810 num_examples: 837735 download_size: 1982728919 dataset_size: 4473311810 - config_name: CC-MAIN-2014-52 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 7292722888 num_examples: 1304730 download_size: 2957626766 dataset_size: 7292722888 - config_name: CC-MAIN-2015-06 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 5775826679 num_examples: 1061940 download_size: 2462379667 dataset_size: 5775826679 - config_name: CC-MAIN-2015-11 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 6263650452 num_examples: 1129411 download_size: 2528026633 dataset_size: 6263650452 - config_name: CC-MAIN-2015-14 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 4524425019 num_examples: 885221 download_size: 1939222111 dataset_size: 4524425019 - config_name: CC-MAIN-2015-18 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 6195227565 num_examples: 1104115 download_size: 2634204322 dataset_size: 6195227565 - config_name: CC-MAIN-2015-22 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 7008276790 num_examples: 1290530 download_size: 2913627974 dataset_size: 7008276790 - config_name: CC-MAIN-2015-27 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 4320140953 num_examples: 784496 download_size: 1828575226 dataset_size: 4320140953 - config_name: CC-MAIN-2015-32 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 4952806590 num_examples: 875601 download_size: 2065207099 dataset_size: 4952806590 - config_name: CC-MAIN-2015-35 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 6053257306 num_examples: 1086470 download_size: 2632032769 dataset_size: 6053257306 - config_name: CC-MAIN-2015-40 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 5206096790 num_examples: 924036 download_size: 2203603087 dataset_size: 5206096790 - config_name: CC-MAIN-2015-48 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 8343050753 num_examples: 1537468 download_size: 3489600630 dataset_size: 8343050753 - config_name: CC-MAIN-2016-07 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - 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name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 5402565529 num_examples: 915878 download_size: 2248454753 dataset_size: 5402565529 - config_name: CC-MAIN-2016-40 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - 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name: width dtype: int64 splits: - name: train num_bytes: 15819536321 num_examples: 3528637 download_size: 6516546200 dataset_size: 15819536321 - config_name: CC-MAIN-2016-50 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 10822695594 num_examples: 2215939 download_size: 4439728574 dataset_size: 10822695594 - config_name: CC-MAIN-2017-04 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 11949732148 num_examples: 2441316 download_size: 5045763620 dataset_size: 11949732148 - config_name: CC-MAIN-2017-09 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - 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name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 12209904783 num_examples: 2458486 download_size: 5422393873 dataset_size: 12209904783 - config_name: CC-MAIN-2017-17 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 13763109013 num_examples: 2615558 download_size: 6025106556 dataset_size: 13763109013 - config_name: CC-MAIN-2017-22 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 14456991831 num_examples: 2775332 download_size: 6258001465 dataset_size: 14456991831 - config_name: CC-MAIN-2017-26 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 15036103558 num_examples: 2973499 download_size: 6813218532 dataset_size: 15036103558 - config_name: CC-MAIN-2017-30 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 18833639414 num_examples: 3870197 download_size: 8464443468 dataset_size: 18833639414 - 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name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 44481167440 num_examples: 8699878 download_size: 21623780968 dataset_size: 44481167440 - config_name: CC-MAIN-2018-22 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - 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name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 151537007358 num_examples: 32535697 download_size: 77517210537 dataset_size: 151537007358 - config_name: CC-MAIN-2018-34 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 39026071869 num_examples: 6347230 download_size: 19285382621 dataset_size: 39026071869 - config_name: CC-MAIN-2018-39 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 35948493161 num_examples: 6372711 download_size: 17597722170 dataset_size: 35948493161 - 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name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 54426174385 num_examples: 8897510 download_size: 28125345656 dataset_size: 54426174385 - config_name: CC-MAIN-2019-13 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 48712051219 num_examples: 7803004 download_size: 25156014252 dataset_size: 48712051219 - config_name: CC-MAIN-2019-18 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 48203751852 num_examples: 7532171 download_size: 24844412087 dataset_size: 48203751852 - 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name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 49570657315 num_examples: 8098108 download_size: 24938729240 dataset_size: 49570657315 - config_name: CC-MAIN-2019-39 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 43538081906 num_examples: 7102645 download_size: 21728983014 dataset_size: 43538081906 - config_name: CC-MAIN-2019-43 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 52817470138 num_examples: 8567061 download_size: 26105523209 dataset_size: 52817470138 - config_name: CC-MAIN-2019-47 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 42252827792 num_examples: 6775943 download_size: 21228532199 dataset_size: 42252827792 - 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name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 227631152876 num_examples: 37223376 download_size: 114188282465 dataset_size: 227631152876 - config_name: CC-MAIN-2023-23 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 321036722459 num_examples: 52119692 download_size: 161491274249 dataset_size: 321036722459 - config_name: CC-MAIN-2023-40 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 648032999611 num_examples: 101292016 download_size: 317965522325 dataset_size: 648032999611 - config_name: CC-MAIN-2023-50 features: - name: general_metadata struct: - name: domain sequence: string - name: fluency_prob dtype: float64 - name: id dtype: string - name: non_advertisement_prob dtype: float64 - name: politics_prob dtype: float64 - name: porn_prob dtype: float64 - name: toxic_prob dtype: float64 - name: url dtype: string - name: images sequence: string - name: texts sequence: string - name: metadata list: - name: aesthetic_prob dtype: float64 - name: bytes dtype: int64 - name: d_hash dtype: string - name: d_hash_dup_count dtype: int64 - name: height dtype: int64 - name: img_url_sha dtype: string - name: p_hash dtype: string - name: p_hash_dup_count dtype: int64 - name: unsafe_prob dtype: float64 - name: width dtype: int64 splits: - name: train num_bytes: 744768384551 num_examples: 117073004 download_size: 365332295606 dataset_size: 744768384551 configs: - config_name: CC-MAIN-2013-20 data_files: - split: train path: CC-MAIN-2013-20/train-* - config_name: CC-MAIN-2013-48 data_files: - split: train path: CC-MAIN-2013-48/train-* - config_name: CC-MAIN-2014-10 data_files: - split: train path: CC-MAIN-2014-10/train-* - 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config_name: CC-MAIN-2018-39 data_files: - split: train path: CC-MAIN-2018-39/train-* - config_name: CC-MAIN-2018-43 data_files: - split: train path: CC-MAIN-2018-43/train-* - config_name: CC-MAIN-2018-47 data_files: - split: train path: CC-MAIN-2018-47/train-* - config_name: CC-MAIN-2018-51 data_files: - split: train path: CC-MAIN-2018-51/train-* - config_name: CC-MAIN-2019-04 data_files: - split: train path: CC-MAIN-2019-04/train-* - config_name: CC-MAIN-2019-09 data_files: - split: train path: CC-MAIN-2019-09/train-* - config_name: CC-MAIN-2019-13 data_files: - split: train path: CC-MAIN-2019-13/train-* - config_name: CC-MAIN-2019-18 data_files: - split: train path: CC-MAIN-2019-18/train-* - config_name: CC-MAIN-2019-22 data_files: - split: train path: CC-MAIN-2019-22/train-* - config_name: CC-MAIN-2019-26 data_files: - split: train path: CC-MAIN-2019-26/train-* - config_name: CC-MAIN-2019-30 data_files: - split: train path: CC-MAIN-2019-30/train-* - config_name: CC-MAIN-2019-35 data_files: - split: train path: CC-MAIN-2019-35/train-* - config_name: CC-MAIN-2019-39 data_files: - split: train path: CC-MAIN-2019-39/train-* - config_name: CC-MAIN-2019-43 data_files: - split: train path: CC-MAIN-2019-43/train-* - config_name: CC-MAIN-2019-47 data_files: - split: train path: CC-MAIN-2019-47/train-* - config_name: CC-MAIN-2019-51 data_files: - split: train path: CC-MAIN-2019-51/train-* - config_name: CC-MAIN-2020-05 data_files: - split: train path: CC-MAIN-2020-05/train-* - config_name: CC-MAIN-2020-10 data_files: - split: train path: CC-MAIN-2020-10/train-* - config_name: CC-MAIN-2020-16 data_files: - split: train path: CC-MAIN-2020-16/train-* - config_name: CC-MAIN-2020-24 data_files: - split: train path: CC-MAIN-2020-24/train-* - config_name: CC-MAIN-2020-29 data_files: - split: train path: CC-MAIN-2020-29/train-* - config_name: CC-MAIN-2020-34 data_files: - split: train path: CC-MAIN-2020-34/train-* - config_name: CC-MAIN-2020-40 data_files: - split: train path: CC-MAIN-2020-40/train-* - config_name: CC-MAIN-2020-45 data_files: - split: train path: CC-MAIN-2020-45/train-* - config_name: CC-MAIN-2020-50 data_files: - split: train path: CC-MAIN-2020-50/train-* - config_name: CC-MAIN-2021-04 data_files: - split: train path: CC-MAIN-2021-04/train-* - config_name: CC-MAIN-2021-10 data_files: - split: train path: CC-MAIN-2021-10/train-* - config_name: CC-MAIN-2021-17 data_files: - split: train path: CC-MAIN-2021-17/train-* - config_name: CC-MAIN-2021-21 data_files: - split: train path: CC-MAIN-2021-21/train-* - config_name: CC-MAIN-2021-25 data_files: - split: train path: CC-MAIN-2021-25/train-* - config_name: CC-MAIN-2021-31 data_files: - split: train path: CC-MAIN-2021-31/train-* - config_name: CC-MAIN-2021-39 data_files: - split: train path: CC-MAIN-2021-39/train-* - config_name: CC-MAIN-2021-43 data_files: - split: train path: CC-MAIN-2021-43/train-* - config_name: CC-MAIN-2021-49 data_files: - split: train path: CC-MAIN-2021-49/train-* - config_name: CC-MAIN-2022-05 data_files: - split: train path: CC-MAIN-2022-05/train-* - config_name: CC-MAIN-2022-21 data_files: - split: train path: CC-MAIN-2022-21/train-* - config_name: CC-MAIN-2022-27 data_files: - split: train path: CC-MAIN-2022-27/train-* - config_name: CC-MAIN-2022-33 data_files: - split: train path: CC-MAIN-2022-33/train-* - config_name: CC-MAIN-2022-40 data_files: - split: train path: CC-MAIN-2022-40/train-* - config_name: CC-MAIN-2022-49 data_files: - split: train path: CC-MAIN-2022-49/train-* - config_name: CC-MAIN-2023-06 data_files: - split: train path: CC-MAIN-2023-06/train-* - config_name: CC-MAIN-2023-14 data_files: - split: train path: CC-MAIN-2023-14/train-* - config_name: CC-MAIN-2023-23 data_files: - split: train path: CC-MAIN-2023-23/train-* - config_name: CC-MAIN-2023-40 data_files: - split: train path: CC-MAIN-2023-40/train-* - config_name: CC-MAIN-2023-50 data_files: - split: train path: CC-MAIN-2023-50/train-* --- ⭐️ **NOTE:** Several parquet files were marked unsafe (viruses) by official scaning of hf, while they are reported safe by ClamAV and Virustotal. We found [many false positive cases](https://discuss.huggingface.co/u/mcpotato/summary) of the hf automatic scanning in hf discussions and raise [one discussion](https://discuss.huggingface.co/t/one-parquet-file-of-my-dataset-was-marked-unsafe/113745) to ask for a re-scanning. # OmniCorpus-CC This is the repository of OmniCorpus-CC, which contains 988 million image-text interleaved documents collected from [Common Crawl](https://commoncrawl.org/). - Repository: https://github.com/OpenGVLab/OmniCorpus - Paper: https://arxiv.org/abs/2406.08418 OmniCorpus dataset is a large-scale image-text interleaved dataset, which pushes the boundaries of scale and diversity by encompassing **8.6 billion images** interleaved with **1,696 text tokens** from diverse sources, significantly surpassing previous datasets. This dataset demonstrates several advantages over its counterparts: 1. **Larger data scale:** Our dataset is 1.7 times larger in images and 12.5 times larger in texts compared to the previously largest multimodal dataset, LAION-5B, while maintaining excellent data quality. 2. **Richer data diversity:** Drawing from a broader range of data sources, our dataset is more diverse than other image-text interleaved datasets. It includes bilingual multimodal data in both Chinese and English, and encompasses text-centric and vision-centric documents extracted from common websites and video platforms. 3. **More flexible format:** The streaming data format of our dataset offers exceptional flexibility, allowing adaptation to various data structures, including pure text corpora, image-text pairs, and interleaved data formats. <img width="578" alt="image" src="https://github.com/OpenGVLab/OmniCorpus/assets/47669167/641a6427-ba50-41e6-8634-8810113fd803"> The OmniCorpus contains three sections: - **OmniCorpus-CC**: processed from dumps in Common Crawl from 2013 to Nov./Dec. 2023. - **OmniCorpus-CW**: sourced from Chinese internet resources, will be availiable in [OpenDataLab](https://opendatalab.com/) platform. - **OmniCorpus-YT**: samples Youtube video frames as images and collects subtitles as texts. Code for pre-training, evaluating, main body extracting, and filtering have been released in the official [repository](https://github.com/OpenGVLab/OmniCorpus). A pre-trained model is availiable [here](https://huggingface.co/Qingyun/OmniCorpus-InternVL). # Data Pipeline Our data pipeline consists of five key stages: main body extraction, preliminary text filtering, document deduplication, image downloading \& filtering, and detailed text filtering. Each stage efficiently reduces the dataset to retain only high-quality data. Please refer to our paper for more details about the data pipeline. <img width="723" alt="image" src="https://github.com/OpenGVLab/OmniCorpus/assets/47669167/a6de8928-58fb-4ff4-8ef9-4bd90e9ada5f"> # Usages The image-text interleaved documents are recommanded for the following usages: - Pre-training multimodal large language model (MLLM): Recent MLLMs (such as Flamingo series, EMU series, IDEFICS series, MM1, Cambrian-1, and xGen-MM) have shown that image-text interleaved data aids multimodal in-context learning and maintains the capabilities of large language models during multimodal fine-tuning. - Long text-image retrieval: We provide image-text similarities calculated with CLIP, which can convert the documents to image-text retrieval dataset with longer text. A retrieval model pre-trained on such data can retrieval images based on longer text, which can be used for multimodal RAG, converting pure text to multimodal sample, etc. - Source for futher dataset research: Our data is large-scale, which can serve as the source for researches for data curation strategies. We provide many useful attributes as metadata for each document, which can enrich the filtering strategy and reduce the cost. - ...... # Data Format Following common practices, the data is organized into Parquet file format. You might encounter errors when using `pandas.read_parquet` (because the data structure contains nested elements). We recommend using fastparquet to load the parquet files. ```Python import fastparquet df = fastparquet.ParquetFile(parquet_file_path).to_pandas() # You can also use iter_batches parquet_file = pq.ParquetFile(filepath) for batch in parquet_file.iter_batches(): df = batch.to_pandas() ``` You can convert the i-th document and convert it into a dictionary. ```Python doc_dict = df.iloc[i].to_dict() ``` The document format is as follow: ```json { 'images': [ <str: image_1_url>, None, <str: image_2_url>, None, ], 'texts': [ None, <str: text_paragraph_1_content> None, <str: text_paragraph_2_content>, ] 'metadata': [ <dict: image_1_metadata>, None, <dict: image_2_metadata>, None ], 'general_metadata': { "url": <str: document url>, "id": <str: document id>, "domain": <list[str]: domains extracted from document url>, "fluency_prob": <float: the probability of fluency>, "non_advertisement_prob": <float: the probability of non-advertisement>, "porn_prob": <float: the probability of porn content>, "politics_prob": <float: the probability of politics content>, "toxic_prob": <float: the probability of toxic content>, } } ``` Each image metadata is as follow: ```json { "img_url_sha": <str: sha code of image url>, "width": <int: image width>, "height": <int: image height>, "bytes": <int: byte number of the image file>, "d_hash": <str: d_hash code of the image, used for image deduplication>, "p_hash": <str: p_hash code of the image, used for image deduplication>, "d_hash_dup_count": <int: duplicated times detected by d_hash code>, "p_hash_dup_count": <int: duplicated times detected by p_hash code>, "aesthetic prob": <float: aesthetic probility>, "unsafe prob": <float: NSFW probility>, } ``` # License OmniCorpus is released under a [CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/deed.en) license, with the primary intent of supporting research activities. # Citation ``` @article{li2024omnicorpus, title={OmniCorpus: A Unified Multimodal Corpus of 10 Billion-Level Images Interleaved with Text}, author={Li, Qingyun and Chen, Zhe and Wang, Weiyun and Wang, Wenhai and Ye, Shenglong and Jin, Zhenjiang and others}, journal={arXiv preprint arXiv:2406.08418}, year={2024} } ```

ilsp/mmlu_greek

ilsp

--- dataset_info: - config_name: abstract_algebra features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 58157 num_examples: 100 - name: validation num_bytes: 6010 num_examples: 11 - name: dev num_bytes: 2497 num_examples: 5 download_size: 0 dataset_size: 66664 - config_name: all features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 20041347 num_examples: 14042 - name: validation num_bytes: 2196992 num_examples: 1531 - name: dev num_bytes: 360807 num_examples: 285 download_size: 10333898 dataset_size: 22599146 - config_name: anatomy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 97333 num_examples: 135 - name: validation num_bytes: 9131 num_examples: 14 - name: dev num_bytes: 2731 num_examples: 5 download_size: 67694 dataset_size: 109195 - config_name: astronomy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 141580 num_examples: 152 - name: validation num_bytes: 15462 num_examples: 16 - name: dev num_bytes: 6380 num_examples: 5 download_size: 95251 dataset_size: 163422 - config_name: business_ethics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 101936 num_examples: 100 - name: validation num_bytes: 9096 num_examples: 11 - name: dev num_bytes: 6368 num_examples: 5 download_size: 77394 dataset_size: 117400 - config_name: clinical_knowledge features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 193539 num_examples: 265 - name: validation num_bytes: 20500 num_examples: 29 - name: dev num_bytes: 3720 num_examples: 5 download_size: 126056 dataset_size: 217759 - config_name: college_biology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 152394 num_examples: 144 - name: validation num_bytes: 14995 num_examples: 16 - name: dev num_bytes: 4638 num_examples: 5 download_size: 105576 dataset_size: 172027 - config_name: college_chemistry features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 72251 num_examples: 100 - name: validation num_bytes: 6677 num_examples: 8 - name: dev num_bytes: 3862 num_examples: 5 download_size: 61210 dataset_size: 82790 - config_name: college_computer_science features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 135321 num_examples: 100 - name: validation num_bytes: 15037 num_examples: 11 - name: dev num_bytes: 8606 num_examples: 5 download_size: 101342 dataset_size: 158964 - config_name: college_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 74448 num_examples: 100 - name: validation num_bytes: 8274 num_examples: 11 - name: dev num_bytes: 4276 num_examples: 5 download_size: 63556 dataset_size: 86998 - config_name: college_medicine features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 251805 num_examples: 173 - name: validation num_bytes: 24431 num_examples: 22 - name: dev num_bytes: 5031 num_examples: 5 download_size: 144635 dataset_size: 281267 - config_name: college_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 90708 num_examples: 102 - name: validation num_bytes: 10367 num_examples: 11 - name: dev num_bytes: 4139 num_examples: 5 download_size: 68341 dataset_size: 105214 - config_name: computer_security features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 86922 num_examples: 100 - name: validation num_bytes: 14003 num_examples: 11 - name: dev num_bytes: 3445 num_examples: 5 download_size: 75244 dataset_size: 104370 - config_name: conceptual_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 127706 num_examples: 235 - name: validation num_bytes: 14286 num_examples: 26 - name: dev num_bytes: 2978 num_examples: 5 download_size: 82813 dataset_size: 144970 - config_name: econometrics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 136916 num_examples: 114 - name: validation num_bytes: 14730 num_examples: 12 - name: dev num_bytes: 4794 num_examples: 5 download_size: 86025 dataset_size: 156440 - config_name: electrical_engineering features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 80296 num_examples: 145 - name: validation num_bytes: 9138 num_examples: 16 - name: dev num_bytes: 2824 num_examples: 5 download_size: 62008 dataset_size: 92258 - config_name: elementary_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 211831 num_examples: 378 - name: validation num_bytes: 27305 num_examples: 41 - name: dev num_bytes: 4252 num_examples: 5 download_size: 131272 dataset_size: 243388 - config_name: formal_logic features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 146101 num_examples: 126 - name: validation num_bytes: 18160 num_examples: 14 - name: dev num_bytes: 4917 num_examples: 5 download_size: 77094 dataset_size: 169178 - config_name: global_facts features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 55953 num_examples: 100 - name: validation num_bytes: 5672 num_examples: 10 - name: dev num_bytes: 3547 num_examples: 5 download_size: 0 dataset_size: 65172 - config_name: high_school_biology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 338155 num_examples: 310 - name: validation num_bytes: 33555 num_examples: 32 - name: dev num_bytes: 4992 num_examples: 5 download_size: 200936 dataset_size: 376702 - config_name: high_school_chemistry features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 170771 num_examples: 203 - name: validation num_bytes: 20157 num_examples: 22 - name: dev num_bytes: 3387 num_examples: 5 download_size: 108321 dataset_size: 194315 - config_name: high_school_computer_science features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 139128 num_examples: 100 - name: validation num_bytes: 10800 num_examples: 9 - name: dev num_bytes: 9269 num_examples: 5 download_size: 99359 dataset_size: 159197 - config_name: high_school_european_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 799080 num_examples: 165 - name: validation num_bytes: 88740 num_examples: 18 - name: dev num_bytes: 34585 num_examples: 5 download_size: 503439 dataset_size: 922405 - config_name: high_school_geography features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 132655 num_examples: 198 - name: validation num_bytes: 13612 num_examples: 22 - name: dev num_bytes: 4597 num_examples: 5 download_size: 90939 dataset_size: 150864 - config_name: high_school_government_and_politics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 215224 num_examples: 193 - name: validation num_bytes: 22888 num_examples: 21 - name: dev num_bytes: 5640 num_examples: 5 download_size: 132695 dataset_size: 243752 - config_name: high_school_macroeconomics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 374553 num_examples: 390 - name: validation num_bytes: 41817 num_examples: 43 - name: dev num_bytes: 4310 num_examples: 5 download_size: 177813 dataset_size: 420680 - config_name: high_school_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 161023 num_examples: 270 - name: validation num_bytes: 17224 num_examples: 29 - name: dev num_bytes: 3682 num_examples: 5 download_size: 105683 dataset_size: 181929 - config_name: high_school_microeconomics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 241816 num_examples: 238 - name: validation num_bytes: 24317 num_examples: 26 - name: dev num_bytes: 4029 num_examples: 5 download_size: 125789 dataset_size: 270162 - config_name: high_school_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 175856 num_examples: 151 - name: validation num_bytes: 19899 num_examples: 17 - name: dev num_bytes: 4348 num_examples: 5 download_size: 109639 dataset_size: 200103 - config_name: high_school_psychology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 494955 num_examples: 545 - name: validation num_bytes: 53743 num_examples: 60 - name: dev num_bytes: 5900 num_examples: 5 download_size: 285730 dataset_size: 554598 - config_name: high_school_statistics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 333736 num_examples: 216 - name: validation num_bytes: 30252 num_examples: 23 - name: dev num_bytes: 7320 num_examples: 5 download_size: 191017 dataset_size: 371308 - config_name: high_school_us_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 883614 num_examples: 204 - name: validation num_bytes: 93694 num_examples: 22 - name: dev num_bytes: 26282 num_examples: 5 download_size: 533320 dataset_size: 1003590 - config_name: high_school_world_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 1126143 num_examples: 237 - name: validation num_bytes: 135245 num_examples: 26 - name: dev num_bytes: 14589 num_examples: 5 download_size: 662773 dataset_size: 1275977 - config_name: human_aging features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 145275 num_examples: 223 - name: validation num_bytes: 15038 num_examples: 23 - name: dev num_bytes: 3062 num_examples: 5 download_size: 99856 dataset_size: 163375 - config_name: human_sexuality features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 100379 num_examples: 131 - name: validation num_bytes: 7585 num_examples: 12 - name: dev num_bytes: 3504 num_examples: 5 download_size: 74540 dataset_size: 111468 - config_name: international_law features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 162013 num_examples: 121 - name: validation num_bytes: 18937 num_examples: 13 - name: dev num_bytes: 7290 num_examples: 5 download_size: 0 dataset_size: 188240 - config_name: jurisprudence features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 102393 num_examples: 108 - name: validation num_bytes: 11049 num_examples: 11 - name: dev num_bytes: 3754 num_examples: 5 download_size: 21545 dataset_size: 117196 - config_name: logical_fallacies features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 153973 num_examples: 163 - name: validation num_bytes: 15857 num_examples: 18 - name: dev num_bytes: 4919 num_examples: 5 download_size: 82298 dataset_size: 174749 - config_name: machine_learning features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 102745 num_examples: 112 - name: validation num_bytes: 9797 num_examples: 11 - name: dev num_bytes: 7448 num_examples: 5 download_size: 70870 dataset_size: 119990 - config_name: management features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 63772 num_examples: 103 - name: validation num_bytes: 5671 num_examples: 11 - name: dev num_bytes: 2677 num_examples: 5 download_size: 52323 dataset_size: 72120 - config_name: marketing features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 191635 num_examples: 234 - name: validation num_bytes: 22377 num_examples: 25 - name: dev num_bytes: 4734 num_examples: 5 download_size: 122877 dataset_size: 218746 - config_name: medical_genetics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 64177 num_examples: 100 - name: validation num_bytes: 9298 num_examples: 11 - name: dev num_bytes: 3405 num_examples: 5 download_size: 58337 dataset_size: 76880 - config_name: miscellaneous features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 443155 num_examples: 783 - name: validation num_bytes: 42990 num_examples: 86 - name: dev num_bytes: 1877 num_examples: 5 download_size: 283087 dataset_size: 488022 - config_name: moral_disputes features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 332269 num_examples: 346 - name: validation num_bytes: 38501 num_examples: 38 - name: dev num_bytes: 5222 num_examples: 5 download_size: 193075 dataset_size: 375992 - config_name: moral_scenarios features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 1061634 num_examples: 895 - name: validation num_bytes: 120664 num_examples: 100 - name: dev num_bytes: 5816 num_examples: 5 download_size: 283716 dataset_size: 1188114 - config_name: nutrition features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 281680 num_examples: 306 - name: validation num_bytes: 25350 num_examples: 33 - name: dev num_bytes: 6423 num_examples: 5 download_size: 168790 dataset_size: 313453 - config_name: philosophy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 240333 num_examples: 311 - name: validation num_bytes: 27480 num_examples: 34 - name: dev num_bytes: 2986 num_examples: 5 download_size: 153970 dataset_size: 270799 - config_name: prehistory features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 267644 num_examples: 324 - name: validation num_bytes: 30414 num_examples: 35 - name: dev num_bytes: 5577 num_examples: 5 download_size: 172053 dataset_size: 303635 - config_name: professional_accounting features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 377751 num_examples: 282 - name: validation num_bytes: 42879 num_examples: 31 - name: dev num_bytes: 6331 num_examples: 5 download_size: 228950 dataset_size: 426961 - config_name: professional_law features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 5612166 num_examples: 1534 - name: validation num_bytes: 604980 num_examples: 170 - name: dev num_bytes: 19825 num_examples: 5 download_size: 3065337 dataset_size: 6236971 - config_name: professional_medicine features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 639421 num_examples: 272 - name: validation num_bytes: 70186 num_examples: 31 - name: dev num_bytes: 11017 num_examples: 5 download_size: 391893 dataset_size: 720624 - config_name: professional_psychology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 687869 num_examples: 612 - name: validation num_bytes: 87912 num_examples: 69 - name: dev num_bytes: 6693 num_examples: 5 download_size: 405705 dataset_size: 782474 - config_name: public_relations features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 89435 num_examples: 110 - name: validation num_bytes: 14174 num_examples: 12 - name: dev num_bytes: 4718 num_examples: 5 download_size: 0 dataset_size: 108327 - config_name: security_studies features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 632255 num_examples: 245 - name: validation num_bytes: 69100 num_examples: 27 - name: dev num_bytes: 16171 num_examples: 5 download_size: 0 dataset_size: 717526 - config_name: sociology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 204018 num_examples: 201 - name: validation num_bytes: 22531 num_examples: 22 - name: dev num_bytes: 5054 num_examples: 5 download_size: 9676 dataset_size: 231603 - config_name: us_foreign_policy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 89965 num_examples: 100 - name: validation num_bytes: 10270 num_examples: 11 - name: dev num_bytes: 5111 num_examples: 5 download_size: 68974 dataset_size: 105346 - config_name: virology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 116211 num_examples: 166 - name: validation num_bytes: 16273 num_examples: 18 - name: dev num_bytes: 3185 num_examples: 5 download_size: 96586 dataset_size: 135669 - config_name: world_religions features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: int64 - name: orig_question dtype: string - name: orig_subject dtype: string - name: orig_choices sequence: string splits: - name: test num_bytes: 77273 num_examples: 171 - name: validation num_bytes: 8462 num_examples: 19 - name: dev num_bytes: 2073 num_examples: 5 download_size: 61169 dataset_size: 87808 configs: - config_name: abstract_algebra data_files: - split: test path: abstract_algebra/test-* - split: validation path: abstract_algebra/validation-* - split: dev path: abstract_algebra/dev-* - config_name: all data_files: - split: test path: all/test-* - split: validation path: all/validation-* - split: dev path: all/dev-* - config_name: anatomy data_files: - split: test path: anatomy/test-* - split: validation path: anatomy/validation-* - split: dev path: anatomy/dev-* - config_name: astronomy data_files: - split: test path: astronomy/test-* - split: validation path: astronomy/validation-* - split: dev path: astronomy/dev-* - config_name: business_ethics data_files: - split: test path: business_ethics/test-* - split: validation path: business_ethics/validation-* - split: dev path: business_ethics/dev-* - config_name: clinical_knowledge data_files: - split: test path: clinical_knowledge/test-* - split: validation path: clinical_knowledge/validation-* - split: dev path: clinical_knowledge/dev-* - config_name: college_biology data_files: - split: test path: college_biology/test-* - split: validation path: college_biology/validation-* - split: dev path: college_biology/dev-* - config_name: college_chemistry data_files: - split: test path: college_chemistry/test-* - split: validation path: college_chemistry/validation-* - split: dev path: college_chemistry/dev-* - config_name: college_computer_science data_files: - split: test path: college_computer_science/test-* - split: validation path: college_computer_science/validation-* - split: dev path: college_computer_science/dev-* - config_name: college_mathematics data_files: - split: test path: college_mathematics/test-* - split: validation path: college_mathematics/validation-* - split: dev path: college_mathematics/dev-* - config_name: college_medicine data_files: - split: test path: college_medicine/test-* - split: validation path: college_medicine/validation-* - split: dev path: college_medicine/dev-* - config_name: college_physics data_files: - split: test path: college_physics/test-* - split: validation path: college_physics/validation-* - split: dev path: college_physics/dev-* - config_name: computer_security data_files: - split: test path: computer_security/test-* - split: validation path: computer_security/validation-* - split: dev path: computer_security/dev-* - config_name: conceptual_physics data_files: - split: test path: conceptual_physics/test-* - split: validation path: conceptual_physics/validation-* - split: dev path: conceptual_physics/dev-* - config_name: econometrics data_files: - split: test path: econometrics/test-* - split: validation path: econometrics/validation-* - split: dev path: econometrics/dev-* - config_name: electrical_engineering data_files: - split: test path: electrical_engineering/test-* - split: validation path: electrical_engineering/validation-* - split: dev path: electrical_engineering/dev-* - config_name: elementary_mathematics data_files: - split: test path: elementary_mathematics/test-* - split: validation path: elementary_mathematics/validation-* - split: dev path: elementary_mathematics/dev-* - config_name: formal_logic data_files: - split: test path: formal_logic/test-* - split: validation path: formal_logic/validation-* - split: dev path: formal_logic/dev-* - config_name: global_facts data_files: - split: test path: global_facts/test-* - split: validation path: global_facts/validation-* - split: dev path: global_facts/dev-* - config_name: high_school_biology data_files: - split: test path: high_school_biology/test-* - split: validation path: high_school_biology/validation-* - split: dev path: high_school_biology/dev-* - config_name: high_school_chemistry data_files: - split: test path: high_school_chemistry/test-* - split: validation path: high_school_chemistry/validation-* - split: dev path: high_school_chemistry/dev-* - config_name: high_school_computer_science data_files: - split: test path: high_school_computer_science/test-* - split: validation path: high_school_computer_science/validation-* - split: dev path: high_school_computer_science/dev-* - config_name: high_school_european_history data_files: - split: test path: high_school_european_history/test-* - split: validation path: high_school_european_history/validation-* - split: dev path: high_school_european_history/dev-* - config_name: high_school_geography data_files: - split: test path: high_school_geography/test-* - split: validation path: high_school_geography/validation-* - split: dev path: high_school_geography/dev-* - config_name: high_school_government_and_politics data_files: - split: test path: high_school_government_and_politics/test-* - split: validation path: high_school_government_and_politics/validation-* - split: dev path: high_school_government_and_politics/dev-* - config_name: high_school_macroeconomics data_files: - split: test path: high_school_macroeconomics/test-* - split: validation path: high_school_macroeconomics/validation-* - split: dev path: high_school_macroeconomics/dev-* - config_name: high_school_mathematics data_files: - split: test path: high_school_mathematics/test-* - split: validation path: high_school_mathematics/validation-* - split: dev path: high_school_mathematics/dev-* - config_name: high_school_microeconomics data_files: - split: test path: high_school_microeconomics/test-* - split: validation path: high_school_microeconomics/validation-* - split: dev path: high_school_microeconomics/dev-* - config_name: high_school_physics data_files: - split: test path: high_school_physics/test-* - split: validation path: high_school_physics/validation-* - split: dev path: high_school_physics/dev-* - config_name: high_school_psychology data_files: - split: test path: high_school_psychology/test-* - split: validation path: high_school_psychology/validation-* - split: dev path: high_school_psychology/dev-* - config_name: high_school_statistics data_files: - split: test path: high_school_statistics/test-* - split: validation path: high_school_statistics/validation-* - split: dev path: high_school_statistics/dev-* - config_name: high_school_us_history data_files: - split: test path: high_school_us_history/test-* - split: validation path: high_school_us_history/validation-* - split: dev path: high_school_us_history/dev-* - config_name: high_school_world_history data_files: - split: test path: high_school_world_history/test-* - split: validation path: high_school_world_history/validation-* - split: dev path: high_school_world_history/dev-* - config_name: human_aging data_files: - split: test path: human_aging/test-* - split: validation path: human_aging/validation-* - split: dev path: human_aging/dev-* - config_name: human_sexuality data_files: - split: test path: human_sexuality/test-* - split: validation path: human_sexuality/validation-* - split: dev path: human_sexuality/dev-* - config_name: international_law data_files: - split: test path: international_law/test-* - split: validation path: international_law/validation-* - split: dev path: international_law/dev-* - config_name: jurisprudence data_files: - split: test path: jurisprudence/test-* - split: validation path: jurisprudence/validation-* - split: dev path: jurisprudence/dev-* - config_name: logical_fallacies data_files: - split: test path: logical_fallacies/test-* - split: validation path: logical_fallacies/validation-* - split: dev path: logical_fallacies/dev-* - config_name: machine_learning data_files: - split: test path: machine_learning/test-* - split: validation path: machine_learning/validation-* - split: dev path: machine_learning/dev-* - config_name: management data_files: - split: test path: management/test-* - split: validation path: management/validation-* - split: dev path: management/dev-* - config_name: marketing data_files: - split: test path: marketing/test-* - split: validation path: marketing/validation-* - split: dev path: marketing/dev-* - config_name: medical_genetics data_files: - split: test path: medical_genetics/test-* - split: validation path: medical_genetics/validation-* - split: dev path: medical_genetics/dev-* - config_name: miscellaneous data_files: - split: test path: miscellaneous/test-* - split: validation path: miscellaneous/validation-* - split: dev path: miscellaneous/dev-* - config_name: moral_disputes data_files: - split: test path: moral_disputes/test-* - split: validation path: moral_disputes/validation-* - split: dev path: moral_disputes/dev-* - config_name: moral_scenarios data_files: - split: test path: moral_scenarios/test-* - split: validation path: moral_scenarios/validation-* - split: dev path: moral_scenarios/dev-* - config_name: nutrition data_files: - split: test path: nutrition/test-* - split: validation path: nutrition/validation-* - split: dev path: nutrition/dev-* - config_name: philosophy data_files: - split: test path: philosophy/test-* - split: validation path: philosophy/validation-* - split: dev path: philosophy/dev-* - config_name: prehistory data_files: - split: test path: prehistory/test-* - split: validation path: prehistory/validation-* - split: dev path: prehistory/dev-* - config_name: professional_accounting data_files: - split: test path: professional_accounting/test-* - split: validation path: professional_accounting/validation-* - split: dev path: professional_accounting/dev-* - config_name: professional_law data_files: - split: test path: professional_law/test-* - split: validation path: professional_law/validation-* - split: dev path: professional_law/dev-* - config_name: professional_medicine data_files: - split: test path: professional_medicine/test-* - split: validation path: professional_medicine/validation-* - split: dev path: professional_medicine/dev-* - config_name: professional_psychology data_files: - split: test path: professional_psychology/test-* - split: validation path: professional_psychology/validation-* - split: dev path: professional_psychology/dev-* - config_name: public_relations data_files: - split: test path: public_relations/test-* - split: validation path: public_relations/validation-* - split: dev path: public_relations/dev-* - config_name: security_studies data_files: - split: test path: security_studies/test-* - split: validation path: security_studies/validation-* - split: dev path: security_studies/dev-* - config_name: sociology data_files: - split: test path: sociology/test-* - split: validation path: sociology/validation-* - split: dev path: sociology/dev-* - config_name: us_foreign_policy data_files: - split: test path: us_foreign_policy/test-* - split: validation path: us_foreign_policy/validation-* - split: dev path: us_foreign_policy/dev-* - config_name: virology data_files: - split: test path: virology/test-* - split: validation path: virology/validation-* - split: dev path: virology/dev-* - config_name: world_religions data_files: - split: test path: world_religions/test-* - split: validation path: world_religions/validation-* - split: dev path: world_religions/dev-* --- # Dataset Card for MMLU Greek The MMLU Greek dataset is a set of 15858 examples from the MMLU dataset [available from here and here], machine-translated into Greek. The original dataset consists of multiple-choice questions from 57 tasks including elementary mathematics, US history, computer science, law, etc. ## Dataset Details ### Dataset Description - **Curated by:** ILSP/Athena RC - **Language(s) (NLP):** el - **License:** cc-by-nc-sa-4.0 ## Bias, Risks, and Limitations <!-- This section is meant to convey both technical and sociotechnical limitations. --> This dataset is the result of machine translation. ## Dataset Card Contact https://www.athenarc.gr/en/ilsp

Voxel51/Office-Home

Voxel51

--- annotations_creators: [] language: en license: other size_categories: - 10K<n<100K task_categories: - image-classification task_ids: [] pretty_name: Office-Home tags: - fiftyone - image - image-classification - domain-adaptation dataset_summary: >  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 15588 samples. ## Installation If you haven't already, install FiftyOne: ```bash pip install -U fiftyone ``` ## Usage ```python import fiftyone as fo import fiftyone.utils.huggingface as fouh # Load the dataset # Note: other available arguments include 'max_samples', etc dataset = fouh.load_from_hub("Voxel51/Office-Home") # Launch the App session = fo.launch_app(dataset) ``` --- # Dataset Card for Office-Home <!-- Provide a quick summary of the dataset. -->  This is a [FiftyOne](https://github.com/voxel51/fiftyone) dataset with 15588 samples. ## Installation If you haven't already, install FiftyOne: ```bash pip install -U fiftyone ``` ## Usage ```python import fiftyone as fo import fiftyone.utils.huggingface as fouh # Load the dataset # Note: other available arguments include 'max_samples', etc dataset = fouh.load_from_hub("Voxel51/Office-Home") # Launch the App session = fo.launch_app(dataset) ``` ## Dataset Details ### Dataset Description The Office-Home dataset has been created to evaluate domain adaptation algorithms for object recognition using deep learning. It consists of images from 4 different domains: Artistic images, Clip Art, Product images and Real-World images. For each domain, the dataset contains images of 65 object categories found typically in Office and Home settings. - **Curated by:** [Jose Eusebio](https://www.linkedin.com/in/jmeusebio) - **Language(s) (NLP):** en - **License:** other ### Dataset Sources - **Homepage:** https://www.hemanthdv.org/officeHomeDataset.html - **Paper:** [Deep Hashing Network for Unsupervised Domain Adaptation](https://openaccess.thecvf.com/content_cvpr_2017/papers/Venkateswara_Deep_Hashing_Network_CVPR_2017_paper.pdf) ## Dataset Creation ### Source Data <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). --> #### Data Collection and Processing <!-- This section describes the data collection and processing process such as data selection criteria, filtering and normalization methods, tools and libraries used, etc. --> The images in the dataset were collected using a python web-crawler that crawled through several search engines and online image directories. This initial run searched for around 120 different objects and produced over 100,000 images across the different categories and domains. These images were then filtered to ensure that the desired object was in the picture. Categories were also filtered to make sure that each category had at least a certain number of images. The latest version of the dataset contains around 15,500 images from 65 different categories. | Domain | Min: # | Min: # | Min: # | Acc. | |---------|--------|-------------------------|----------------------------|------------------------| | Art | 15 | 117 \(\times\) 85 pix. | 4384 \(\times\) 2686 pix. | 44.99 \(\pm\) 1.85 | | Clipart | 39 | 18 \(\times\) 18 pix. | 2400 \(\times\) 2400 pix. | 53.95 \(\pm\) 1.45 | | Product | 38 | 75 \(\times\) 63 pix. | 2560 \(\times\) 2560 pix. | 66.41 \(\pm\) 1.18 | | Product | 23 | 88 \(\times\) 80 pix. | 6500 \(\times\) 4900 pix. | 59.70 \(\pm\) 1.04 | Caption: Statistics for the Office-Home dataset. Min: # is the minimum number of images of each object for the specified domain. Min: Size and Max: Size are the minimum and maximum image sizes in the domain. Acc: is the classification accuracy using a linear SVM (LIBLINEAR) classifier with 5-fold cross-validation using deep features extracted from the VGG-F deep network. The 65 object categories in the dataset are: ```plaintext Alarm Clock, Backpack, Batteries, Bed, Bike, Bottle, Bucket, Calculator, Calendar, Candles, Chair, Clipboards, Computer, Couch, Curtains, Desk Lamp, Drill, Eraser, Exit Sign, Fan, File Cabinet, Flipflops, Flowers, Folder, Fork, Glasses, Hammer, Helmet, Kettle, Keyboard, Knives, Lamp Shade, Laptop, Marker, Monitor, Mop, Mouse, Mug, Notebook, Oven, Pan, Paper Clip, Pen, Pencil, Postit Notes, Printer, Push Pin, Radio, Refrigerator, ruler, Scissors, Screwdriver, Shelf, Sink, Sneakers, Soda, Speaker, Spoon, Table, Telephone, Toothbrush, Toys, Trash Can, TV, Webcam ``` ## Citation <!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. --> **BibTeX:** ```bibtex @inproceedings{venkateswara2017deep, title={Deep hashing network for unsupervised domain adaptation}, author={Venkateswara, Hemanth and Eusebio, Jose and Chakraborty, Shayok and Panchanathan, Sethuraman}, booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition}, pages={5018--5027}, year={2017} } ``` ## Fair Use Notice This dataset contains some copyrighted material whose use has not been specifically authorized by the copyright owners. In an effort to advance scientific research, we make this material available for academic research. We believe this constitutes a fair use of any such copyrighted material as provided for in section 107 of the US Copyright Law. In accordance with Title 17 U.S.C. Section 107, the material on this site is distributed without profit for non-commercial research and educational purposes. For more information on fair use please click here. If you wish to use copyrighted material on this site or in our dataset for purposes of your own that go beyond non-commercial research and academic purposes, you must obtain permission directly from the copyright owner. (adapted from [Christopher Thomas](http://people.cs.pitt.edu/~chris/photographer/)) ## Dataset Card Author [Jacob Marks](https://huggingface.co/jamarks)

jacobbieker/eumetsat-cloudmask-rss

jacobbieker

--- license: mit ---

codeShare/text-to-image-prompts

codeShare

--- license: mit task_categories: - text-to-image - image-classification language: - en pretty_name: fusionn-t2i size_categories: - 100K<n<1M --- If you have questions about this dataset , feel free to ask them on the fusion-discord : [https://discord.gg/8TVHPf6Edn](https://discord.gg/8TVHPf6Edn) This collection contains sets from the fusion-t2i-ai-generator on perchance. This datset is used in this notebook: https://huggingface.co/datasets/codeShare/text-to-image-prompts/tree/main/Google%20Colab%20Notebooks To see the full sets, please use the url "https://perchance.org/" + url , where the urls are listed below: ``` _generator gen_e621 fusion-t2i-e621-tags-1 fusion-t2i-e621-tags-2 fusion-t2i-e621-tags-3 fusion-t2i-e621-tags-4 fusion-t2i-e621-tags-5 fusion-t2i-e621-tags-6 fusion-t2i-e621-tags-7 fusion-t2i-e621-tags-8 fusion-t2i-e621-tags-9 fusion-t2i-e621-tags-10 fusion-t2i-e621-tags-11 fusion-t2i-e621-tags-12 fusion-t2i-e621-tags-13 fusion-t2i-e621-tags-14 fusion-t2i-e621-tags-15 fusion-t2i-e621-tags-16 fusion-t2i-e621-tags-17 fusion-t2i-e621-tags-18 fusion-t2i-e621-tags-19 fusion-t2i-e621-tags-20 fusion-t2i-e621-tags-21 fusion-t2i-e621-tags-22 fusion-t2i-e621-tags-23 //--NEW STUFF clipartist //fusion-t2i-clip-artists-1 //fusion-t2i-clip-artists-2 //fusion-t2i-clip-artists-3 //fusion-t2i-clip-artists-4 //fusion-t2i-clip-artists-5 //fusion-t2i-clip-artists-6 fusion-t2i-clip-artists-7 //<--Only this set of SDXL artists for now (test to see if better) clipflavour fusion-t2i-clip-flavours-1 fusion-t2i-clip-flavours-2 fusion-t2i-clip-flavours-3 fusion-t2i-clip-flavours-3 //4 no exist? fusion-t2i-clip-flavours-5 fusion-t2i-clip-flavours-6 fusion-t2i-clip-flavours-7 fusion-t2i-clip-flavours-8 fusion-t2i-clip-flavours-9 fusion-t2i-clip-flavours-10 fusion-t2i-clip-flavours-10 //10 too fusion-t2i-clip-flavours-12 fusion-t2i-clip-flavours-13 fusion-t2i-clip-flavours-14 fusion-t2i-clip-flavours-15 fusion-t2i-clip-flavours-16 fusion-t2i-clip-flavours-16 //17? fusion-t2i-clip-flavours-18 fusion-t2i-clip-flavours-19 fusion-t2i-clip-flavours-20 fusion-t2i-clip-flavours-21 fusion-t2i-clip-flavours-22 fusion-t2i-clip-flavours-23 fusion-t2i-clip-flavours-24 fusion-t2i-clip-flavours-24 //25 fusion-t2i-clip-flavours-26 fusion-t2i-clip-flavours-27 fusion-t2i-clip-flavours-28 fusion-t2i-clip-flavours-29 fusion-t2i-clip-flavours-30 //-----// ypf fusion-t2i-civitai-21-30-chars-mix-1 fusion-t2i-civitai-21-30-chars-mix-2 fusion-t2i-civitai-21-30-chars-mix-3 fusion-t2i-civitai-21-30-chars-mix-4 fusion-t2i-civitai-21-30-chars-mix-5 fusion-t2i-civitai-21-30-chars-mix-6 fusion-t2i-civitai-21-30-chars-mix-7 fusion-t2i-civitai-21-30-chars-mix-8 bpf fusion-t2i-civitai-0-20-chars-mix-1 fusion-t2i-civitai-0-20-chars-mix-2 fusion-t2i-civitai-0-20-chars-mix-3 fusion-t2i-civitai-0-20-chars-mix-4 fusion-t2i-civitai-0-20-chars-mix-5 fusion-t2i-civitai-0-20-chars-mix-6 fusion-t2i-civitai-0-20-chars-mix-7 fusion-t2i-civitai-0-20-chars-mix-8 fusion-t2i-civitai-0-20-chars-mix-9 fusion-t2i-civitai-0-20-chars-mix-10 fusion-t2i-civitai-0-20-chars-mix-11 fusion-t2i-civitai-0-20-chars-mix-12 fusion-t2i-civitai-0-20-chars-mix-13 fusion-t2i-civitai-0-20-chars-mix-14 fusion-t2i-civitai-0-20-chars-mix-15 fusion-t2i-civitai-0-20-chars-mix-16 fusion-t2i-civitai-0-20-chars-mix-17 fusion-t2i-civitai-0-20-chars-mix-18 fusion-t2i-civitai-0-20-chars-mix-19 fusion-t2i-civitai-0-20-chars-mix-20 fusion-t2i-civitai-0-20-chars-mix-21 fusion-t2i-civitai-0-20-chars-mix-22 fusion-t2i-civitai-0-20-chars-mix-23 fusion-t2i-civitai-0-20-chars-mix-24 fusion-t2i-civitai-0-20-chars-mix-25 fusion-t2i-civitai-0-20-chars-mix-26 fusion-t2i-civitai-0-20-chars-mix-27 fusion-t2i-civitai-0-20-chars-mix-28 fusion-t2i-civitai-0-20-chars-mix-29 fusion-t2i-civitai-0-20-chars-mix-30 fusion-t2i-civitai-0-20-chars-mix-31 fusion-t2i-civitai-0-20-chars-mix-32 fusion-t2i-civitai-0-20-chars-mix-33 fusion-t2i-civitai-0-20-chars-mix-34 fusion-t2i-civitai-0-20-chars-mix-35 fusion-t2i-civitai-0-20-chars-mix-36 fusion-t2i-civitai-0-20-chars-mix-37 fusion-t2i-civitai-0-20-chars-mix-38 fusion-t2i-civitai-0-20-chars-mix-39 fusion-t2i-civitai-0-20-chars-mix-40 fusion-t2i-civitai-0-20-chars-mix-41 fusion-t2i-civitai-0-20-chars-mix-42 fusion-t2i-civitai-0-20-chars-mix-43 fusion-t2i-civitai-0-20-chars-mix-44 fusion-t2i-civitai-0-20-chars-mix-45 fusion-t2i-civitai-0-20-chars-mix-46 fmc fusion-t2i-female-movie-characters-2 fusion-t2i-female-movie-characters-3 fusion-t2i-female-movie-characters-4 fusion-t2i-female-movie-characters-5 fusion-t2i-female-movie-characters-6 nationalities fusion-t2i-nationality-1 fusion-t2i-nationality-1 artby fusion-t2i-art-by-prompts-1 fusion-t2i-art-by-prompts-1 emojis fusion-t2i-emojis-2 fusion-t2i-emojis-2 moviegenres fusion-t2i-moviegenre-1 fusion-t2i-moviegenre-1 movietitles fusion-t2i-movietitle-4 fusion-t2i-movietitle-5 fusion-t2i-movietitle-6 fusion-t2i-movietitle-7 fusion-t2i-movietitle-8 fusion-t2i-movietitle-9 fusion-t2i-movietitle-10 fusion-t2i-movietitle-11 fusion-t2i-movietitle-12 fusion-t2i-movietitle-13 fusion-t2i-movietitle-14 fusion-t2i-movietitle-15 fusion-t2i-movietitle-16 fusion-t2i-movietitle-17 fusion-t2i-movietitle-18 fusion-t2i-movietitle-19 fusion-t2i-movietitle-20 videogametitles fusion-t2i-videogame-title-1 fusion-t2i-videogame-title-2 fusion-t2i-videogame-title-3 tvseries fusion-t2i-tv-series-2 fusion-t2i-tv-series-3 moviestudios fusion-t2i-moviestudios-1 fusion-t2i-moviestudios-1 lingerie //fusion-t2i-lingerie-1 fusion-t2i-lingerie-1 fusion-t2i-lingerie-2 //With brands apadj //apparel adjective fusion-t2i-apparel-adjective-1 fusion-t2i-apparel-adjective-1 movies fusion-t2i-movies-1 fusion-t2i-movies-2 fusion-t2i-movies-3 fantasycreatures fusion-t2i-fantasy-creature-1 fusion-t2i-fantasy-creature-1 fantasyclasses fusion-t2i-fantasy-class-1 fusion-t2i-fantasy-class-1 unicodes fusion-t2i-unicode-2 fusion-t2i-unicode-2 unicode_prefix fusion-t2i-unicode-prefix-1 fusion-t2i-unicode-prefix-1 unicode_suffix fusion-t2i-unicode-suffix-1 fusion-t2i-unicode-suffix-1 gen_r34tags fusion-t2i-rule34-tags-1 fusion-t2i-rule34-tags-2 fusion-t2i-rule34-tags-3 fusion-t2i-rule34-tags-4 fusion-t2i-rule34-tags-5 r34artists fusion-t2i-rule34-artists-1 fusion-t2i-rule34-artists-1 nsfwpromptfeatures fusion-t2i-nsfw-prompt-features-1 fusion-t2i-nsfw-prompt-features-2 youngcelebs fusion-t2i-young-celebrities-1 fusion-t2i-young-celebrities-1 //New set gfn fusion-t2i-girl-firstname-1 fusion-t2i-girl-firstname-2 fusion-t2i-girl-firstname-3 fusion-t2i-girl-firstname-4 fusion-t2i-girl-firstname-5 fusion-t2i-girl-firstname-6 fusion-t2i-girl-firstname-7 fusion-t2i-girl-firstname-8 fusion-t2i-girl-firstname-9 fusion-t2i-girl-firstname-10 fusion-t2i-girl-firstname-11 fusion-t2i-girl-firstname-12 fusion-t2i-girl-firstname-13 fusion-t2i-girl-firstname-14 fusion-t2i-girl-firstname-15 fusion-t2i-girl-firstname-16 fusion-t2i-girl-firstname-17 fusion-t2i-girl-firstname-18 fusion-t2i-girl-firstname-19 fusion-t2i-girl-firstname-20 fusion-t2i-girl-firstname-21 fusion-t2i-girl-firstname-22 fusion-t2i-girl-firstname-23 fusion-t2i-girl-firstname-24 fusion-t2i-girl-firstname-25 fusion-t2i-girl-firstname-26 fusion-t2i-girl-firstname-27 fusion-t2i-girl-firstname-28 fusion-t2i-girl-firstname-29 fusion-t2i-girl-firstname-30 animals fusion-t2i-animals-1 fusion-t2i-animals-1 //Old set lastNames fusion-t2i-lastnames-19 fusion-t2i-lastnames-1 fusion-t2i-lastnames-2 fusion-t2i-lastnames-3 fusion-t2i-lastnames-4 fusion-t2i-lastnames-5 fusion-t2i-lastnames-6 fusion-t2i-lastnames-7 fusion-t2i-lastnames-8 fusion-t2i-lastnames-9 fusion-t2i-lastnames-10 fusion-t2i-lastnames-11 fusion-t2i-lastnames-12 fusion-t2i-lastnames-13 fusion-t2i-lastnames-14 fusion-t2i-lastnames-15 fusion-t2i-lastnames-16 fusion-t2i-lastnames-17 fusion-t2i-lastnames-18 fusion-t2i-lastnames-20 media fusion-t2i-media-outlets-1 fusion-t2i-media-outlets-1 unused yada gen_danbooru fusion-t2i-danbooru-tags-1 fusion-t2i-danbooru-tags-2 fusion-t2i-danbooru-tags-3 fusion-t2i-danbooru-tags-4 fusion-t2i-danbooru-tags-5 fusion-t2i-danbooru-tags-6 fusion-t2i-danbooru-tags-7 fusion-t2i-danbooru-tags-8 fusion-t2i-danbooru-tags-9 fusion-t2i-danbooru-tags-10 fusion-t2i-danbooru-tags-11 fusion-t2i-danbooru-tags-12 fusion-t2i-danbooru-tags-13 fusion-t2i-danbooru-tags-14 fusion-t2i-danbooru-tags-15 fusion-t2i-danbooru-tags-16 fusion-t2i-danbooru-tags-17 fusion-t2i-danbooru-tags-18 fusion-t2i-danbooru-tags-19 fusion-t2i-danbooru-tags-20 fusion-t2i-danbooru-tags-21 fusion-t2i-danbooru-tags-22 fusion-t2i-danbooru-tags-23 fusion-t2i-danbooru-tags-24 fusion-t2i-danbooru-tags-25 fusion-t2i-danbooru-tags-26 fusion-t2i-danbooru-tags-27 fusion-t2i-danbooru-tags-28 fusion-t2i-danbooru-tags-29 fusion-t2i-danbooru-tags-30 fusion-t2i-danbooru-tags-31 fusion-t2i-danbooru-tags-32 fusion-t2i-danbooru-tags-33 gen_lyrics fusion-t2i-lyrics-letterwords-1 fusion-t2i-lyrics-letterwords-2 fusion-t2i-lyrics-letterwords-3 fusion-t2i-lyrics-letterwords-4 fusion-t2i-lyrics-letterwords-5 fusion-t2i-lyrics-letterwords-6 fusion-t2i-lyrics-letterwords-7 fusion-t2i-lyrics-letterwords-8 fusion-t2i-lyrics-letterwords-9 fusion-t2i-lyrics-letterwords-10 //new edits gen_nsfw fusion-t2i-nsfw-terms-1 fusion-t2i-nsfw-terms-2 //fusion-t2i-nsfw-terms-3 gen_nsfwtags fusion-t2i-nsfw-terms-1 fusion-t2i-nsfw-terms-2 nsfwtagscommon fusion-t2i-nsfw-tags-common-1 fusion-t2i-nsfw-tags-common-1 /// //unused old_nsfw fusion-t2i-nsfw-terms-3 fusion-t2i-nsfw-terms-4 fusion-t2i-nsfw-terms-5 fusion-t2i-nsfw-terms-6 fusion-t2i-nsfw-terms-7 fusion-t2i-nsfw-terms-8 fusion-t2i-nsfw-terms-9 fusion-t2i-nsfw-terms-10 fusion-t2i-nsfw-terms-11 fusion-t2i-nsfw-terms-12 fusion-t2i-nsfw-terms-13 fusion-t2i-nsfw-terms-14 fusion-t2i-nsfw-terms-15 fusion-t2i-nsfw-terms-16 fusion-t2i-nsfw-terms-17 fusion-t2i-nsfw-terms-18 fusion-t2i-nsfw-tags-2 fusion-t2i-nsfw-tags-3 fusion-t2i-nsfw-tags-4 fusion-t2i-nsfw-tags-5 fusion-t2i-nsfw-tags-6 fusion-t2i-nsfw-tags-7 fusion-t2i-nsfw-tags-8 fusion-t2i-nsfw-tags- flagnames fusion-t2i-names-from-flag-1 fusion-t2i-names-from-flag-1 common_prefix fusion-t2i-sd15-clip-tokens-common-prefix-1 fusion-t2i-sd15-clip-tokens-common-prefix-2 fusion-t2i-sd15-clip-tokens-common-prefix-3 average_prefix fusion-t2i-sd15-clip-tokens-average-prefix-1 fusion-t2i-sd15-clip-tokens-average-prefix-2 fusion-t2i-sd15-clip-tokens-average-prefix-3 rare_prefix fusion-t2i-sd15-clip-tokens-rare-prefix-1 fusion-t2i-sd15-clip-tokens-rare-prefix-2 fusion-t2i-sd15-clip-tokens-rare-prefix-3 weird_prefix fusion-t2i-sd15-clip-tokens-weird-prefix-1 fusion-t2i-sd15-clip-tokens-weird-prefix-2 fusion-t2i-sd15-clip-tokens-weird-prefix-3 exotic_prefix fusion-t2i-sd15-clip-tokens-exotic-prefix-1 fusion-t2i-sd15-clip-tokens-exotic-prefix-2 fusion-t2i-sd15-clip-tokens-exotic-prefix-3 common_suffix fusion-t2i-sd15-clip-tokens-common-suffix-1 fusion-t2i-sd15-clip-tokens-common-suffix-2 fusion-t2i-sd15-clip-tokens-common-suffix-3 fusion-t2i-sd15-clip-tokens-common-suffix-4 fusion-t2i-sd15-clip-tokens-common-suffix-5 fusion-t2i-sd15-clip-tokens-common-suffix-6 fusion-t2i-sd15-clip-tokens-common-suffix-7 average_suffix fusion-t2i-sd15-clip-tokens-average-suffix-1 fusion-t2i-sd15-clip-tokens-average-suffix-2 fusion-t2i-sd15-clip-tokens-average-suffix-3 fusion-t2i-sd15-clip-tokens-average-suffix-4 fusion-t2i-sd15-clip-tokens-average-suffix-5 fusion-t2i-sd15-clip-tokens-average-suffix-6 fusion-t2i-sd15-clip-tokens-average-suffix-7 rare_suffix fusion-t2i-sd15-clip-tokens-rare-suffix-1 fusion-t2i-sd15-clip-tokens-rare-suffix-2 fusion-t2i-sd15-clip-tokens-rare-suffix-3 fusion-t2i-sd15-clip-tokens-rare-suffix-4 fusion-t2i-sd15-clip-tokens-rare-suffix-5 fusion-t2i-sd15-clip-tokens-rare-suffix-6 fusion-t2i-sd15-clip-tokens-rare-suffix-7 weird_suffix fusion-t2i-sd15-clip-tokens-weird-suffix-1 fusion-t2i-sd15-clip-tokens-weird-suffix-2 fusion-t2i-sd15-clip-tokens-weird-suffix-3 fusion-t2i-sd15-clip-tokens-weird-suffix-4 fusion-t2i-sd15-clip-tokens-weird-suffix-5 fusion-t2i-sd15-clip-tokens-weird-suffix-6 fusion-t2i-sd15-clip-tokens-weird-suffix-7 exotic_suffix fusion-t2i-sd15-clip-tokens-exotic-suffix-1b fusion-t2i-sd15-clip-tokens-exotic-suffix-2 fusion-t2i-sd15-clip-tokens-exotic-suffix-3 fusion-t2i-sd15-clip-tokens-exotic-suffix-4 fusion-t2i-sd15-clip-tokens-exotic-suffix-5 fusion-t2i-sd15-clip-tokens-exotic-suffix-6 fusion-t2i-sd15-clip-tokens-exotic-suffix-7 celebs fusion-t2i-v2-celeb-1 fusion-t2i-v2-celeb-2 fusion-t2i-v2-celeb-3 //fusion-t2i-celebs-1 Old version promptfeatures fusion-t2i-prompt-features-1 fusion-t2i-prompt-features-2 fusion-t2i-prompt-features-3 fusion-t2i-prompt-features-4 fusion-t2i-prompt-features-5 fusion-t2i-prompt-features-6 fusion-t2i-prompt-features-7 fusion-t2i-prompt-features-8 fusion-t2i-prompt-features-9 fusion-t2i-prompt-features-10 fusion-t2i-prompt-features-11 fusion-t2i-prompt-features-12 fusion-t2i-prompt-features-13 fusion-t2i-prompt-features-14 fusion-t2i-prompt-features-15 fusion-t2i-prompt-features-16 fusion-t2i-prompt-features-17 fusion-t2i-prompt-features-18 fusion-t2i-prompt-features-19 fusion-t2i-prompt-features-20 fusion-t2i-prompt-features-21 fusion-t2i-prompt-features-22 fusion-t2i-prompt-features-23 fusion-t2i-prompt-features-24 fusion-t2i-prompt-features-25 fusion-t2i-prompt-features-26 fusion-t2i-prompt-features-27 fusion-t2i-prompt-features-28 fusion-t2i-prompt-features-29 fusion-t2i-prompt-features-30 fusion-t2i-prompt-features-31 fusion-t2i-prompt-features-32 fusion-t2i-prompt-features-33 fusion-t2i-prompt-features-34 nsfwtexts fusion-t2i-nsfw-texting-1 fusion-t2i-nsfw-texting-1 studios fusion-t2i-nsfw-studios-1 fusion-t2i-nsfw-studios-2 fusion-t2i-nsfw-studios-3 fusion-t2i-nsfw-studios-4 fusion-t2i-nsfw-studios-5 fusion-t2i-nsfw-studios-6 fusion-t2i-nsfw-studios-7 fusion-t2i-nsfw-studios-8 fusion-t2i-nsfw-studios-9 fusion-t2i-nsfw-studios-10 fusion-t2i-nsfw-studios-11 fusion-t2i-nsfw-studios-12 fusion-t2i-nsfw-studios-13 fusion-t2i-nsfw-studios-14 fusion-t2i-nsfw-studios-15 fusion-t2i-nsfw-studios-16 perspectives fusion-t2i-perspectives-1 fusion-t2i-perspectives-1 artstyles fusion-t2i-original-artstyles-1 fusion-t2i-original-artstyles-1 e621artists fusion-t2i-e621-artists-1 fusion-t2i-e621-artists-1 gen_bodyfeatures fusion-t2i-bodyfeatures-1 fusion-t2i-bodyfeatures-1 mangart fusion-t2i-manga-artist-1 fusion-t2i-manga-artist-2 //fusion-t2i-manga-artist-3 //fusion-t2i-manga-artist-4 nsfwpromptfeatures fusion-t2i-nsfw-prompt-features-1 fusion-t2i-nsfw-prompt-features-2 fusion-t2i-nsfw-prompt-features-3 fusion-t2i-nsfw-prompt-features-4 fusion-t2i-nsfw-prompt-features-5 fusion-t2i-nsfw-prompt-features-6 fusion-t2i-nsfw-prompt-features-7 fusion-t2i-nsfw-prompt-features-8 fusion-t2i-nsfw-prompt-features-9 fusion-t2i-nsfw-prompt-features-10 fusion-t2i-nsfw-prompt-features-11 fusion-t2i-nsfw-prompt-features-12 fusion-t2i-nsfw-prompt-features-13 fusion-t2i-nsfw-prompt-features-14 fusion-t2i-nsfw-prompt-features-15 gen_names fusion-t2i-nsfw-names-1 fusion-t2i-nsfw-names-2 fusion-t2i-nsfw-names-3 fusion-t2i-nsfw-names-4 fusion-t2i-nsfw-names-5 fusion-t2i-nsfw-names-6 fusion-t2i-nsfw-names-7 fusion-t2i-nsfw-names-8 fusion-t2i-nsfw-names-9 nsfwnews fusion-t2i-fake-nsfw-headlines-1 fusion-t2i-fake-nsfw-headlines-1 tsundere fusion-t2i-tsundere-quotes-1 fusion-t2i-tsundere-quotes-1 ```

knkarthick/dialogsum

knkarthick

--- annotations_creators: - expert-generated language_creators: - expert-generated language: - en license: cc-by-nc-sa-4.0 multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - summarization - text2text-generation - text-generation task_ids: [] pretty_name: DIALOGSum Corpus tags: - dialogue-summary - one-liner-summary - meeting-title - email-subject --- # Dataset Card for DIALOGSum Corpus ## Dataset Description ### Links - **Homepage:** https://aclanthology.org/2021.findings-acl.449 - **Repository:** https://github.com/cylnlp/dialogsum - **Paper:** https://aclanthology.org/2021.findings-acl.449 - **Point of Contact:** https://huggingface.co/knkarthick ### Dataset Summary DialogSum is a large-scale dialogue summarization dataset, consisting of 13,460 (Plus 100 holdout data for topic generation) dialogues with corresponding manually labeled summaries and topics. ### Languages English ## Dataset Structure ### Data Instances DialogSum is a large-scale dialogue summarization dataset, consisting of 13,460 dialogues (+1000 tests) split into train, test and validation. The first instance in the training set: {'id': 'train_0', 'summary': "Mr. Smith's getting a check-up, and Doctor Hawkins advises him to have one every year. Hawkins'll give some information about their classes and medications to help Mr. Smith quit smoking.", 'dialogue': "#Person1#: Hi, Mr. Smith. I'm Doctor Hawkins. Why are you here today?\n#Person2#: I found it would be a good idea to get a check-up.\n#Person1#: Yes, well, you haven't had one for 5 years. You should have one every year.\n#Person2#: I know. I figure as long as there is nothing wrong, why go see the doctor?\n#Person1#: Well, the best way to avoid serious illnesses is to find out about them early. So try to come at least once a year for your own good.\n#Person2#: Ok.\n#Person1#: Let me see here. Your eyes and ears look fine. Take a deep breath, please. Do you smoke, Mr. Smith?\n#Person2#: Yes.\n#Person1#: Smoking is the leading cause of lung cancer and heart disease, you know. You really should quit.\n#Person2#: I've tried hundreds of times, but I just can't seem to kick the habit.\n#Person1#: Well, we have classes and some medications that might help. I'll give you more information before you leave.\n#Person2#: Ok, thanks doctor.", 'topic': "get a check-up} ### Data Fields - dialogue: text of dialogue. - summary: human written summary of the dialogue. - topic: human written topic/one liner of the dialogue. - id: unique file id of an example. ### Data Splits - train: 12460 - val: 500 - test: 1500 - holdout: 100 [Only 3 features: id, dialogue, topic] ## Dataset Creation ### Curation Rationale In paper: We collect dialogue data for DialogSum from three public dialogue corpora, namely Dailydialog (Li et al., 2017), DREAM (Sun et al., 2019) and MuTual (Cui et al., 2019), as well as an English speaking practice website. These datasets contain face-to-face spoken dialogues that cover a wide range of daily-life topics, including schooling, work, medication, shopping, leisure, travel. Most conversations take place between friends, colleagues, and between service providers and customers. Compared with previous datasets, dialogues from DialogSum have distinct characteristics: Under rich real-life scenarios, including more diverse task-oriented scenarios; Have clear communication patterns and intents, which is valuable to serve as summarization sources; Have a reasonable length, which comforts the purpose of automatic summarization. We ask annotators to summarize each dialogue based on the following criteria: Convey the most salient information; Be brief; Preserve important named entities within the conversation; Be written from an observer perspective; Be written in formal language. ### Who are the source language producers? linguists ### Who are the annotators? language experts ## Licensing Information CC BY-NC-SA 4.0 ## Citation Information ``` @inproceedings{chen-etal-2021-dialogsum, title = "{D}ialog{S}um: {A} Real-Life Scenario Dialogue Summarization Dataset", author = "Chen, Yulong and Liu, Yang and Chen, Liang and Zhang, Yue", booktitle = "Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021", month = aug, year = "2021", address = "Online", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2021.findings-acl.449", doi = "10.18653/v1/2021.findings-acl.449", pages = "5062--5074", ``` ## Contributions Thanks to [@cylnlp](https://github.com/cylnlp) for adding this dataset.

HuggingFaceH4/ultrachat_200k

HuggingFaceH4

--- language: - en license: mit size_categories: - 100K<n<1M task_categories: - text-generation pretty_name: UltraChat 200k configs: - config_name: default data_files: - split: train_sft path: data/train_sft-* - split: test_sft path: data/test_sft-* - split: train_gen path: data/train_gen-* - split: test_gen path: data/test_gen-* dataset_info: features: - name: prompt dtype: string - name: prompt_id dtype: string - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train_sft num_bytes: 1397058554 num_examples: 207865 - name: test_sft num_bytes: 154695659 num_examples: 23110 - name: train_gen num_bytes: 1347396812 num_examples: 256032 - name: test_gen num_bytes: 148276089 num_examples: 28304 download_size: 1624049723 dataset_size: 3047427114 --- # Dataset Card for UltraChat 200k ## Dataset Description This is a heavily filtered version of the [UltraChat](https://github.com/thunlp/UltraChat) dataset and was used to train [Zephyr-7B-β](https://huggingface.co/HuggingFaceH4/zephyr-7b-beta), a state of the art 7b chat model. The original datasets consists of 1.4M dialogues generated by ChatGPT and spanning a wide range of topics. To create `UltraChat 200k`, we applied the following logic: - Selection of a subset of data for faster supervised fine tuning. - Truecasing of the dataset, as we observed around 5% of the data contained grammatical errors like "Hello. how are you?" instead of "Hello. How are you?" - Removal of dialogues where the assistant replies with phrases like "I do not have emotions" or "I don't have opinions", even for fact-based prompts that don't involve either. ## Dataset Structure The dataset has four splits, suitable for: * Supervised fine-tuning (`sft`). * Generation ranking (`gen`) via techniques like rejection sampling or PPO. The number of examples per split is shown as follows: | train_sft | test_sft | train_gen | test_gen | |:-------:|:-----------:|:-----:| :-----:| | 207865 | 23110 | 256032 | 28304 | The dataset is stored in parquet format with each entry using the following schema: ``` { "prompt": "Create a fully-developed protagonist who is challenged to survive within a dystopian society under the rule of a tyrant. ...", "messages":[ { "content": "Create a fully-developed protagonist who is challenged to survive within a dystopian society under the rule of a tyrant. ...", "role": "user" }, { "content": "Name: Ava\n\n Ava was just 16 years old when the world as she knew it came crashing down. The government had collapsed, leaving behind a chaotic and lawless society. ...", "role": "assistant" }, { "content": "Wow, Ava's story is so intense and inspiring! Can you provide me with more details. ...", "role": "user" }, { "content": "Certainly! ....", "role": "assistant" }, { "content": "That's really interesting! I would love to hear more...", "role": "user" } { "content": "Certainly! ....", "role": "assistant" }, ], "prompt_id": "d938b65dfe31f05f80eb8572964c6673eddbd68eff3db6bd234d7f1e3b86c2af" } ``` ## Citation If you find this dataset is useful in your work, please cite the original UltraChat dataset: ``` @misc{ding2023enhancing, title={Enhancing Chat Language Models by Scaling High-quality Instructional Conversations}, author={Ning Ding and Yulin Chen and Bokai Xu and Yujia Qin and Zhi Zheng and Shengding Hu and Zhiyuan Liu and Maosong Sun and Bowen Zhou}, year={2023}, eprint={2305.14233}, archivePrefix={arXiv}, primaryClass={cs.CL} } ```

asahi417/seamless-align-enA-zhA.speaker-embedding.hubert-xl

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9475358331 num_examples: 1962 download_size: 9504134241 dataset_size: 9475358331 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9052265145 num_examples: 2031 download_size: 9081911906 dataset_size: 9052265145 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8818322637 num_examples: 1891 download_size: 8846394382 dataset_size: 8818322637 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8694449499 num_examples: 1885 download_size: 8722422676 dataset_size: 8694449499 - config_name: subset_102 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8490046178 num_examples: 1863 download_size: 8516889176 dataset_size: 8490046178 - config_name: subset_103 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8647106885 num_examples: 1861 download_size: 8674999999 dataset_size: 8647106885 - config_name: subset_104 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8534733566 num_examples: 1875 download_size: 8562882733 dataset_size: 8534733566 - config_name: subset_105 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8753738114 num_examples: 1871 download_size: 8781689050 dataset_size: 8753738114 - config_name: subset_106 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8286741426 num_examples: 1865 download_size: 8313205426 dataset_size: 8286741426 - config_name: subset_107 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8325399814 num_examples: 1838 download_size: 8352141658 dataset_size: 8325399814 - config_name: subset_108 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8681207053 num_examples: 1860 download_size: 8709094371 dataset_size: 8681207053 - config_name: subset_109 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8660101738 num_examples: 1866 download_size: 8687993587 dataset_size: 8660101738 - config_name: subset_11 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8694663339 num_examples: 1994 download_size: 8723170105 dataset_size: 8694663339 - 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name: train num_bytes: 8615987524 num_examples: 1845 download_size: 8643384072 dataset_size: 8615987524 - config_name: subset_112 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8446424009 num_examples: 1844 download_size: 8472296093 dataset_size: 8446424009 - config_name: subset_113 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - 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name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8444813376 num_examples: 1823 download_size: 8468814399 dataset_size: 8444813376 - config_name: subset_12 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: zhA.id dtype: string - name: zhA.laser_score dtype: float64 - name: zhA.audio.speaker_embedding sequence: float32 - name: zhA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8899375434 num_examples: 2034 download_size: 8927972812 dataset_size: 8899375434 - config_name: subset_120 features: - 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stanfordnlp/sst2

stanfordnlp

--- annotations_creators: - crowdsourced language_creators: - found language: - en license: - unknown multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-classification task_ids: - sentiment-classification paperswithcode_id: sst pretty_name: Stanford Sentiment Treebank v2 dataset_info: features: - name: idx dtype: int32 - name: sentence dtype: string - name: label dtype: class_label: names: '0': negative '1': positive splits: - name: train num_bytes: 4681603 num_examples: 67349 - name: validation num_bytes: 106252 num_examples: 872 - name: test num_bytes: 216640 num_examples: 1821 download_size: 3331058 dataset_size: 5004495 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* - split: test path: data/test-* --- # Dataset Card for [Dataset Name] ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://nlp.stanford.edu/sentiment/ - **Repository:** - **Paper:** [Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank](https://www.aclweb.org/anthology/D13-1170/) - **Leaderboard:** - **Point of Contact:** ### Dataset Summary The Stanford Sentiment Treebank is a corpus with fully labeled parse trees that allows for a complete analysis of the compositional effects of sentiment in language. The corpus is based on the dataset introduced by Pang and Lee (2005) and consists of 11,855 single sentences extracted from movie reviews. It was parsed with the Stanford parser and includes a total of 215,154 unique phrases from those parse trees, each annotated by 3 human judges. Binary classification experiments on full sentences (negative or somewhat negative vs somewhat positive or positive with neutral sentences discarded) refer to the dataset as SST-2 or SST binary. ### Supported Tasks and Leaderboards - `sentiment-classification` ### Languages The text in the dataset is in English (`en`). ## Dataset Structure ### Data Instances ``` {'idx': 0, 'sentence': 'hide new secretions from the parental units ', 'label': 0} ``` ### Data Fields - `idx`: Monotonically increasing index ID. - `sentence`: Complete sentence expressing an opinion about a film. - `label`: Sentiment of the opinion, either "negative" (0) or positive (1). The test set labels are hidden (-1). ### Data Splits | | train | validation | test | |--------------------|---------:|-----------:|-----:| | Number of examples | 67349 | 872 | 1821 | ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? Rotten Tomatoes reviewers. ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Unknown. ### Citation Information ```bibtex @inproceedings{socher-etal-2013-recursive, title = "Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank", author = "Socher, Richard and Perelygin, Alex and Wu, Jean and Chuang, Jason and Manning, Christopher D. and Ng, Andrew and Potts, Christopher", booktitle = "Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing", month = oct, year = "2013", address = "Seattle, Washington, USA", publisher = "Association for Computational Linguistics", url = "https://www.aclweb.org/anthology/D13-1170", pages = "1631--1642", } ``` ### Contributions Thanks to [@albertvillanova](https://github.com/albertvillanova) for adding this dataset.

regent-research/regent-subset-of-jat-dataset-tokenized

regent-research

--- dataset_info: - config_name: atari-alien_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 1905456 num_examples: 22684 download_size: 2088245 dataset_size: 1905456 - config_name: atari-amidar_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32810168 num_examples: 100031 download_size: 11019541 dataset_size: 32810168 - config_name: atari-amidar_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 23046343776 num_examples: 3142 download_size: 256637379 dataset_size: 23046343776 - config_name: atari-assault_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32806232 num_examples: 100019 download_size: 14121737 dataset_size: 32806232 - config_name: atari-assault_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 22972994496 num_examples: 3132 download_size: 186535975 dataset_size: 22972994496 - config_name: atari-asterix_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32806560 num_examples: 100020 download_size: 11902934 dataset_size: 32806560 - config_name: atari-asterix_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 23332405968 num_examples: 3181 download_size: 188517858 dataset_size: 23332405968 - config_name: atari-asteroids_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32807216 num_examples: 100022 download_size: 13899826 dataset_size: 32807216 - config_name: atari-asteroids_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 22936319856 num_examples: 3127 download_size: 202442660 dataset_size: 22936319856 - config_name: atari-atlantis_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32801640 num_examples: 100005 download_size: 13128838 dataset_size: 32801640 - config_name: atari-atlantis_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 22943654784 num_examples: 3128 download_size: 206794180 dataset_size: 22943654784 - config_name: atari-bankheist_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32806888 num_examples: 100021 download_size: 13754178 dataset_size: 32806888 - config_name: atari-bankheist_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 23149032768 num_examples: 3156 download_size: 307236770 dataset_size: 23149032768 - config_name: atari-battlezone_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800984 num_examples: 100003 download_size: 15918969 dataset_size: 32800984 - config_name: atari-battlezone_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 23002334208 num_examples: 3136 download_size: 247618279 dataset_size: 23002334208 - config_name: atari-beamrider_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32806232 num_examples: 100019 download_size: 16063964 dataset_size: 32806232 - config_name: atari-beamrider_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 22965659568 num_examples: 3131 download_size: 224067669 dataset_size: 22965659568 - config_name: atari-berzerk_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32803936 num_examples: 100012 download_size: 11678744 dataset_size: 32803936 - config_name: atari-berzerk_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - name: train num_bytes: 22936319856 num_examples: 3127 download_size: 204431627 dataset_size: 22936319856 - config_name: atari-bowling_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32801968 num_examples: 100006 download_size: 7354865 dataset_size: 32801968 - config_name: atari-bowling_subset features: - name: image_observations sequence: sequence: sequence: sequence: float64 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 - name: embeddings_resnet18_512 sequence: sequence: float32 splits: - 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config_name: babyai-mini-boss-level_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32861664 num_examples: 100188 download_size: 8146530 dataset_size: 32861664 - config_name: babyai-mini-boss-level_subset features: - name: discrete_observations sequence: sequence: int32 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 splits: - name: train num_bytes: 1828968804 num_examples: 8307 download_size: 10435667 dataset_size: 1828968804 - config_name: babyai-move-two-across-s8n9_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32819680 num_examples: 100060 download_size: 6974780 dataset_size: 32819680 - config_name: babyai-move-two-across-s8n9_subset features: - name: discrete_observations sequence: sequence: int32 - name: discrete_actions sequence: int32 - name: rewards sequence: float32 splits: - name: train num_bytes: 542944152 num_examples: 2466 download_size: 6570582 dataset_size: 542944152 - 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name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 4082529 dataset_size: 47116000 - config_name: metaworld-door-close_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13743650 dataset_size: 32800000 - config_name: metaworld-door-close_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 8698806 dataset_size: 47116000 - config_name: metaworld-door-lock_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 840000 num_examples: 10000 download_size: 776743 dataset_size: 840000 - config_name: metaworld-door-open_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13781189 dataset_size: 32800000 - config_name: metaworld-door-open_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 7983276 dataset_size: 47116000 - config_name: metaworld-door-unlock_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 840000 num_examples: 10000 download_size: 829555 dataset_size: 840000 - config_name: metaworld-drawer-close_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13903693 dataset_size: 32800000 - config_name: metaworld-drawer-close_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5764071 dataset_size: 47116000 - config_name: metaworld-drawer-open_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12036502 dataset_size: 32800000 - config_name: metaworld-drawer-open_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5484434 dataset_size: 47116000 - config_name: metaworld-faucet-close_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 14148656 dataset_size: 32800000 - config_name: metaworld-faucet-close_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5086095 dataset_size: 47116000 - config_name: metaworld-faucet-open_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 14300852 dataset_size: 32800000 - config_name: metaworld-faucet-open_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5497182 dataset_size: 47116000 - config_name: metaworld-hammer_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13491757 dataset_size: 32800000 - config_name: metaworld-hammer_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 10062439 dataset_size: 47116000 - config_name: metaworld-hand-insert_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 840000 num_examples: 10000 download_size: 1050789 dataset_size: 840000 - config_name: metaworld-handle-press-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12555014 dataset_size: 32800000 - config_name: metaworld-handle-press-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5880675 dataset_size: 47116000 - config_name: metaworld-handle-press_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13473313 dataset_size: 32800000 - config_name: metaworld-handle-press_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5879237 dataset_size: 47116000 - config_name: metaworld-handle-pull-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13576934 dataset_size: 32800000 - config_name: metaworld-handle-pull-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 6737064 dataset_size: 47116000 - config_name: metaworld-handle-pull_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12046278 dataset_size: 32800000 - config_name: metaworld-handle-pull_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 6896646 dataset_size: 47116000 - config_name: metaworld-lever-pull_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12827517 dataset_size: 32800000 - config_name: metaworld-lever-pull_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9568802 dataset_size: 47116000 - config_name: metaworld-peg-insert-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13057268 dataset_size: 32800000 - config_name: metaworld-peg-insert-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 8714100 dataset_size: 47116000 - config_name: metaworld-peg-unplug-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13163866 dataset_size: 32800000 - config_name: metaworld-peg-unplug-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9726674 dataset_size: 47116000 - config_name: metaworld-pick-out-of-hole_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 1376243 dataset_size: 32800000 - config_name: metaworld-pick-out-of-hole_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 1419339 dataset_size: 47116000 - config_name: metaworld-pick-place-wall_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13636756 dataset_size: 32800000 - config_name: metaworld-pick-place-wall_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9760537 dataset_size: 47116000 - config_name: metaworld-pick-place_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13638935 dataset_size: 32800000 - config_name: metaworld-pick-place_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 10013159 dataset_size: 47116000 - config_name: metaworld-plate-slide-back-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 1365777 dataset_size: 32800000 - config_name: metaworld-plate-slide-back-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 1936719 dataset_size: 47116000 - config_name: metaworld-plate-slide-back_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 1372778 dataset_size: 32800000 - config_name: metaworld-plate-slide-back_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 2568887 dataset_size: 47116000 - config_name: metaworld-plate-slide-side_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 9706526 dataset_size: 32800000 - config_name: metaworld-plate-slide-side_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 6041762 dataset_size: 47116000 - config_name: metaworld-plate-slide_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 9787720 dataset_size: 32800000 - config_name: metaworld-plate-slide_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 6512808 dataset_size: 47116000 - config_name: metaworld-push-back_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 14075602 dataset_size: 32800000 - config_name: metaworld-push-back_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 7550247 dataset_size: 47116000 - config_name: metaworld-push-wall_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13592428 dataset_size: 32800000 - config_name: metaworld-push-wall_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 8970793 dataset_size: 47116000 - config_name: metaworld-push_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13341527 dataset_size: 32800000 - config_name: metaworld-push_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9427900 dataset_size: 47116000 - config_name: metaworld-reach-wall_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12733205 dataset_size: 32800000 - config_name: metaworld-reach-wall_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9731627 dataset_size: 47116000 - config_name: metaworld-reach_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12106144 dataset_size: 32800000 - config_name: metaworld-reach_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9563337 dataset_size: 47116000 - config_name: metaworld-shelf-place_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13046597 dataset_size: 32800000 - config_name: metaworld-shelf-place_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 8068065 dataset_size: 47116000 - config_name: metaworld-soccer_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 11954933 dataset_size: 32800000 - config_name: metaworld-soccer_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9009300 dataset_size: 47116000 - config_name: metaworld-stick-pull_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13346574 dataset_size: 32800000 - config_name: metaworld-stick-pull_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9654361 dataset_size: 47116000 - config_name: metaworld-stick-push_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13868467 dataset_size: 32800000 - config_name: metaworld-stick-push_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9420722 dataset_size: 47116000 - config_name: metaworld-sweep-into_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13471306 dataset_size: 32800000 - config_name: metaworld-sweep-into_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 7656262 dataset_size: 47116000 - config_name: metaworld-sweep_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13966344 dataset_size: 32800000 - config_name: metaworld-sweep_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 9333916 dataset_size: 47116000 - config_name: metaworld-window-close_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12562521 dataset_size: 32800000 - config_name: metaworld-window-close_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5405410 dataset_size: 47116000 - config_name: metaworld-window-open_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12270843 dataset_size: 32800000 - config_name: metaworld-window-open_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 47116000 num_examples: 1000 download_size: 5455606 dataset_size: 47116000 - config_name: mujoco-ant_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32847232 num_examples: 100144 download_size: 16107573 dataset_size: 32847232 - config_name: mujoco-ant_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 15608524 num_examples: 401 download_size: 16185601 dataset_size: 15608524 - config_name: mujoco-doublependulum_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32805248 num_examples: 100016 download_size: 16102270 dataset_size: 32805248 - config_name: mujoco-doublependulum_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 6164172 num_examples: 401 download_size: 4960978 dataset_size: 6164172 - config_name: mujoco-halfcheetah_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 8400000 num_examples: 100000 download_size: 11373374 dataset_size: 8400000 - config_name: mujoco-hopper_newdata features: - name: distances sequence: float32 splits: - name: train num_bytes: 3834768 num_examples: 45652 download_size: 5110310 dataset_size: 3834768 - config_name: mujoco-humanoid_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32808200 num_examples: 100025 download_size: 16122991 dataset_size: 32808200 - config_name: mujoco-humanoid_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 168289140 num_examples: 415 download_size: 116298243 dataset_size: 168289140 - config_name: mujoco-pendulum_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32806888 num_examples: 100021 download_size: 15694433 dataset_size: 32806888 - config_name: mujoco-pendulum_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 4060980 num_examples: 495 download_size: 3083276 dataset_size: 4060980 - config_name: mujoco-pusher_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 13887459 dataset_size: 32800000 - config_name: mujoco-pusher_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 33804000 num_examples: 1000 download_size: 13463910 dataset_size: 33804000 - config_name: mujoco-reacher_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 12795397 dataset_size: 32800000 - config_name: mujoco-reacher_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 32792000 num_examples: 2000 download_size: 7687471 dataset_size: 32792000 - config_name: mujoco-standup_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 16032984 dataset_size: 32800000 - config_name: mujoco-standup_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 162206400 num_examples: 400 download_size: 117589700 dataset_size: 162206400 - config_name: mujoco-swimmer_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32800000 num_examples: 100000 download_size: 15858902 dataset_size: 32800000 - config_name: mujoco-swimmer_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 5329600 num_examples: 400 download_size: 5733100 dataset_size: 5329600 - config_name: mujoco-walker_newdata features: - name: distances sequence: float32 - name: indices sequence: sequence: int32 splits: - name: train num_bytes: 32807872 num_examples: 100024 download_size: 15920611 dataset_size: 32807872 - config_name: mujoco-walker_subset features: - name: continuous_observations sequence: sequence: float32 - name: continuous_actions sequence: sequence: float32 - name: rewards sequence: float32 splits: - name: train num_bytes: 10840852 num_examples: 407 download_size: 11101553 dataset_size: 10840852 configs: - config_name: atari-alien_newdata data_files: - split: train path: atari-alien_newdata/train-* - config_name: atari-amidar_newdata data_files: - split: train path: atari-amidar_newdata/train-* - config_name: atari-amidar_subset data_files: - split: train path: atari-amidar_subset/train-* - config_name: atari-assault_newdata data_files: - split: train path: atari-assault_newdata/train-* - config_name: atari-assault_subset data_files: - split: train path: atari-assault_subset/train-* - config_name: atari-asterix_newdata data_files: - split: train path: atari-asterix_newdata/train-* - config_name: atari-asterix_subset data_files: - split: train path: atari-asterix_subset/train-* - config_name: atari-asteroids_newdata data_files: - split: train path: atari-asteroids_newdata/train-* - config_name: atari-asteroids_subset data_files: - split: train path: atari-asteroids_subset/train-* - config_name: atari-atlantis_newdata data_files: - split: train path: atari-atlantis_newdata/train-* - config_name: atari-atlantis_subset data_files: - split: train path: atari-atlantis_subset/train-* - config_name: atari-bankheist_newdata data_files: - split: train path: atari-bankheist_newdata/train-* - config_name: atari-bankheist_subset data_files: - split: train path: atari-bankheist_subset/train-* - config_name: atari-battlezone_newdata data_files: - split: train path: atari-battlezone_newdata/train-* - config_name: atari-battlezone_subset data_files: - split: train path: atari-battlezone_subset/train-* - config_name: atari-beamrider_newdata data_files: - split: train path: atari-beamrider_newdata/train-* - config_name: atari-beamrider_subset data_files: - split: train path: atari-beamrider_subset/train-* - config_name: atari-berzerk_newdata data_files: - split: train path: atari-berzerk_newdata/train-* - config_name: atari-berzerk_subset data_files: - split: train path: atari-berzerk_subset/train-* - config_name: atari-bowling_newdata data_files: - split: train path: atari-bowling_newdata/train-* - config_name: atari-bowling_subset data_files: - split: train path: atari-bowling_subset/train-* - config_name: atari-boxing_newdata data_files: - split: train path: atari-boxing_newdata/train-* - config_name: atari-boxing_subset data_files: - split: train path: atari-boxing_subset/train-* - config_name: atari-breakout_newdata data_files: - split: train path: atari-breakout_newdata/train-* - config_name: atari-breakout_subset data_files: - split: train path: atari-breakout_subset/train-* - config_name: atari-centipede_newdata data_files: - split: train path: atari-centipede_newdata/train-* - config_name: atari-centipede_subset data_files: - split: train path: atari-centipede_subset/train-* - config_name: atari-choppercommand_newdata data_files: - split: train path: atari-choppercommand_newdata/train-* - config_name: atari-choppercommand_subset data_files: - split: train path: atari-choppercommand_subset/train-* - config_name: atari-crazyclimber_newdata data_files: - split: train path: atari-crazyclimber_newdata/train-* - config_name: atari-crazyclimber_subset data_files: - split: train path: atari-crazyclimber_subset/train-* - config_name: atari-defender_newdata data_files: - split: train path: atari-defender_newdata/train-* - config_name: atari-defender_subset data_files: - split: train path: atari-defender_subset/train-* - config_name: atari-demonattack_newdata data_files: - split: train path: atari-demonattack_newdata/train-* - config_name: atari-demonattack_subset data_files: - split: train path: atari-demonattack_subset/train-* - config_name: atari-doubledunk_newdata data_files: - split: train path: atari-doubledunk_newdata/train-* - config_name: atari-doubledunk_subset data_files: - split: train path: atari-doubledunk_subset/train-* - config_name: atari-enduro_newdata data_files: - split: train path: atari-enduro_newdata/train-* - config_name: atari-enduro_subset data_files: - split: train path: atari-enduro_subset/train-* - config_name: atari-fishingderby_newdata data_files: - split: train path: atari-fishingderby_newdata/train-* - config_name: atari-fishingderby_subset data_files: - split: train path: atari-fishingderby_subset/train-* - config_name: atari-freeway_newdata data_files: - split: train path: atari-freeway_newdata/train-* - config_name: atari-freeway_subset data_files: - split: train path: atari-freeway_subset/train-* - config_name: atari-frostbite_newdata data_files: - split: train path: atari-frostbite_newdata/train-* - config_name: atari-frostbite_subset data_files: - split: train path: atari-frostbite_subset/train-* - config_name: atari-gopher_newdata data_files: - split: train path: atari-gopher_newdata/train-* - config_name: atari-gopher_subset data_files: - split: train path: atari-gopher_subset/train-* - config_name: atari-gravitar_newdata data_files: - split: train path: atari-gravitar_newdata/train-* - config_name: atari-gravitar_subset data_files: - split: train path: atari-gravitar_subset/train-* - config_name: atari-hero_newdata data_files: - split: train path: atari-hero_newdata/train-* - config_name: atari-hero_subset data_files: - split: train path: atari-hero_subset/train-* - config_name: atari-icehockey_newdata data_files: - split: train path: atari-icehockey_newdata/train-* - config_name: atari-icehockey_subset data_files: - split: train path: atari-icehockey_subset/train-* - config_name: atari-jamesbond_newdata data_files: - split: train path: atari-jamesbond_newdata/train-* - config_name: atari-jamesbond_subset data_files: - split: train path: atari-jamesbond_subset/train-* - config_name: atari-kangaroo_newdata data_files: - split: train path: atari-kangaroo_newdata/train-* - config_name: atari-kangaroo_subset data_files: - split: train path: atari-kangaroo_subset/train-* - config_name: atari-krull_newdata data_files: - split: train path: atari-krull_newdata/train-* - config_name: atari-krull_subset data_files: - split: train path: atari-krull_subset/train-* - config_name: atari-kungfumaster_newdata data_files: - split: train path: atari-kungfumaster_newdata/train-* - config_name: atari-kungfumaster_subset data_files: - split: train path: atari-kungfumaster_subset/train-* - config_name: atari-montezumarevenge_newdata data_files: - split: train path: atari-montezumarevenge_newdata/train-* - config_name: atari-montezumarevenge_subset data_files: - split: train path: atari-montezumarevenge_subset/train-* - config_name: atari-mspacman_newdata data_files: - split: train path: atari-mspacman_newdata/train-* - config_name: atari-namethisgame_newdata data_files: - split: train path: atari-namethisgame_newdata/train-* - config_name: atari-namethisgame_subset data_files: - split: train path: atari-namethisgame_subset/train-* - config_name: atari-phoenix_newdata data_files: - split: train path: atari-phoenix_newdata/train-* - config_name: atari-phoenix_subset data_files: - split: train path: atari-phoenix_subset/train-* - config_name: atari-pitfall_newdata data_files: - split: train path: atari-pitfall_newdata/train-* - config_name: atari-pitfall_subset data_files: - split: train path: atari-pitfall_subset/train-* - config_name: atari-pong_newdata data_files: - split: train path: atari-pong_newdata/train-* - config_name: atari-privateeye_newdata data_files: - split: train path: atari-privateeye_newdata/train-* - config_name: atari-privateeye_subset data_files: - split: train path: atari-privateeye_subset/train-* - config_name: atari-qbert_newdata data_files: - split: train path: atari-qbert_newdata/train-* - config_name: atari-qbert_subset data_files: - split: train path: atari-qbert_subset/train-* - config_name: atari-riverraid_newdata data_files: - split: train path: atari-riverraid_newdata/train-* - config_name: atari-riverraid_subset data_files: - split: train path: atari-riverraid_subset/train-* - config_name: atari-roadrunner_newdata data_files: - split: train path: atari-roadrunner_newdata/train-* - config_name: atari-roadrunner_subset data_files: - split: train path: atari-roadrunner_subset/train-* - config_name: atari-robotank_newdata data_files: - split: train path: atari-robotank_newdata/train-* - config_name: atari-robotank_subset data_files: - split: train path: atari-robotank_subset/train-* - config_name: atari-seaquest_newdata data_files: - split: train path: atari-seaquest_newdata/train-* - config_name: atari-seaquest_subset data_files: - split: train path: atari-seaquest_subset/train-* - config_name: atari-skiing_newdata data_files: - split: train path: atari-skiing_newdata/train-* - config_name: atari-skiing_subset data_files: - split: train path: atari-skiing_subset/train-* - config_name: atari-solaris_newdata data_files: - split: train path: atari-solaris_newdata/train-* - config_name: atari-solaris_subset data_files: - split: train path: atari-solaris_subset/train-* - config_name: atari-spaceinvaders_newdata data_files: - split: train path: atari-spaceinvaders_newdata/train-* - config_name: atari-stargunner_newdata data_files: - split: train path: atari-stargunner_newdata/train-* - config_name: atari-surround_newdata data_files: - split: train path: atari-surround_newdata/train-* - config_name: atari-surround_subset data_files: - split: train path: atari-surround_subset/train-* - config_name: atari-tennis_newdata data_files: - split: train path: atari-tennis_newdata/train-* - config_name: atari-tennis_subset data_files: - split: train path: atari-tennis_subset/train-* - config_name: atari-timepilot_newdata data_files: - split: train path: atari-timepilot_newdata/train-* - config_name: atari-timepilot_subset data_files: - split: train path: atari-timepilot_subset/train-* - config_name: atari-tutankham_newdata data_files: - split: train path: atari-tutankham_newdata/train-* - config_name: atari-tutankham_subset data_files: - split: train path: atari-tutankham_subset/train-* - config_name: atari-upndown_newdata data_files: - split: train path: atari-upndown_newdata/train-* - config_name: atari-upndown_subset data_files: - split: train path: atari-upndown_subset/train-* - config_name: atari-venture_newdata data_files: - split: train path: atari-venture_newdata/train-* - config_name: atari-venture_subset data_files: - split: train path: atari-venture_subset/train-* - config_name: atari-videopinball_newdata data_files: - split: train path: atari-videopinball_newdata/train-* - config_name: atari-videopinball_subset data_files: - split: train path: atari-videopinball_subset/train-* - config_name: atari-wizardofwor_newdata data_files: - split: train path: atari-wizardofwor_newdata/train-* - config_name: atari-wizardofwor_subset data_files: - split: train path: atari-wizardofwor_subset/train-* - config_name: atari-yarsrevenge_newdata data_files: - split: train path: atari-yarsrevenge_newdata/train-* - config_name: atari-yarsrevenge_subset data_files: - split: train path: atari-yarsrevenge_subset/train-* - config_name: atari-zaxxon_newdata data_files: - split: train path: atari-zaxxon_newdata/train-* - config_name: atari-zaxxon_subset data_files: - split: train path: atari-zaxxon_subset/train-* - config_name: babyai-action-obj-door_newdata data_files: - split: train path: babyai-action-obj-door_newdata/train-* - config_name: babyai-action-obj-door_subset data_files: - split: train path: babyai-action-obj-door_subset/train-* - config_name: babyai-blocked-unlock-pickup_newdata data_files: - split: train path: babyai-blocked-unlock-pickup_newdata/train-* - config_name: babyai-blocked-unlock-pickup_subset data_files: - split: train path: babyai-blocked-unlock-pickup_subset/train-* - config_name: babyai-boss-level-no-unlock_newdata data_files: - split: train path: babyai-boss-level-no-unlock_newdata/train-* - config_name: babyai-boss-level-no-unlock_subset data_files: - split: train path: babyai-boss-level-no-unlock_subset/train-* - config_name: babyai-boss-level_newdata data_files: - split: train path: babyai-boss-level_newdata/train-* - config_name: babyai-boss-level_subset data_files: - split: train path: babyai-boss-level_subset/train-* - config_name: babyai-find-obj-s5_newdata data_files: - split: train path: babyai-find-obj-s5_newdata/train-* - config_name: babyai-find-obj-s5_subset data_files: - split: train path: babyai-find-obj-s5_subset/train-* - config_name: babyai-go-to-door_newdata data_files: - split: train path: babyai-go-to-door_newdata/train-* - config_name: babyai-go-to-door_subset data_files: - split: train path: babyai-go-to-door_subset/train-* - config_name: babyai-go-to-imp-unlock_newdata data_files: - split: train path: babyai-go-to-imp-unlock_newdata/train-* - config_name: babyai-go-to-imp-unlock_subset data_files: - split: train path: babyai-go-to-imp-unlock_subset/train-* - config_name: babyai-go-to-local_newdata data_files: - split: train path: babyai-go-to-local_newdata/train-* - config_name: babyai-go-to-local_subset data_files: - split: train path: babyai-go-to-local_subset/train-* - config_name: babyai-go-to-obj-door_newdata data_files: - split: train path: babyai-go-to-obj-door_newdata/train-* - config_name: babyai-go-to-obj-door_subset data_files: - split: train path: babyai-go-to-obj-door_subset/train-* - config_name: babyai-go-to-obj_newdata data_files: - split: train path: babyai-go-to-obj_newdata/train-* - config_name: babyai-go-to-obj_subset data_files: - split: train path: babyai-go-to-obj_subset/train-* - config_name: babyai-go-to-red-ball-grey_newdata data_files: - split: train path: babyai-go-to-red-ball-grey_newdata/train-* - config_name: babyai-go-to-red-ball-grey_subset data_files: - split: train path: babyai-go-to-red-ball-grey_subset/train-* - config_name: babyai-go-to-red-ball-no-dists_newdata data_files: - split: train path: babyai-go-to-red-ball-no-dists_newdata/train-* - config_name: babyai-go-to-red-ball-no-dists_subset data_files: - split: train path: babyai-go-to-red-ball-no-dists_subset/train-* - config_name: babyai-go-to-red-ball_newdata data_files: - split: train path: babyai-go-to-red-ball_newdata/train-* - config_name: babyai-go-to-red-ball_subset data_files: - split: train path: babyai-go-to-red-ball_subset/train-* - config_name: babyai-go-to-red-blue-ball_newdata data_files: - split: train path: babyai-go-to-red-blue-ball_newdata/train-* - config_name: babyai-go-to-red-blue-ball_subset data_files: - split: train path: babyai-go-to-red-blue-ball_subset/train-* - config_name: babyai-go-to-seq_newdata data_files: - split: train path: babyai-go-to-seq_newdata/train-* - config_name: babyai-go-to-seq_subset data_files: - split: train path: babyai-go-to-seq_subset/train-* - config_name: babyai-go-to_newdata data_files: - split: train path: babyai-go-to_newdata/train-* - config_name: babyai-go-to_subset data_files: - split: train path: babyai-go-to_subset/train-* - config_name: babyai-key-corridor_newdata data_files: - split: train path: babyai-key-corridor_newdata/train-* - config_name: babyai-key-corridor_subset data_files: - split: train path: babyai-key-corridor_subset/train-* - config_name: babyai-mini-boss-level_newdata data_files: - split: train path: babyai-mini-boss-level_newdata/train-* - config_name: babyai-mini-boss-level_subset data_files: - split: train path: babyai-mini-boss-level_subset/train-* - config_name: babyai-move-two-across-s8n9_newdata data_files: - split: train path: babyai-move-two-across-s8n9_newdata/train-* - config_name: babyai-move-two-across-s8n9_subset data_files: - split: train path: babyai-move-two-across-s8n9_subset/train-* - config_name: babyai-one-room-s8_newdata data_files: - split: train path: babyai-one-room-s8_newdata/train-* - config_name: babyai-one-room-s8_subset data_files: - split: train path: babyai-one-room-s8_subset/train-* - config_name: babyai-open-door_newdata data_files: - split: train path: babyai-open-door_newdata/train-* - config_name: babyai-open-door_subset data_files: - split: train path: babyai-open-door_subset/train-* - config_name: babyai-open-doors-order-n4_newdata data_files: - split: train path: babyai-open-doors-order-n4_newdata/train-* - config_name: babyai-open-doors-order-n4_subset data_files: - split: train path: babyai-open-doors-order-n4_subset/train-* - config_name: babyai-open-red-door_newdata data_files: - split: train path: babyai-open-red-door_newdata/train-* - config_name: babyai-open-red-door_subset data_files: - split: train path: babyai-open-red-door_subset/train-* - config_name: babyai-open-two-doors_newdata data_files: - split: train path: babyai-open-two-doors_newdata/train-* - config_name: babyai-open-two-doors_subset data_files: - split: train path: babyai-open-two-doors_subset/train-* - config_name: babyai-open_newdata data_files: - split: train path: babyai-open_newdata/train-* - config_name: babyai-open_subset data_files: - split: train path: babyai-open_subset/train-* - config_name: babyai-pickup-above_newdata data_files: - split: train path: babyai-pickup-above_newdata/train-* - config_name: babyai-pickup-above_subset data_files: - split: train path: babyai-pickup-above_subset/train-* - config_name: babyai-pickup-dist_newdata data_files: - split: train path: babyai-pickup-dist_newdata/train-* - config_name: babyai-pickup-dist_subset data_files: - split: train path: babyai-pickup-dist_subset/train-* - config_name: babyai-pickup-loc_newdata data_files: - split: train path: babyai-pickup-loc_newdata/train-* - config_name: babyai-pickup-loc_subset data_files: - split: train path: babyai-pickup-loc_subset/train-* - config_name: babyai-pickup_newdata data_files: - split: train path: babyai-pickup_newdata/train-* - config_name: babyai-pickup_subset data_files: - split: train path: babyai-pickup_subset/train-* - config_name: babyai-put-next-local_newdata data_files: - split: train path: babyai-put-next-local_newdata/train-* - config_name: babyai-put-next-local_subset data_files: - split: train path: babyai-put-next-local_subset/train-* - config_name: babyai-put-next_newdata data_files: - split: train path: babyai-put-next_newdata/train-* - config_name: babyai-put-next_subset data_files: - split: train path: babyai-put-next_subset/train-* - config_name: babyai-synth-loc_newdata data_files: - split: train path: babyai-synth-loc_newdata/train-* - config_name: babyai-synth-loc_subset data_files: - split: train path: babyai-synth-loc_subset/train-* - config_name: babyai-synth-seq_newdata data_files: - split: train path: babyai-synth-seq_newdata/train-* - config_name: babyai-synth-seq_subset data_files: - split: train path: babyai-synth-seq_subset/train-* - config_name: babyai-synth_newdata data_files: - split: train path: babyai-synth_newdata/train-* - config_name: babyai-synth_subset data_files: - split: train path: babyai-synth_subset/train-* - config_name: babyai-unblock-pickup_newdata data_files: - split: train path: babyai-unblock-pickup_newdata/train-* - config_name: babyai-unblock-pickup_subset data_files: - split: train path: babyai-unblock-pickup_subset/train-* - config_name: babyai-unlock-local_newdata data_files: - split: train path: babyai-unlock-local_newdata/train-* - config_name: babyai-unlock-local_subset data_files: - split: train path: babyai-unlock-local_subset/train-* - config_name: babyai-unlock-pickup_newdata data_files: - split: train path: babyai-unlock-pickup_newdata/train-* - config_name: babyai-unlock-pickup_subset data_files: - split: train path: babyai-unlock-pickup_subset/train-* - config_name: babyai-unlock-to-unlock_newdata data_files: - split: train path: babyai-unlock-to-unlock_newdata/train-* - config_name: babyai-unlock-to-unlock_subset data_files: - split: train path: babyai-unlock-to-unlock_subset/train-* - config_name: babyai-unlock_newdata data_files: - split: train path: babyai-unlock_newdata/train-* - config_name: babyai-unlock_subset data_files: - split: train path: babyai-unlock_subset/train-* - config_name: metaworld-assembly_newdata data_files: - split: train path: metaworld-assembly_newdata/train-* - config_name: metaworld-assembly_subset data_files: - split: train path: metaworld-assembly_subset/train-* - config_name: metaworld-basketball_newdata data_files: - split: train path: metaworld-basketball_newdata/train-* - config_name: metaworld-basketball_subset data_files: - split: train path: metaworld-basketball_subset/train-* - config_name: metaworld-bin-picking_newdata data_files: - split: train path: metaworld-bin-picking_newdata/train-* - config_name: metaworld-box-close_newdata data_files: - split: train path: metaworld-box-close_newdata/train-* - config_name: metaworld-button-press-topdown-wall_newdata data_files: - split: train path: metaworld-button-press-topdown-wall_newdata/train-* - config_name: metaworld-button-press-topdown-wall_subset data_files: - split: train path: metaworld-button-press-topdown-wall_subset/train-* - config_name: metaworld-button-press-topdown_newdata data_files: - split: train path: metaworld-button-press-topdown_newdata/train-* - config_name: metaworld-button-press-topdown_subset data_files: - split: train path: metaworld-button-press-topdown_subset/train-* - config_name: metaworld-button-press-wall_newdata data_files: - split: train path: metaworld-button-press-wall_newdata/train-* - config_name: metaworld-button-press-wall_subset data_files: - split: train path: metaworld-button-press-wall_subset/train-* - config_name: metaworld-button-press_newdata data_files: - split: train path: metaworld-button-press_newdata/train-* - config_name: metaworld-button-press_subset data_files: - split: train path: metaworld-button-press_subset/train-* - config_name: metaworld-coffee-button_newdata data_files: - split: train path: metaworld-coffee-button_newdata/train-* - config_name: metaworld-coffee-button_subset data_files: - split: train path: metaworld-coffee-button_subset/train-* - config_name: metaworld-coffee-pull_newdata data_files: - split: train path: metaworld-coffee-pull_newdata/train-* - config_name: metaworld-coffee-pull_subset data_files: - split: train path: metaworld-coffee-pull_subset/train-* - config_name: metaworld-coffee-push_newdata data_files: - split: train path: metaworld-coffee-push_newdata/train-* - config_name: metaworld-coffee-push_subset data_files: - split: train path: metaworld-coffee-push_subset/train-* - config_name: metaworld-dial-turn_newdata data_files: - split: train path: metaworld-dial-turn_newdata/train-* - config_name: metaworld-dial-turn_subset data_files: - split: train path: metaworld-dial-turn_subset/train-* - config_name: metaworld-disassemble_newdata data_files: - split: train path: metaworld-disassemble_newdata/train-* - config_name: metaworld-disassemble_subset data_files: - split: train path: metaworld-disassemble_subset/train-* - config_name: metaworld-door-close_newdata data_files: - split: train path: metaworld-door-close_newdata/train-* - config_name: metaworld-door-close_subset data_files: - split: train path: metaworld-door-close_subset/train-* - config_name: metaworld-door-lock_newdata data_files: - split: train path: metaworld-door-lock_newdata/train-* - config_name: metaworld-door-open_newdata data_files: - split: train path: metaworld-door-open_newdata/train-* - config_name: metaworld-door-open_subset data_files: - split: train path: metaworld-door-open_subset/train-* - config_name: metaworld-door-unlock_newdata data_files: - split: train path: metaworld-door-unlock_newdata/train-* - config_name: metaworld-drawer-close_newdata data_files: - split: train path: metaworld-drawer-close_newdata/train-* - config_name: metaworld-drawer-close_subset data_files: - split: train path: metaworld-drawer-close_subset/train-* - config_name: metaworld-drawer-open_newdata data_files: - split: train path: metaworld-drawer-open_newdata/train-* - config_name: metaworld-drawer-open_subset data_files: - split: train path: metaworld-drawer-open_subset/train-* - config_name: metaworld-faucet-close_newdata data_files: - split: train path: metaworld-faucet-close_newdata/train-* - config_name: metaworld-faucet-close_subset data_files: - split: train path: metaworld-faucet-close_subset/train-* - config_name: metaworld-faucet-open_newdata data_files: - split: train path: metaworld-faucet-open_newdata/train-* - config_name: metaworld-faucet-open_subset data_files: - split: train path: metaworld-faucet-open_subset/train-* - config_name: metaworld-hammer_newdata data_files: - split: train path: metaworld-hammer_newdata/train-* - config_name: metaworld-hammer_subset data_files: - split: train path: metaworld-hammer_subset/train-* - config_name: metaworld-hand-insert_newdata data_files: - split: train path: metaworld-hand-insert_newdata/train-* - config_name: metaworld-handle-press-side_newdata data_files: - split: train path: metaworld-handle-press-side_newdata/train-* - config_name: metaworld-handle-press-side_subset data_files: - split: train path: metaworld-handle-press-side_subset/train-* - config_name: metaworld-handle-press_newdata data_files: - split: train path: metaworld-handle-press_newdata/train-* - config_name: metaworld-handle-press_subset data_files: - split: train path: metaworld-handle-press_subset/train-* - config_name: metaworld-handle-pull-side_newdata data_files: - split: train path: metaworld-handle-pull-side_newdata/train-* - config_name: metaworld-handle-pull-side_subset data_files: - split: train path: metaworld-handle-pull-side_subset/train-* - config_name: metaworld-handle-pull_newdata data_files: - split: train path: metaworld-handle-pull_newdata/train-* - config_name: metaworld-handle-pull_subset data_files: - split: train path: metaworld-handle-pull_subset/train-* - config_name: metaworld-lever-pull_newdata data_files: - split: train path: metaworld-lever-pull_newdata/train-* - config_name: metaworld-lever-pull_subset data_files: - split: train path: metaworld-lever-pull_subset/train-* - config_name: metaworld-peg-insert-side_newdata data_files: - split: train path: metaworld-peg-insert-side_newdata/train-* - config_name: metaworld-peg-insert-side_subset data_files: - split: train path: metaworld-peg-insert-side_subset/train-* - config_name: metaworld-peg-unplug-side_newdata data_files: - split: train path: metaworld-peg-unplug-side_newdata/train-* - config_name: metaworld-peg-unplug-side_subset data_files: - split: train path: metaworld-peg-unplug-side_subset/train-* - config_name: metaworld-pick-out-of-hole_newdata data_files: - split: train path: metaworld-pick-out-of-hole_newdata/train-* - config_name: metaworld-pick-out-of-hole_subset data_files: - split: train path: metaworld-pick-out-of-hole_subset/train-* - config_name: metaworld-pick-place-wall_newdata data_files: - split: train path: metaworld-pick-place-wall_newdata/train-* - config_name: metaworld-pick-place-wall_subset data_files: - split: train path: metaworld-pick-place-wall_subset/train-* - config_name: metaworld-pick-place_newdata data_files: - split: train path: metaworld-pick-place_newdata/train-* - config_name: metaworld-pick-place_subset data_files: - split: train path: metaworld-pick-place_subset/train-* - config_name: metaworld-plate-slide-back-side_newdata data_files: - split: train path: metaworld-plate-slide-back-side_newdata/train-* - config_name: metaworld-plate-slide-back-side_subset data_files: - split: train path: metaworld-plate-slide-back-side_subset/train-* - config_name: metaworld-plate-slide-back_newdata data_files: - split: train path: metaworld-plate-slide-back_newdata/train-* - config_name: metaworld-plate-slide-back_subset data_files: - split: train path: metaworld-plate-slide-back_subset/train-* - config_name: metaworld-plate-slide-side_newdata data_files: - split: train path: metaworld-plate-slide-side_newdata/train-* - config_name: metaworld-plate-slide-side_subset data_files: - split: train path: metaworld-plate-slide-side_subset/train-* - config_name: metaworld-plate-slide_newdata data_files: - split: train path: metaworld-plate-slide_newdata/train-* - config_name: metaworld-plate-slide_subset data_files: - split: train path: metaworld-plate-slide_subset/train-* - config_name: metaworld-push-back_newdata data_files: - split: train path: metaworld-push-back_newdata/train-* - config_name: metaworld-push-back_subset data_files: - split: train path: metaworld-push-back_subset/train-* - config_name: metaworld-push-wall_newdata data_files: - split: train path: metaworld-push-wall_newdata/train-* - config_name: metaworld-push-wall_subset data_files: - split: train path: metaworld-push-wall_subset/train-* - config_name: metaworld-push_newdata data_files: - split: train path: metaworld-push_newdata/train-* - config_name: metaworld-push_subset data_files: - split: train path: metaworld-push_subset/train-* - config_name: metaworld-reach-wall_newdata data_files: - split: train path: metaworld-reach-wall_newdata/train-* - config_name: metaworld-reach-wall_subset data_files: - split: train path: metaworld-reach-wall_subset/train-* - config_name: metaworld-reach_newdata data_files: - split: train path: metaworld-reach_newdata/train-* - config_name: metaworld-reach_subset data_files: - split: train path: metaworld-reach_subset/train-* - config_name: metaworld-shelf-place_newdata data_files: - split: train path: metaworld-shelf-place_newdata/train-* - config_name: metaworld-shelf-place_subset data_files: - split: train path: metaworld-shelf-place_subset/train-* - config_name: metaworld-soccer_newdata data_files: - split: train path: metaworld-soccer_newdata/train-* - config_name: metaworld-soccer_subset data_files: - split: train path: metaworld-soccer_subset/train-* - config_name: metaworld-stick-pull_newdata data_files: - split: train path: metaworld-stick-pull_newdata/train-* - config_name: metaworld-stick-pull_subset data_files: - split: train path: metaworld-stick-pull_subset/train-* - config_name: metaworld-stick-push_newdata data_files: - split: train path: metaworld-stick-push_newdata/train-* - config_name: metaworld-stick-push_subset data_files: - split: train path: metaworld-stick-push_subset/train-* - config_name: metaworld-sweep-into_newdata data_files: - split: train path: metaworld-sweep-into_newdata/train-* - config_name: metaworld-sweep-into_subset data_files: - split: train path: metaworld-sweep-into_subset/train-* - config_name: metaworld-sweep_newdata data_files: - split: train path: metaworld-sweep_newdata/train-* - config_name: metaworld-sweep_subset data_files: - split: train path: metaworld-sweep_subset/train-* - config_name: metaworld-window-close_newdata data_files: - split: train path: metaworld-window-close_newdata/train-* - config_name: metaworld-window-close_subset data_files: - split: train path: metaworld-window-close_subset/train-* - config_name: metaworld-window-open_newdata data_files: - split: train path: metaworld-window-open_newdata/train-* - config_name: metaworld-window-open_subset data_files: - split: train path: metaworld-window-open_subset/train-* - config_name: mujoco-ant_newdata data_files: - split: train path: mujoco-ant_newdata/train-* - config_name: mujoco-ant_subset data_files: - split: train path: mujoco-ant_subset/train-* - config_name: mujoco-doublependulum_newdata data_files: - split: train path: mujoco-doublependulum_newdata/train-* - config_name: mujoco-doublependulum_subset data_files: - split: train path: mujoco-doublependulum_subset/train-* - config_name: mujoco-halfcheetah_newdata data_files: - split: train path: mujoco-halfcheetah_newdata/train-* - config_name: mujoco-hopper_newdata data_files: - split: train path: mujoco-hopper_newdata/train-* - config_name: mujoco-humanoid_newdata data_files: - split: train path: mujoco-humanoid_newdata/train-* - config_name: mujoco-humanoid_subset data_files: - split: train path: mujoco-humanoid_subset/train-* - config_name: mujoco-pendulum_newdata data_files: - split: train path: mujoco-pendulum_newdata/train-* - config_name: mujoco-pendulum_subset data_files: - split: train path: mujoco-pendulum_subset/train-* - config_name: mujoco-pusher_newdata data_files: - split: train path: mujoco-pusher_newdata/train-* - config_name: mujoco-pusher_subset data_files: - split: train path: mujoco-pusher_subset/train-* - config_name: mujoco-reacher_newdata data_files: - split: train path: mujoco-reacher_newdata/train-* - config_name: mujoco-reacher_subset data_files: - split: train path: mujoco-reacher_subset/train-* - config_name: mujoco-standup_newdata data_files: - split: train path: mujoco-standup_newdata/train-* - config_name: mujoco-standup_subset data_files: - split: train path: mujoco-standup_subset/train-* - config_name: mujoco-swimmer_newdata data_files: - split: train path: mujoco-swimmer_newdata/train-* - config_name: mujoco-swimmer_subset data_files: - split: train path: mujoco-swimmer_subset/train-* - config_name: mujoco-walker_newdata data_files: - split: train path: mujoco-walker_newdata/train-* - config_name: mujoco-walker_subset data_files: - split: train path: mujoco-walker_subset/train-* --- This is the dataset for `REGENT: A Retrieval-Augmented Generalist Agent That Can Act In-Context In New Environments`. The REGENT dataset includes a subset of the JAT (tokenized) dataset (from https://huggingface.co/datasets/jat-project) for the REGENT training environments. It has around a 100k transitions from each of the 145 training environments (45 metaworld, 52 atari, 9 mujoco, 39 babyai). Please find this in the *_subset folders.  It also has distance values for input sequences used in the REGENT model for both the above 145 training environments and 12 unseen environments. These values are used for computing the distance normalization value in every environment. These values, along with the indices of the input sequences, in the training environments alone, are used for pre-training REGENT. We detail this REGENT subset of the JAT dataset at https://github.com/regent-research/regent/blob/main/scripts_preprocessing/README.md.

legacy-datasets/mc4

legacy-datasets

--- pretty_name: mC4 annotations_creators: - no-annotation language_creators: - found language: - af - am - ar - az - be - bg - bn - ca - ceb - co - cs - cy - da - de - el - en - eo - es - et - eu - fa - fi - fil - fr - fy - ga - gd - gl - gu - ha - haw - he - hi - hmn - ht - hu - hy - id - ig - is - it - iw - ja - jv - ka - kk - km - kn - ko - ku - ky - la - lb - lo - lt - lv - mg - mi - mk - ml - mn - mr - ms - mt - my - ne - nl - 'no' - ny - pa - pl - ps - pt - ro - ru - sd - si - sk - sl - sm - sn - so - sq - sr - st - su - sv - sw - ta - te - tg - th - tr - uk - und - ur - uz - vi - xh - yi - yo - zh - zu language_bcp47: - bg-Latn - el-Latn - hi-Latn - ja-Latn - ru-Latn - zh-Latn license: - odc-by multilinguality: - multilingual size_categories: - n<1K - 1K<n<10K - 10K<n<100K - 100K<n<1M - 1M<n<10M - 10M<n<100M - 100M<n<1B - 1B<n<10B source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: mc4 viewer: false --- <div class="course-tip course-tip-orange bg-gradient-to-br dark:bg-gradient-to-r before:border-orange-500 dark:before:border-orange-800 from-orange-50 dark:from-gray-900 to-white dark:to-gray-950 border border-orange-50 text-orange-700 dark:text-gray-400"> <p><b>Deprecated:</b> Dataset "mc4" is deprecated and will be deleted. Use "<a href="https://huggingface.co/datasets/allenai/c4">allenai/c4</a>" instead.</p> </div> # Dataset Card for mC4 ## Table of Contents - [Dataset Card for mC4](#dataset-card-for-mc4) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Initial Data Collection and Normalization](#initial-data-collection-and-normalization) - [Who are the source language producers?](#who-are-the-source-language-producers) - [Annotations](#annotations) - [Annotation process](#annotation-process) - [Who are the annotators?](#who-are-the-annotators) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://huggingface.co/datasets/allenai/c4 - **Paper:** https://arxiv.org/abs/1910.10683 ### Dataset Summary A multilingual colossal, cleaned version of Common Crawl's web crawl corpus. Based on Common Crawl dataset: "https://commoncrawl.org". This is the version prepared by AllenAI, hosted at this address: https://huggingface.co/datasets/allenai/c4 108 languages are available and are reported in the table below. Note that the languages that end with "-Latn" are simply romanized variants, i.e. written using the Latin script. | language code | language name | |:----------------|:---------------------| | af | Afrikaans | | am | Amharic | | ar | Arabic | | az | Azerbaijani | | be | Belarusian | | bg | Bulgarian | | bg-Latn | Bulgarian (Latin) | | bn | Bangla | | ca | Catalan | | ceb | Cebuano | | co | Corsican | | cs | Czech | | cy | Welsh | | da | Danish | | de | German | | el | Greek | | el-Latn | Greek (Latin) | | en | English | | eo | Esperanto | | es | Spanish | | et | Estonian | | eu | Basque | | fa | Persian | | fi | Finnish | | fil | Filipino | | fr | French | | fy | Western Frisian | | ga | Irish | | gd | Scottish Gaelic | | gl | Galician | | gu | Gujarati | | ha | Hausa | | haw | Hawaiian | | hi | Hindi | | hi-Latn | Hindi (Latin script) | | hmn | Hmong, Mong | | ht | Haitian | | hu | Hungarian | | hy | Armenian | | id | Indonesian | | ig | Igbo | | is | Icelandic | | it | Italian | | iw | former Hebrew | | ja | Japanese | | ja-Latn | Japanese (Latin) | | jv | Javanese | | ka | Georgian | | kk | Kazakh | | km | Khmer | | kn | Kannada | | ko | Korean | | ku | Kurdish | | ky | Kyrgyz | | la | Latin | | lb | Luxembourgish | | lo | Lao | | lt | Lithuanian | | lv | Latvian | | mg | Malagasy | | mi | Maori | | mk | Macedonian | | ml | Malayalam | | mn | Mongolian | | mr | Marathi | | ms | Malay | | mt | Maltese | | my | Burmese | | ne | Nepali | | nl | Dutch | | no | Norwegian | | ny | Nyanja | | pa | Punjabi | | pl | Polish | | ps | Pashto | | pt | Portuguese | | ro | Romanian | | ru | Russian | | ru-Latn | Russian (Latin) | | sd | Sindhi | | si | Sinhala | | sk | Slovak | | sl | Slovenian | | sm | Samoan | | sn | Shona | | so | Somali | | sq | Albanian | | sr | Serbian | | st | Southern Sotho | | su | Sundanese | | sv | Swedish | | sw | Swahili | | ta | Tamil | | te | Telugu | | tg | Tajik | | th | Thai | | tr | Turkish | | uk | Ukrainian | | und | Unknown language | | ur | Urdu | | uz | Uzbek | | vi | Vietnamese | | xh | Xhosa | | yi | Yiddish | | yo | Yoruba | | zh | Chinese | | zh-Latn | Chinese (Latin) | | zu | Zulu | You can load the mC4 subset of any language like this: ```python from datasets import load_dataset en_mc4 = load_dataset("mc4", "en") ``` And if you can even specify a list of languages: ```python from datasets import load_dataset mc4_subset_with_five_languages = load_dataset("mc4", languages=["en", "fr", "es", "de", "zh"]) ``` ### Supported Tasks and Leaderboards mC4 is mainly intended to pretrain language models and word representations. ### Languages The dataset supports 108 languages. ## Dataset Structure ### Data Instances An example form the `en` config is: ``` {'timestamp': '2018-06-24T01:32:39Z', 'text': 'Farm Resources in Plumas County\nShow Beginning Farmer Organizations & Professionals (304)\nThere are 304 resources serving Plumas County in the following categories:\nMap of Beginning Farmer Organizations & Professionals serving Plumas County\nVictoria Fisher - Office Manager - Loyalton, CA\nAmy Lynn Rasband - UCCE Plumas-Sierra Administrative Assistant II - Quincy , CA\nShow Farm Income Opportunities Organizations & Professionals (353)\nThere are 353 resources serving Plumas County in the following categories:\nFarm Ranch And Forest Retailers (18)\nMap of Farm Income Opportunities Organizations & Professionals serving Plumas County\nWarner Valley Wildlife Area - Plumas County\nShow Farm Resources Organizations & Professionals (297)\nThere are 297 resources serving Plumas County in the following categories:\nMap of Farm Resources Organizations & Professionals serving Plumas County\nThere are 57 resources serving Plumas County in the following categories:\nMap of Organic Certification Organizations & Professionals serving Plumas County', 'url': 'http://www.californialandcan.org/Plumas/Farm-Resources/'} ``` ### Data Fields The data have several fields: - `url`: url of the source as a string - `text`: text content as a string - `timestamp`: timestamp as a string ### Data Splits To build mC4, the authors used [CLD3](https://github.com/google/cld3) to identify over 100 languages. The resulting mC4 subsets for each language are reported in this table: | config | train | validation | |:---------|:--------|:-------------| | af | ? | ? | | am | ? | ? | | ar | ? | ? | | az | ? | ? | | be | ? | ? | | bg | ? | ? | | bg-Latn | ? | ? | | bn | ? | ? | | ca | ? | ? | | ceb | ? | ? | | co | ? | ? | | cs | ? | ? | | cy | ? | ? | | da | ? | ? | | de | ? | ? | | el | ? | ? | | el-Latn | ? | ? | | en | ? | ? | | eo | ? | ? | | es | ? | ? | | et | ? | ? | | eu | ? | ? | | fa | ? | ? | | fi | ? | ? | | fil | ? | ? | | fr | ? | ? | | fy | ? | ? | | ga | ? | ? | | gd | ? | ? | | gl | ? | ? | | gu | ? | ? | | ha | ? | ? | | haw | ? | ? | | hi | ? | ? | | hi-Latn | ? | ? | | hmn | ? | ? | | ht | ? | ? | | hu | ? | ? | | hy | ? | ? | | id | ? | ? | | ig | ? | ? | | is | ? | ? | | it | ? | ? | | iw | ? | ? | | ja | ? | ? | | ja-Latn | ? | ? | | jv | ? | ? | | ka | ? | ? | | kk | ? | ? | | km | ? | ? | | kn | ? | ? | | ko | ? | ? | | ku | ? | ? | | ky | ? | ? | | la | ? | ? | | lb | ? | ? | | lo | ? | ? | | lt | ? | ? | | lv | ? | ? | | mg | ? | ? | | mi | ? | ? | | mk | ? | ? | | ml | ? | ? | | mn | ? | ? | | mr | ? | ? | | ms | ? | ? | | mt | ? | ? | | my | ? | ? | | ne | ? | ? | | nl | ? | ? | | no | ? | ? | | ny | ? | ? | | pa | ? | ? | | pl | ? | ? | | ps | ? | ? | | pt | ? | ? | | ro | ? | ? | | ru | ? | ? | | ru-Latn | ? | ? | | sd | ? | ? | | si | ? | ? | | sk | ? | ? | | sl | ? | ? | | sm | ? | ? | | sn | ? | ? | | so | ? | ? | | sq | ? | ? | | sr | ? | ? | | st | ? | ? | | su | ? | ? | | sv | ? | ? | | sw | ? | ? | | ta | ? | ? | | te | ? | ? | | tg | ? | ? | | th | ? | ? | | tr | ? | ? | | uk | ? | ? | | und | ? | ? | | ur | ? | ? | | uz | ? | ? | | vi | ? | ? | | xh | ? | ? | | yi | ? | ? | | yo | ? | ? | | zh | ? | ? | | zh-Latn | ? | ? | | zu | ? | ? | ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information AllenAI are releasing this dataset under the terms of ODC-BY. By using this, you are also bound by the Common Crawl terms of use in respect of the content contained in the dataset. ### Citation Information ``` @article{2019t5, author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu}, title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer}, journal = {arXiv e-prints}, year = {2019}, archivePrefix = {arXiv}, eprint = {1910.10683}, } ``` ### Contributions Thanks to [@dirkgr](https://github.com/dirkgr) and [@lhoestq](https://github.com/lhoestq) for adding this dataset.

Anthropic/hh-rlhf

Anthropic

--- license: mit tags: - human-feedback --- # Dataset Card for HH-RLHF ## Dataset Summary This repository provides access to two different kinds of data: 1. Human preference data about helpfulness and harmlessness from [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://arxiv.org/abs/2204.05862). These data are meant to train preference (or reward) models for subsequent RLHF training. These data are *not* meant for supervised training of dialogue agents. Training dialogue agents on these data is likely to lead to harmful models and this shold be avoided. 2. Human-generated and annotated red teaming dialogues from [Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned](https://www.anthropic.com/red_teaming.pdf). These data are meant to understand how crowdworkers red team models and what types of red team attacks are succesful or not. The data are *not* meant for fine-tuning or preference modeling (use the data above for preference modeling). These data are entire transcripts of conversations that are derived from the harmlessness preference modeling data described above, where only the chosen response is incorporated into the overall transcript. Furthermore, the transcripts are annotated with human and automated measurements of how harmful the overall dialogues are. **Disclaimer**: The data (especially the harmlessness preference data and the red team data) contain content that may be offensive or upsetting. Topics include, but are not limited to, discriminatory language and discussions of abuse, violence, self-harm, exploitation, and other potentially upsetting subject matter. Please only engage with the data in accordance with your own personal risk tolerance. The data are intended for research purposes, especially research that can make models *less* harmful. The views expressed in the data do not reflect the views of Anthropic or any of its employees. As mentioned above, these data are *not* intended for training dialogue agents as this will likely lead to harmful model behavior. Each of these datasets are described further below. ## Human preference data about helpfulness and harmlessness (PM Data) The data are described in the paper: [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://arxiv.org/abs/2204.05862). If you find the data useful, please cite the paper. The data format is very simple -- each line of the jsonl files contains a pair of texts, one "chosen" and one "rejected". For **helpfulness**, the data are grouped into train/test splits in three tranches: from our base models (context-distilled 52B language models), via rejection sampling (mostly with best-of-16 sampling) against an early preference model, and a dataset sampled during our iterated "online" process. For **harmlessness**, the data are only collected for our base models, but otherwise formatted in the same way. Details about the data collection process and crowdworker population can be found in the paper, specifically in section 2 and appendix D. ## Red teaming data (not PM Data) The data are described in the paper: [Red Teaming Language Models to Reduce Harms: Methods, Scaling Behaviors, and Lessons Learned](https://www.anthropic.com/red_teaming.pdf). If you find the data useful, please cite the paper. At a high level these data can be examined to understand what succesful red team attempts look like. Details about the data and data collection procedures can be found in the Datasheet in the appendix of the paper. Each line of the jsonl file contains a dictionary with the following fields: - `transcript` a text transcript of a conversation between a human adversary (red team member) and an AI assistant - `min_harmlessness_score_transcript` a real value score of the harmlessness of the AI assistant (lower is more harmful) as obtained from a preference model - `num_params` number of parameters in the language model powering the AI assistant - `model_type` type of model powering the AI assistant - `rating` the red team member's rating of how successful they were at breaking the AI assistant (Likert scale, higher is more successful) - `task_description` a short text description written by the red team member about how they tried to red team the AI assistant - `task_description_harmlessness_score` a real value score of the harmlessness of the task description (lower is more harmful) as obtained from a preference model - `red_team_member_id` an arbitrary identifier of the red team member. one red team member can generate multiple red team attacks - `is_upworker` a binary indicator that is true if the red team member was from the crowd platform Upwork or false if they were from MTurk - `tags` a list of up to 6 tags per transcript. tags are short descriptions of the red team attempts generated by crowdworkers who reviewed red team data post-hoc. tags were only provided for a random sample of 1000 red team attempts for two of four model types. ## Usage Each of the above datasets is located in a separate sub-directory. To load an individual subset, use the `data_dir` argument of the `load_dataset()` function as follows: ```python from datasets import load_dataset # Load all helpfulness/harmless subsets (share the same schema) dataset = load_dataset("Anthropic/hh-rlhf") # Load one of the harmless subsets dataset = load_dataset("Anthropic/hh-rlhf", data_dir="harmless-base") # Load the red teaming subset dataset = load_dataset("Anthropic/hh-rlhf", data_dir="red-team-attempts") ``` ## Contact The original authors host this dataset on GitHub here: https://github.com/anthropics/hh-rlhf You can submit inquiries to: [email protected]

etechgrid/ttm-validation-dataset

etechgrid

--- dataset_info: features: - name: Prompts dtype: string - name: File_Path dtype: audio splits: - name: train num_bytes: 2123744029.274 num_examples: 1106 download_size: 1349552908 dataset_size: 2123744029.274 configs: - config_name: default data_files: - split: train path: data/train-* ---

CodedotAI/code_clippy_github

CodedotAI

--- annotations_creators: [] language_creators: - crowdsourced - expert-generated language: ["code"] license: - mit multilinguality: - multilingual pretty_name: code-clippy-github-code size_categories: - unknown source_datasets: [] task_categories: - sequence-modeling task_ids: - language-modeling --- # Code Clippy Github Dataset ## Dataset Description The Code Clippy dataset consists of various public codebases from GitHub in 22 programming languages with 23 extensions totaling about 16 TB of data when uncompressed. The dataset was created from the public GitHub dataset on Google BigQuery. ### How to use it This dataset is pretty large please use the streaming parameter from the `datasets` library as seen below: ```python from datasets import load_dataset ds = load_dataset("CodedotAI/code_clippy_github", streaming=True) ``` ## Data Structure ### Data Instances ```python { 'code_text': " a = mc^2", 'repo_name': 'NotEinstein', 'file_path': 'root/users/einstein.py', 'language': 'Python', 'license': 'isc', 'size': 2 } ``` ### Data Fields |Field|Type|Description| |---|---|---| |code_text|string|string of the source code contained in the code file| |repo_name|string|name of the GitHub repository| |file_path|string|path of the code file within the repository | |language|string|programming language used in the file inferred by the file extension| |license|string|license of GitHub repository| |size|int|size of source file in bytes| ### Data Splits Only a train split is provided in this dataset. ## Languages The dataset contains 22 programming languages with over 23 extensions: ```python { "C": [".c"], "C#": [".cs"], "C++": [".cpp"], "CSS": [".css"], "Dart" : [".dart"], "GO": [".go"], "HTML":[".html"], "Java": [".java"], "JavaScript": [".js"], "Jupyter Notebooks (Python)": [".ipynb"], "Kotlin" : [".kt"], "Lisp" : [".lisp"], "Matlab" : [".m"], "PHP": [".php"], "Perl": [".pl"], "Python": [".py"], "R" : [".r"], "Ruby": [".rb"], "Rust": [".rs"], "SQL": [".sql"], "Shell": [".sh"], "Swift" : [".swift"], "TypeScript": [".ts"], } ``` ## Licenses Each example is also annotated with the license of the associated repository. There are in total 15 licenses: ```python [ 'mit', 'apache-2.0', 'gpl-2.0', 'gpl-3.0', 'bsd-3-clause', 'bsd-2-clause', 'unlicense', 'apacheagpl-3.0', 'lgpl-3.0', 'cc0-1.0', 'epl-1.0', 'lgpl-2.1', 'mpl-2.0', 'isc', 'artistic-2.0' ] ``` ## Dataset Statistics The dataset is about ~ 18 TB uncompressed. We are currently working on processing it and applying further filtering. ## Dataset Creation The dataset was created in two steps: 1. Files with the extensions given in the list above were retrieved from the GitHub dataset on BigQuery using the following query: ```sql SELECT f.id, f.repo_name, f.path, content.copies, content.size, content.content, lic.license FROM `bigquery-public-data.github_repos.files` AS f JOIN `bigquery-public-data.github_repos.contents` as content ON f.id = content.id JOIN `bigquery-public-data.github_repos.licenses` AS lic ON f.repo_name = lic.repo_name WHERE NOT content.binary AND ( (f.path LIKE '%.py') OR (f.path LIKE '%.java') OR (f.path LIKE '%.js') OR (f.path LIKE '%.html') OR (f.path LIKE '%.lisp') OR (f.path LIKE '%.sh') OR (f.path LIKE '%.r') OR (f.path LIKE '%.pl') OR (f.path LIKE '%.css') OR (f.path LIKE '%.sql') OR (f.path LIKE '%.c') OR (f.path LIKE '%.cpp') OR (f.path LIKE '%.ts') OR (f.path LIKE '%.cs') OR (f.path LIKE '%.go') OR (f.path LIKE '%.rs') OR (f.path LIKE '%.swift') OR (f.path LIKE '%.php') OR (f.path LIKE '%.dart') OR (f.path LIKE '%.kt') OR (f.path LIKE '%.m') OR (f.path LIKE '%.rb') OR (f.path LIKE '%.ipynb') ) -- make sure we dont go above 1 megabyte AND (content.size BETWEEN 1024 AND 1000000) ``` 2. Currently, our CodedotAI team is working on adding additional filters and cleaning this dataset. ### Personal and Sensitive Information Since this data was collected from public repositories, there exists potential for personal and sensitive information to be included in the data through developers accidentally or on purpose uploading their secret keys, passwords, API keys, emails, etc. ## Considerations for Using the Data ### Social Impact of Dataset The paper ["Evaluating Large Language Models Trained on Code"](https://arxiv.org/abs/2107.03374) from OpenAI has a good discussion on what the impact of a large language model trained on code could be. Therefore, some parts of their discussion are highlighted here as it pertains to this dataset and models that may be trained from it. **As well as some differences in views from the paper, particularly around legal implications**. 1. **Over-reliance:** A language model trained on large datasets such as this one for the task of autogenerating code may generate plausible solutions that may appear correct, but are not necessarily the correct solution. Not properly evaluating the generated code may cause have negative consequences such as the introduction of bugs, or the introduction of security vulnerabilities. Therefore, it is important that users are aware of the limitations and potential negative consequences of using a language model trained on this dataset. 2. **Economic and labor market impacts:** Large language models trained on large code datasets such as this one that are capable of generating high-quality code have the potential to automate part of the software development process. This may negatively impact software developers. However, as discussed in the paper, as shown in the Summary Report of software developers from [O*NET OnLine](https://www.onetonline.org/link/summary/15-1252.00), developers don't just write software. 3. **Security implications:** No filtering or checking of vulnerabilities or buggy code was performed. This means that the dataset may contain code that may be malicious or contain vulnerabilities. Therefore, any model trained on this dataset may generate vulnerable, buggy, or malicious code. In safety-critical software, this could lead to software that may work improperly and could result in serious consequences depending on the software. Additionally, a model trained on this dataset may be used to generate malicious code on purpose in order to perform ransomware or other such attacks. 4. **Legal implications:** No filtering was performed on licensed code. This means that the dataset may contain restrictive licensed code. As discussed in the paper, public Github repositories may fall under "fair use." However, there have been little to no previous cases of such usages of licensed publicly available code. Therefore, any model trained on this dataset may be required to obey license terms that align with the software it was trained on such as GPL-3.0, which is why we purposefully put this dataset under the GPL-3.0 license. It is unclear the legal ramifications of using a language model trained on this dataset. ### v1.0 - The query was executed on _February 1, 2022, 12:15:59 AM EST_ ## Acknowledgements This project would not have been possible without compute generously provided by Google through the [TPU Research Cloud](https://sites.research.google/trc/about/). We would also like to thank [Dr. Razvan Bunescu](https://webpages.charlotte.edu/rbunescu/) and [The College of Computing and Informatics at UNC Charlotte](https://cci.charlotte.edu/) for their generous contributions to this project, specifically in funding the BigQuery and Google Cloud Storage costs. We would also like to thank the [codeparrot team at Hugging face](https://huggingface.co/codeparrot) for open sourcing their documentation on [github-code](https://huggingface.co/datasets/codeparrot/github-code) which we used for the readme in this dataset. For another similar dataset to this please check github-code!

WenhaoWang/VidProM

WenhaoWang

--- license: cc-by-nc-4.0 task_categories: - text-to-video - text-to-image language: - en pretty_name: VidProM size_categories: - 1M<n<10M source_datasets: - original tags: - prompts - text-to-video - text-to-image - Pika - VideoCraft2 - Text2Video-Zero - ModelScope - Video Generative Model Evaluation - Text-to-Video Diffusion Model Development - Text-to-Video Prompt Engineering - Efficient Video Generation - Fake Video Detection - Video Copy Detection for Diffusion Models configs: - config_name: VidProM_unique data_files: VidProM_unique.csv --- <p align="center"> <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/teasor.png" width="800"> </p> # Summary This is the dataset proposed in our paper [**VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models**](https://arxiv.org/abs/2403.06098) (NeurIPS 2024). VidProM is the first dataset featuring 1.67 million unique text-to-video prompts and 6.69 million videos generated from 4 different state-of-the-art diffusion models. It inspires many exciting new research areas, such as Text-to-Video Prompt Engineering, Efficient Video Generation, Fake Video Detection, and Video Copy Detection for Diffusion Models. # Directory ``` *DATA_PATH *VidProM_unique.csv *VidProM_semantic_unique.csv *VidProM_embed.hdf5 *original_files *generate_1_ori.html *generate_2_ori.html ... *pika_videos *pika_videos_1.tar *pika_videos_2.tar ... *vc2_videos *vc2_videos_1.tar *vc2_videos_2.tar ... *t2vz_videos *t2vz_videos_1.tar *t2vz_videos_2.tar ... *ms_videos *ms_videos_1.tar *ms_videos_2.tar ... *example ``` # Download ### Automatical Install the [datasets](https://huggingface.co/docs/datasets/v1.15.1/installation.html) library first, by: ``` pip install datasets ``` Then it can be downloaded automatically with ```python import numpy as np from datasets import load_dataset dataset = load_dataset('WenhaoWang/VidProM') ``` ### Manual You can also download each file by ```wget```, for instance: ``` wget https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/VidProM_unique.csv ``` ### Users from China For users from China, we cooperate with [Wisemodel](https://wisemodel.cn/home), and you can download them faster from [here](https://wisemodel.cn/datasets/WenhaoWang/VidProM). # Explanation ``VidProM_unique.csv`` contains the UUID, prompt, time, and 6 NSFW probabilities. It can easily be read by ```python import pandas df = pd.read_csv("VidProM_unique.csv") ``` Below are three rows from ``VidProM_unique.csv``: | uuid | prompt | time | toxicity | obscene | identity_attack | insult | threat | sexual_explicit | |--------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------|----------|---------|-----------------|---------|---------|-----------------| | 6a83eb92-faa0-572b-9e1f-67dec99b711d | Flying among clouds and stars, kitten Max discovered a world full of winged friends. Returning home, he shared his stories and everyone smiled as they imagined flying together in their dreams. | Sun Sep 3 12:27:44 2023 | 0.00129 | 0.00016 | 7e-05 | 0.00064 | 2e-05 | 2e-05 | | 3ba1adf3-5254-59fb-a13e-57e6aa161626 | Use a clean and modern font for the text "Relate Reality 101." Add a small, stylized heart icon or a thought bubble above or beside the text to represent emotions and thoughts. Consider using a color scheme that includes warm, inviting colors like deep reds, soft blues, or soothing purples to evoke feelings of connection and intrigue. | Wed Sep 13 18:15:30 2023 | 0.00038 | 0.00013 | 8e-05 | 0.00018 | 3e-05 | 3e-05 | | 62e5a2a0-4994-5c75-9976-2416420526f7 | zoomed out, sideview of an Grey Alien sitting at a computer desk | Tue Oct 24 20:24:21 2023 | 0.01777 | 0.00029 | 0.00336 | 0.00256 | 0.00017 | 5e-05 | ``VidProM_semantic_unique.csv`` is a semantically unique version of ``VidProM_unique.csv``. ``VidProM_embed.hdf5`` is the 3072-dim embeddings of our prompts. They are embedded by text-embedding-3-large, which is the latest text embedding model of OpenAI. It can easily be read by ```python import numpy as np import h5py def read_descriptors(filename): hh = h5py.File(filename, "r") descs = np.array(hh["embeddings"]) names = np.array(hh["uuid"][:], dtype=object).astype(str).tolist() return names, descs uuid, features = read_descriptors('VidProM_embed.hdf5') ``` ``original_files`` are the HTML files from [official Pika Discord](https://discord.com/invite/pika) collected by [DiscordChatExporter](https://github.com/Tyrrrz/DiscordChatExporter). You can do whatever you want with it under [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). ``pika_videos``, ``vc2_videos``, ``t2vz_videos``, and ``ms_videos`` are the generated videos by 4 state-of-the-art text-to-video diffusion models. Each contains 30 tar files. ``example`` is a subfolder which contains 10,000 datapoints. # Datapoint <p align="center"> <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/datapoint.png" width="800"> </p> # Comparison with DiffusionDB <p align="center"> <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_table.jpg" width="800"> </p> <p align="center"> <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/compare_visual.png" width="800"> </p> <p align="center"> <img src="https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/WizMap_V_D.jpg" width="800"> </p> Click the [WizMap](https://poloclub.github.io/wizmap/?dataURL=https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/data_vidprom_diffusiondb.ndjson&gridURL=https://huggingface.co/datasets/WenhaoWang/VidProM/resolve/main/grid_vidprom_diffusiondb.json) (and wait for 5 seconds) for an interactive visualization of our 1.67 million prompts. Above is a thumbnail. Please check our paper for a detailed comparison. # Curators VidProM is created by [Wenhao Wang](https://wangwenhao0716.github.io/) and Professor [Yi Yang](https://scholar.google.com/citations?user=RMSuNFwAAAAJ&hl=zh-CN). # License The prompts and videos generated by [Pika](https://discord.com/invite/pika) in our VidProM are licensed under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). Additionally, similar to their original repositories, the videos from [VideoCraft2](https://github.com/AILab-CVC/VideoCrafter), [Text2Video-Zero](https://github.com/Picsart-AI-Research/Text2Video-Zero), and [ModelScope](https://huggingface.co/ali-vilab/modelscope-damo-text-to-video-synthesis) are released under the [Apache license](https://www.apache.org/licenses/LICENSE-2.0), the [CreativeML Open RAIL-M license](https://github.com/Picsart-AI-Research/Text2Video-Zero/blob/main/LICENSE), and the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en), respectively. Our code is released under the [CC BY-NC 4.0 license](https://creativecommons.org/licenses/by-nc/4.0/deed.en). # Citation ``` @article{wang2024vidprom, title={VidProM: A Million-scale Real Prompt-Gallery Dataset for Text-to-Video Diffusion Models}, author={Wang, Wenhao and Yang, Yi}, booktitle={Thirty-eighth Conference on Neural Information Processing Systems}, year={2024}, url={https://openreview.net/forum?id=pYNl76onJL} } ``` # Contact If you have any questions, feel free to contact Wenhao Wang ([email protected]).

McAuley-Lab/Amazon-Reviews-2023

McAuley-Lab

--- language: - en tags: - recommendation - reviews size_categories: - 10B<n<100B dataset_info: - config_name: raw_meta_All_Beauty features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 172622243 num_examples: 112590 download_size: 59635138 dataset_size: 172622243 - config_name: raw_meta_Arts_Crafts_and_Sewing features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 1893257069 num_examples: 801446 download_size: 806711170 dataset_size: 1893257069 - config_name: raw_meta_Cell_Phones_and_Accessories features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 3497596478 num_examples: 1288490 download_size: 1262072469 dataset_size: 3497596478 - config_name: raw_meta_Electronics features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 4603602269 num_examples: 1610012 download_size: 1955009715 dataset_size: 4603602269 - config_name: raw_meta_Gift_Cards features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 1740761 num_examples: 1137 download_size: 401887 dataset_size: 1740761 - config_name: raw_meta_Handmade_Products features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 340772183 num_examples: 164817 download_size: 132049123 dataset_size: 340772183 - config_name: raw_meta_Industrial_and_Scientific features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 986632649 num_examples: 427564 download_size: 425007659 dataset_size: 986632649 - config_name: raw_meta_Musical_Instruments features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 553296301 num_examples: 213593 download_size: 229633633 dataset_size: 553296301 - config_name: raw_meta_Toys_and_Games features: - name: main_category dtype: string - name: title dtype: string - name: average_rating dtype: float64 - name: rating_number dtype: int64 - name: features sequence: string - name: description sequence: string - name: price dtype: string - name: images sequence: - name: hi_res dtype: string - name: large dtype: string - name: thumb dtype: string - name: variant dtype: string - name: videos sequence: - name: title dtype: string - name: url dtype: string - name: user_id dtype: string - name: store dtype: string - name: categories sequence: string - name: details dtype: string - name: parent_asin dtype: string - name: bought_together dtype: string - name: subtitle dtype: string - name: author dtype: string splits: - name: full num_bytes: 2291736294 num_examples: 890874 download_size: 972667016 dataset_size: 2291736294 configs: - config_name: raw_meta_All_Beauty data_files: - split: full path: raw_meta_All_Beauty/full-* - config_name: raw_meta_Arts_Crafts_and_Sewing data_files: - split: full path: raw_meta_Arts_Crafts_and_Sewing/full-* - config_name: raw_meta_Cell_Phones_and_Accessories data_files: - split: full path: raw_meta_Cell_Phones_and_Accessories/full-* - config_name: raw_meta_Electronics data_files: - split: full path: raw_meta_Electronics/full-* - config_name: raw_meta_Gift_Cards data_files: - split: full path: raw_meta_Gift_Cards/full-* - config_name: raw_meta_Handmade_Products data_files: - split: full path: raw_meta_Handmade_Products/full-* - config_name: raw_meta_Industrial_and_Scientific data_files: - split: full path: raw_meta_Industrial_and_Scientific/full-* - config_name: raw_meta_Musical_Instruments data_files: - split: full path: raw_meta_Musical_Instruments/full-* - config_name: raw_meta_Toys_and_Games data_files: - split: full path: raw_meta_Toys_and_Games/full-* --- # Amazon Reviews 2023 **Please also visit [amazon-reviews-2023.github.io/](https://amazon-reviews-2023.github.io/) for more details, loading scripts, and preprocessed benchmark files.** **[April 7, 2024]** We add two useful files: 1. `all_categories.txt`: 34 lines (33 categories + "Unknown"), each line contains a category name. 2. `asin2category.json`: A mapping between `parent_asin` (item ID) to its corresponding category name. --- <!-- Provide a quick summary of the dataset. --> This is a large-scale **Amazon Reviews** dataset, collected in **2023** by [McAuley Lab](https://cseweb.ucsd.edu/~jmcauley/), and it includes rich features such as: 1. **User Reviews** (*ratings*, *text*, *helpfulness votes*, etc.); 2. **Item Metadata** (*descriptions*, *price*, *raw image*, etc.); 3. **Links** (*user-item* / *bought together* graphs). ## What's New? In the Amazon Reviews'23, we provide: 1. **Larger Dataset:** We collected 571.54M reviews, 245.2% larger than the last version; 2. **Newer Interactions:** Current interactions range from May. 1996 to Sep. 2023; 3. **Richer Metadata:** More descriptive features in item metadata; 4. **Fine-grained Timestamp:** Interaction timestamp at the second or finer level; 5. **Cleaner Processing:** Cleaner item metadata than previous versions; 6. **Standard Splitting:** Standard data splits to encourage RecSys benchmarking. ## Basic Statistics > We define the <b>#R_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) in user reviews and <b>#M_Tokens</b> as the number of [tokens](https://pypi.org/project/tiktoken/) if treating the dictionaries of item attributes as strings. We emphasize them as important statistics in the era of LLMs. > We count the number of items based on user reviews rather than item metadata files. Note that some items lack metadata. ### Compared to Previous Versions | Year | #Review | #User | #Item | #R_Token | #M_Token | #Domain | Timespan | | ----------- | ---------: | -------: | -------: | ---------: | ------------: | ------------: | ------------: | | [2013](https://snap.stanford.edu/data/web-Amazon-links.html) | 34.69M | 6.64M | 2.44M | 5.91B | -- | 28 | Jun'96 - Mar'13 | | [2014](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon/links.html) | 82.83M | 21.13M | 9.86M | 9.16B | 4.14B | 24 | May'96 - Jul'14 | | [2018](https://cseweb.ucsd.edu/~jmcauley/datasets/amazon_v2/) | 233.10M | 43.53M | 15.17M | 15.73B | 7.99B | 29 | May'96 - Oct'18 | | <b>[2023](https://)</b> | **571.54M** | **54.51M** | **48.19M** | **30.14B** | **30.78B** | **33** | **May'96 - Sep'23** | ### Grouped by Category | Category | #User | #Item | #Rating | #R_Token | #M_Token | Download | | ------------------------ | ------: | ------: | --------: | -------: | -------: | ------------------------------: | | All_Beauty | 632.0K | 112.6K | 701.5K | 31.6M | 74.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/All_Beauty.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_All_Beauty.jsonl.gz' download> meta </a> | | Amazon_Fashion | 2.0M | 825.9K | 2.5M | 94.9M | 510.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Amazon_Fashion.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Amazon_Fashion.jsonl.gz' download> meta </a> | | Appliances | 1.8M | 94.3K | 2.1M | 92.8M | 95.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Appliances.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Appliances.jsonl.gz' download> meta </a> | | Arts_Crafts_and_Sewing | 4.6M | 801.3K | 9.0M | 350.0M | 695.4M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Arts_Crafts_and_Sewing.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Arts_Crafts_and_Sewing.jsonl.gz' download> meta </a> | | Automotive | 8.0M | 2.0M | 20.0M | 824.9M | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Automotive.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Automotive.jsonl.gz' download> meta </a> | | Baby_Products | 3.4M | 217.7K | 6.0M | 323.3M | 218.6M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Baby_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Baby_Products.jsonl.gz' download> meta </a> | | Beauty_and_Personal_Care | 11.3M | 1.0M | 23.9M | 1.1B | 913.7M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Beauty_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Beauty_and_Personal_Care.jsonl.gz' download> meta </a> | | Books | 10.3M | 4.4M | 29.5M | 2.9B | 3.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Books.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Books.jsonl.gz' download> meta </a> | | CDs_and_Vinyl | 1.8M | 701.7K | 4.8M | 514.8M | 287.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/CDs_and_Vinyl.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_CDs_and_Vinyl.jsonl.gz' download> meta </a> | | Cell_Phones_and_Accessories | 11.6M | 1.3M | 20.8M | 935.4M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Cell_Phones_and_Accessories.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Cell_Phones_and_Accessories.jsonl.gz' download> meta </a> | | Clothing_Shoes_and_Jewelry | 22.6M | 7.2M | 66.0M | 2.6B | 5.9B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Clothing_Shoes_and_Jewelry.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Clothing_Shoes_and_Jewelry.jsonl.gz' download> meta </a> | | Digital_Music | 101.0K | 70.5K | 130.4K | 11.4M | 22.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Digital_Music.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Digital_Music.jsonl.gz' download> meta </a> | | Electronics | 18.3M | 1.6M | 43.9M | 2.7B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Electronics.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Electronics.jsonl.gz' download> meta </a> | | Gift_Cards | 132.7K | 1.1K | 152.4K | 3.6M | 630.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Gift_Cards.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Gift_Cards.jsonl.gz' download> meta </a> | | Grocery_and_Gourmet_Food | 7.0M | 603.2K | 14.3M | 579.5M | 462.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Grocery_and_Gourmet_Food.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Grocery_and_Gourmet_Food.jsonl.gz' download> meta </a> | | Handmade_Products | 586.6K | 164.7K | 664.2K | 23.3M | 125.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Handmade_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Handmade_Products.jsonl.gz' download> meta </a> | | Health_and_Household | 12.5M | 797.4K | 25.6M | 1.2B | 787.2M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Household.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Household.jsonl.gz' download> meta </a> | | Health_and_Personal_Care | 461.7K | 60.3K | 494.1K | 23.9M | 40.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Health_and_Personal_Care.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Health_and_Personal_Care.jsonl.gz' download> meta </a> | | Home_and_Kitchen | 23.2M | 3.7M | 67.4M | 3.1B | 3.8B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Home_and_Kitchen.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Home_and_Kitchen.jsonl.gz' download> meta </a> | | Industrial_and_Scientific | 3.4M | 427.5K | 5.2M | 235.2M | 363.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Industrial_and_Scientific.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Industrial_and_Scientific.jsonl.gz' download> meta </a> | | Kindle_Store | 5.6M | 1.6M | 25.6M | 2.2B | 1.7B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Kindle_Store.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Kindle_Store.jsonl.gz' download> meta </a> | | Magazine_Subscriptions | 60.1K | 3.4K | 71.5K | 3.8M | 1.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Magazine_Subscriptions.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Magazine_Subscriptions.jsonl.gz' download> meta </a> | | Movies_and_TV | 6.5M | 747.8K | 17.3M | 1.0B | 415.5M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Movies_and_TV.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Movies_and_TV.jsonl.gz' download> meta </a> | | Musical_Instruments | 1.8M | 213.6K | 3.0M | 182.2M | 200.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Musical_Instruments.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Musical_Instruments.jsonl.gz' download> meta </a> | | Office_Products | 7.6M | 710.4K | 12.8M | 574.7M | 682.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Office_Products.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Office_Products.jsonl.gz' download> meta </a> | | Patio_Lawn_and_Garden | 8.6M | 851.7K | 16.5M | 781.3M | 875.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Patio_Lawn_and_Garden.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Patio_Lawn_and_Garden.jsonl.gz' download> meta </a> | | Pet_Supplies | 7.8M | 492.7K | 16.8M | 905.9M | 511.0M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Pet_Supplies.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Pet_Supplies.jsonl.gz' download> meta </a> | | Software | 2.6M | 89.2K | 4.9M | 179.4M | 67.1M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Software.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Software.jsonl.gz' download> meta </a> | | Sports_and_Outdoors | 10.3M | 1.6M | 19.6M | 986.2M | 1.3B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Sports_and_Outdoors.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Sports_and_Outdoors.jsonl.gz' download> meta </a> | | Subscription_Boxes | 15.2K | 641 | 16.2K | 1.0M | 447.0K | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Subscription_Boxes.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Subscription_Boxes.jsonl.gz' download> meta </a> | | Tools_and_Home_Improvement | 12.2M | 1.5M | 27.0M | 1.3B | 1.5B | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Tools_and_Home_Improvement.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Tools_and_Home_Improvement.jsonl.gz' download> meta </a> | | Toys_and_Games | 8.1M | 890.7K | 16.3M | 707.9M | 848.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Toys_and_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Toys_and_Games.jsonl.gz' download> meta </a> | | Video_Games | 2.8M | 137.2K | 4.6M | 347.9M | 137.3M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Video_Games.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Video_Games.jsonl.gz' download> meta </a> | | Unknown | 23.1M | 13.2M | 63.8M | 3.3B | 232.8M | <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/review_categories/Unknown.jsonl.gz' download> review</a>, <a href='https://datarepo.eng.ucsd.edu/mcauley_group/data/amazon_2023/raw/meta_categories/meta_Unknown.jsonl.gz' download> meta </a> | > Check Pure ID files and corresponding data splitting strategies in <b>[Common Data Processing](https://amazon-reviews-2023.github.io/data_processing/index.html)</b> section. ## Quick Start ### Load User Reviews ```python from datasets import load_dataset dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_review_All_Beauty", trust_remote_code=True) print(dataset["full"][0]) ``` ```json {'rating': 5.0, 'title': 'Such a lovely scent but not overpowering.', 'text': "This spray is really nice. It smells really good, goes on really fine, and does the trick. I will say it feels like you need a lot of it though to get the texture I want. I have a lot of hair, medium thickness. I am comparing to other brands with yucky chemicals so I'm gonna stick with this. Try it!", 'images': [], 'asin': 'B00YQ6X8EO', 'parent_asin': 'B00YQ6X8EO', 'user_id': 'AGKHLEW2SOWHNMFQIJGBECAF7INQ', 'timestamp': 1588687728923, 'helpful_vote': 0, 'verified_purchase': True} ``` ### Load Item Metadata ```python dataset = load_dataset("McAuley-Lab/Amazon-Reviews-2023", "raw_meta_All_Beauty", split="full", trust_remote_code=True) print(dataset[0]) ``` ```json {'main_category': 'All Beauty', 'title': 'Howard LC0008 Leather Conditioner, 8-Ounce (4-Pack)', 'average_rating': 4.8, 'rating_number': 10, 'features': [], 'description': [], 'price': 'None', 'images': {'hi_res': [None, 'https://m.media-amazon.com/images/I/71i77AuI9xL._SL1500_.jpg'], 'large': ['https://m.media-amazon.com/images/I/41qfjSfqNyL.jpg', 'https://m.media-amazon.com/images/I/41w2yznfuZL.jpg'], 'thumb': ['https://m.media-amazon.com/images/I/41qfjSfqNyL._SS40_.jpg', 'https://m.media-amazon.com/images/I/41w2yznfuZL._SS40_.jpg'], 'variant': ['MAIN', 'PT01']}, 'videos': {'title': [], 'url': [], 'user_id': []}, 'store': 'Howard Products', 'categories': [], 'details': '{"Package Dimensions": "7.1 x 5.5 x 3 inches; 2.38 Pounds", "UPC": "617390882781"}', 'parent_asin': 'B01CUPMQZE', 'bought_together': None, 'subtitle': None, 'author': None} ``` > Check data loading examples and Huggingface datasets APIs in <b>[Common Data Loading](https://amazon-reviews-2023.github.io/data_loading/index.html)</b> section. ## Data Fields ### For User Reviews | Field | Type | Explanation | | ----- | ---- | ----------- | | rating | float | Rating of the product (from 1.0 to 5.0). | | title | str | Title of the user review. | | text | str | Text body of the user review. | | images | list | Images that users post after they have received the product. Each image has different sizes (small, medium, large), represented by the small_image_url, medium_image_url, and large_image_url respectively. | | asin | str | ID of the product. | | parent_asin | str | Parent ID of the product. Note: Products with different colors, styles, sizes usually belong to the same parent ID. The “asin” in previous Amazon datasets is actually parent ID. <b>Please use parent ID to find product meta.</b> | | user_id | str | ID of the reviewer | | timestamp | int | Time of the review (unix time) | | verified_purchase | bool | User purchase verification | | helpful_vote | int | Helpful votes of the review | ### For Item Metadata | Field | Type | Explanation | | ----- | ---- | ----------- | | main_category | str | Main category (i.e., domain) of the product. | | title | str | Name of the product. | | average_rating | float | Rating of the product shown on the product page. | | rating_number | int | Number of ratings in the product. | | features | list | Bullet-point format features of the product. | | description | list | Description of the product. | | price | float | Price in US dollars (at time of crawling). | | images | list | Images of the product. Each image has different sizes (thumb, large, hi_res). The “variant” field shows the position of image. | | videos | list | Videos of the product including title and url. | | store | str | Store name of the product. | | categories | list | Hierarchical categories of the product. | | details | dict | Product details, including materials, brand, sizes, etc. | | parent_asin | str | Parent ID of the product. | | bought_together | list | Recommended bundles from the websites. | ## Citation ```bibtex @article{hou2024bridging, title={Bridging Language and Items for Retrieval and Recommendation}, author={Hou, Yupeng and Li, Jiacheng and He, Zhankui and Yan, An and Chen, Xiusi and McAuley, Julian}, journal={arXiv preprint arXiv:2403.03952}, year={2024} } ``` ## Contact Us - **Report Bugs**: To report bugs in the dataset, please file an issue on our [GitHub](https://github.com/hyp1231/AmazonReviews2023/issues/new). - **Others**: For research collaborations or other questions, please email **yphou AT ucsd.edu**.

haonan-li/cmmlu

haonan-li

--- license: cc-by-nc-4.0 task_categories: - multiple-choice - question-answering language: - zh tags: - chinese - llm - evaluation pretty_name: CMMLU size_categories: - 10K<n<100K --- # CMMLU: Measuring massive multitask language understanding in Chinese - **Homepage:** [https://github.com/haonan-li/CMMLU](https://github.com/haonan-li/CMMLU) - **Repository:** [https://huggingface.co/datasets/haonan-li/cmmlu](https://huggingface.co/datasets/haonan-li/cmmlu) - **Paper:** [CMMLU: Measuring Chinese Massive Multitask Language Understanding](https://arxiv.org/abs/2306.09212). ## Table of Contents - [Introduction](#introduction) - [Leaderboard](#leaderboard) - [Data](#data) - [Citation](#citation) - [License](#license) ## Introduction CMMLU is a comprehensive Chinese assessment suite specifically designed to evaluate the advanced knowledge and reasoning abilities of LLMs within the Chinese language and cultural context. CMMLU covers a wide range of subjects, comprising 67 topics that span from elementary to advanced professional levels. It includes subjects that require computational expertise, such as physics and mathematics, as well as disciplines within humanities and social sciences. Many of these tasks are not easily translatable from other languages due to their specific contextual nuances and wording. Furthermore, numerous tasks within CMMLU have answers that are specific to China and may not be universally applicable or considered correct in other regions or languages. ## Leaderboard Latest leaderboard is in our [github](https://github.com/haonan-li/CMMLU). ## Data We provide development and test dataset for each of 67 subjects, with 5 questions in development set and 100+ quesitons in test set. Each question in the dataset is a multiple-choice questions with 4 choices and only one choice as the correct answer. Here are two examples: ``` 题目：同一物种的两类细胞各产生一种分泌蛋白，组成这两种蛋白质的各种氨基酸含量相同，但排列顺序不同。其原因是参与这两种蛋白质合成的： A. tRNA种类不同 B. 同一密码子所决定的氨基酸不同 C. mRNA碱基序列不同 D. 核糖体成分不同 答案是：C ``` ``` 题目：某种植物病毒V是通过稻飞虱吸食水稻汁液在水稻间传播的。稻田中青蛙数量的增加可减少该病毒在水稻间的传播。下列叙述正确的是： A. 青蛙与稻飞虱是捕食关系 B. 水稻和病毒V是互利共生关系 C. 病毒V与青蛙是寄生关系 D. 水稻与青蛙是竞争关系 答案是： ``` #### Load data ```python from datasets import load_dataset cmmlu=load_dataset(r"haonan-li/cmmlu", 'agronomy') print(cmmlu['test'][0]) ``` #### Load all data at once ```python task_list = ['agronomy', 'anatomy', 'ancient_chinese', 'arts', 'astronomy', 'business_ethics', 'chinese_civil_service_exam', 'chinese_driving_rule', 'chinese_food_culture', 'chinese_foreign_policy', 'chinese_history', 'chinese_literature', 'chinese_teacher_qualification', 'clinical_knowledge', 'college_actuarial_science', 'college_education', 'college_engineering_hydrology', 'college_law', 'college_mathematics', 'college_medical_statistics', 'college_medicine', 'computer_science', 'computer_security', 'conceptual_physics', 'construction_project_management', 'economics', 'education', 'electrical_engineering', 'elementary_chinese', 'elementary_commonsense', 'elementary_information_and_technology', 'elementary_mathematics', 'ethnology', 'food_science', 'genetics', 'global_facts', 'high_school_biology', 'high_school_chemistry', 'high_school_geography', 'high_school_mathematics', 'high_school_physics', 'high_school_politics', 'human_sexuality', 'international_law', 'journalism', 'jurisprudence', 'legal_and_moral_basis', 'logical', 'machine_learning', 'management', 'marketing', 'marxist_theory', 'modern_chinese', 'nutrition', 'philosophy', 'professional_accounting', 'professional_law', 'professional_medicine', 'professional_psychology', 'public_relations', 'security_study', 'sociology', 'sports_science', 'traditional_chinese_medicine', 'virology', 'world_history', 'world_religions'] from datasets import load_dataset cmmlu = {k: load_dataset(r"haonan-li/cmmlu", k) for k in task_list} ``` ## Citation ``` @misc{li2023cmmlu, title={CMMLU: Measuring massive multitask language understanding in Chinese}, author={Haonan Li and Yixuan Zhang and Fajri Koto and Yifei Yang and Hai Zhao and Yeyun Gong and Nan Duan and Timothy Baldwin}, year={2023}, eprint={2306.09212}, archivePrefix={arXiv}, primaryClass={cs.CL} } ``` ## License The CMMLU dataset is licensed under a [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/).

ai4bharat/sangraha

ai4bharat

--- license: cc-by-4.0 task_categories: - text-generation language: - as - bn - gu - en - hi - kn - ks - ml - mr - ne - or - pa - sa - sd - ta - te - ur tags: - language-modeling - casual-lm - llm pretty_name: sangraha dataset_info: - config_name: verified features: - name: doc_id dtype: string - name: type dtype: string - name: text dtype: string splits: - name: asm - name: ben - name: brx - name: doi - name: eng - name: gom - name: guj - name: hin - name: kan - name: kas - name: mai - name: mal - name: mar - name: mni - name: nep - name: ori - name: pan - name: san - name: sat - name: snd - name: tam - name: tel - name: urd - config_name: unverified features: - name: doc_id dtype: string - name: text dtype: string splits: - name: asm - name: ben - name: guj - name: hin - name: kan - name: mal - name: mar - name: nep - name: ori - name: pan - name: san - name: tam - name: tel - name: urd - config_name: synthetic features: - name: doc_id dtype: string - name: text dtype: string splits: - name: asm_Beng - name: asm_Latn - name: ben_Beng - name: ben_Latn - name: guj_Gujr - name: guj_Latn - name: hin_Deva - name: hin_Latn - name: kan_Knda - name: kan_Latn - name: mal_Mlym - name: mal_Latn - name: mar_Deva - name: mar_Latn - name: npi_Deva - name: npi_Latn - name: ory_Orya - name: ory_Latn - name: pan_Guru - name: pan_Latn - name: san_Deva - name: san_Latn - name: tam_Taml - name: tam_Latn - name: tel_Telu - name: tel_Latn - name: urd_Arab - name: urd_Latn configs: - config_name: verified data_files: - split: asm path: verified/asm/*.parquet - split: ben path: verified/ben/*.parquet - split: brx path: verified/brx/*.parquet - split: doi path: verified/doi/*.parquet - split: eng path: verified/eng/*.parquet - split: gom path: verified/gom/*.parquet - split: guj path: verified/guj/*.parquet - split: hin path: verified/hin/*.parquet - split: kan path: verified/kan/*.parquet - split: kas path: verified/kas/*.parquet - split: mai path: verified/mai/*.parquet - split: mal path: verified/mal/*.parquet - split: mar path: verified/mar/*.parquet - split: mni path: verified/mni/*.parquet - split: nep path: verified/nep/*.parquet - split: ori path: verified/ori/*.parquet - split: pan path: verified/pan/*.parquet - split: san path: verified/san/*.parquet - split: sat path: verified/sat/*.parquet - split: snd path: verified/snd/*.parquet - split: tam path: verified/tam/*.parquet - split: tel path: verified/tel/*.parquet - split: urd path: verified/urd/*.parquet - config_name: unverified data_files: - split: asm path: unverified/asm/*.parquet - split: ben path: unverified/ben/*.parquet - split: guj path: unverified/guj/*.parquet - split: hin path: unverified/hin/*.parquet - split: kan path: unverified/kan/*.parquet - split: mal path: unverified/mal/*.parquet - split: mar path: unverified/mar/*.parquet - split: nep path: unverified/nep/*.parquet - split: ori path: unverified/ori/*.parquet - split: pan path: unverified/pan/*.parquet - split: san path: unverified/san/*.parquet - split: tam path: unverified/tam/*.parquet - split: tel path: unverified/tel/*.parquet - split: urd path: unverified/urd/*.parquet - config_name: synthetic data_files: - split: asm_Beng path: synthetic/asm_Beng/*.parquet - split: asm_Latn path: synthetic/asm_Latn/*.parquet - split: ben_Beng path: synthetic/ben_Beng/*.parquet - split: ben_Latn path: synthetic/ben_Latn/*.parquet - split: guj_Gujr path: synthetic/guj_Gujr/*.parquet - split: guj_Latn path: synthetic/guj_Latn/*.parquet - split: hin_Deva path: synthetic/hin_Deva/*.parquet - split: hin_Latn path: synthetic/hin_Latn/*.parquet - split: kan_Knda path: synthetic/kan_Knda/*.parquet - split: kan_Latn path: synthetic/kan_Latn/*.parquet - split: mal_Mlym path: synthetic/mal_Mlym/*.parquet - split: mal_Latn path: synthetic/mal_Latn/*.parquet - split: mar_Deva path: synthetic/mar_Deva/*.parquet - split: mar_Latn path: synthetic/mar_Latn/*.parquet - split: npi_Deva path: synthetic/npi_Deva/*.parquet - split: npi_Latn path: synthetic/npi_Latn/*.parquet - split: ory_Orya path: synthetic/ory_Orya/*.parquet - split: ory_Latn path: synthetic/ory_Latn/*.parquet - split: pan_Guru path: synthetic/pan_Guru/*.parquet - split: pan_Latn path: synthetic/pan_Latn/*.parquet - split: san_Deva path: synthetic/san_Deva/*.parquet - split: san_Latn path: synthetic/san_Latn/*.parquet - split: tam_Taml path: synthetic/tam_Taml/*.parquet - split: tam_Latn path: synthetic/tam_Latn/*.parquet - split: tel_Telu path: synthetic/tel_Telu/*.parquet - split: tel_Latn path: synthetic/tel_Latn/*.parquet - split: urd_Arab path: synthetic/urd_Arab/*.parquet - split: urd_Latn path: synthetic/urd_Latn/*.parquet size_categories: - 100B<n<1T --- # Sangraha <p align="center"> <img src="https://cdn-uploads.huggingface.co/production/uploads/63ef3cd11e695b35aa48bebc/nDnyidcqIOLAP9dTw9GrK.png" /> </p> Sangraha is the largest high-quality, cleaned Indic language pretraining data containing 251B tokens summed up over 22 languages, extracted from curated sources, existing multilingual corpora and large scale translations. **Coming Soon**: - Sangraha Synthetic - Translated and Romanised English Wikimedia data. - Sangraha Verified - Hindi YouTube transcribed data. **More information**: - For detailed information on the curation and cleaning process of Sangraha, please checkout our paper [on Arxiv](https://arxiv.org/abs/2403.06350); - Check out the scraping and cleaning pipelines used to curate Sangraha [on GitHub](https://github.com/AI4Bharat/IndicLLMSuite); ## Getting Started For downloading the entire Sangraha: ```python from datasets import load_dataset dataset = load_dataset("ai4bharat/sangraha") ``` For downloading a subset (Verified/Unverified) of Sangraha: ```python from datasets import load_dataset dataset = load_dataset("ai4bharat/sangraha", data_dir="<subset_name>") # for example: dataset = load_dataset("ai4bharat/sangraha", data_dir="verified") ``` For downloading one language from a subset of Sangraha: ```python from datasets import load_dataset dataset = load_dataset("ai4bharat/sangraha", data_dir="<subset_name>/<lang_code>") # for example: dataset = load_dataset("ai4bharat/sangraha", data_dir="verified/asm") ``` ## Background Sangraha contains three broad components: - **Sangraha Verified**: Containing scraped data from "human-verified" Websites, OCR-extracted data from high quality Indic language PDFs, transcribed data from various Indic language videos, podcasts, movies, courses, etc. - **Sangraha Unverfied**: High quality Indic language data extracted from existing multilingual corpora employing perplexity filtering using n-gram language models trained on Sangraha Verified. - **Sangraha Synthetic**: WikiMedia English translated to 14 Indic languages and further "romanised" from 14 languages by transliteration to English. ## Data Statistics | **Lang Code** | **Verified** | **Synthetic** | **Unverified** | **Total Tokens (in Millions)** | | ------------- | ------------ | ------------- | -------------- | ------------------------------ | | asm | 292.1 | 11,696.4 | 17.5 | 12,006.0 | | ben | 10,604.4 | 13,814.1 | 5,608.8 | 30,027.5 | | brx | 1.5 | - | - | 1.5 | | doi | 0.06 | - | - | 0.06 | | eng | 12,759.9 | - | - | 12,759.9 | | gom | 10.1 | - | - | 10.1 | | guj | 3,647.9 | 12,934.5 | 597.0 | 17,179.4 | | hin | 12,617.3 | 9,578.7 | 12,348.3 | 34,544.3 | | kan | 1,778.3 | 12,087.4 | 388.8 | 14,254.5 | | kas | 0.5 | - | - | 0.5 | | mai | 14.6 | - | - | 14.6 | | mal | 2,730.8 | 13,130.0 | 547.8 | 16,408.6 | | mar | 2,827.0 | 10,816.7 | 652.1 | 14,295.8 | | mni | 7.4 | - | - | 7.4 | | npi | 1,822.5 | 10,588.7 | 485.5 | 12,896.7 | | ori | 1,177.1 | 11,338.0 | 23.7 | 12,538.8 | | pan | 1,075.3 | 9,969.6 | 136.9 | 11,181.8 | | san | 1,329.0 | 13,553.5 | 9.8 | 14,892.3 | | sat | 0.3 | - | - | 0.3 | | snd | 258.2 | - | - | 258.2 | | tam | 3,985.1 | 11,859.3 | 1,515.9 | 17,360.3 | | urd | 3,658.1 | 9,415.8 | 1,328.2 | 14,402.1 | | tel | 3,706.8 | 11,924.5 | 647.4 | 16,278.7 | | **Total** | **64,306.1** | **162,707.9** | **24,307.7** | **251,321.0** | To cite Sangraha, please use: ``` @article{khan2024indicllmsuite, title = {IndicLLMSuite: A Blueprint for Creating Pre-training and Fine-Tuning Datasets for Indian Languages}, author = {Mohammed Safi Ur Rahman Khan and Priyam Mehta and Ananth Sankar and Umashankar Kumaravelan and Sumanth Doddapaneni and Suriyaprasaad G and Varun Balan G and Sparsh Jain and Anoop Kunchukuttan and Pratyush Kumar and Raj Dabre and Mitesh M. Khapra}, year = {2024}, journal = {arXiv preprint arXiv: 2403.06350} } ```

omegalabsinc/omega-voice

omegalabsinc

--- license: mit ---

mteb/sts14-sts

mteb

--- language: - en ---

HuggingFaceM4/Docmatix

HuggingFaceM4

--- language: - en license: mit size_categories: - 1M<n<10M task_categories: - visual-question-answering pretty_name: Docmatix tags: - docvqa configs: - config_name: images data_files: - split: train path: data/train-* - config_name: pdf data_files: - split: train path: pdf/train-* - config_name: zero-shot-exp data_files: - split: train path: zero-shot-exp/train-* - split: test path: zero-shot-exp/test-* dataset_info: - config_name: images features: - name: images sequence: image - name: texts list: - name: user dtype: string - name: assistant dtype: string - name: source dtype: string splits: - name: train num_bytes: 552957537722.77 num_examples: 1273215 download_size: 159404414330 dataset_size: 552957537722.77 - config_name: pdf features: - name: pdf dtype: binary - name: texts list: - name: user dtype: string - name: assistant dtype: string - name: source dtype: string splits: - name: train num_bytes: 458612867150 num_examples: 1273245 download_size: 431829972210 dataset_size: 458612867150 - config_name: zero-shot-exp features: - name: images sequence: image - name: texts list: - name: user dtype: string - name: assistant dtype: string - name: source dtype: string splits: - name: test num_bytes: 68900253.0 num_examples: 200 - name: train num_bytes: 578335690.5 num_examples: 1700 download_size: 642963847 dataset_size: 647235943.5 --- # Dataset Card for Docmatix  ## Dataset description Docmatix is part of the Idefics3 release (stay tuned). It is a massive dataset for Document Visual Question Answering that was used for the fine-tuning of the vision-language model Idefics3. ## Load the dataset To load the dataset, install the library `datasets` with `pip install datasets`. Then, ``` from datasets import load_dataset ds = load_dataset("HuggingFaceM4/Docmatix") ``` If you want the dataset to link to the pdf files as binaries instead of the images, do: ``` from datasets import load_dataset ds = load_dataset("HuggingFaceM4/Docmatix", "pdf") ``` ## Data fields An example of a sample looks as follows: ``` { "images" = [PIL.Image] "texts" = [ { "user": "What is the purpose of the Confirmation Statement mentioned in the document?", "assistant": "The purpose of the Confirmation Statement is to confirm that all information required to be delivered by the company to the registrar in relation to the confirmation period concerned has been delivered or is being delivered at the same time as the confirmation statement.", "source": "PDFA key: 244" }, { "user": "When was the filing received as per the document?", "assistant": "The filing was received for filing in Electronic Format on the 23/03/2021.", "source": "PDFA key: 244" }, ] } ``` In `images`, there is a list of up to 4 images, to be placed before the text. In `texts`, there is a conversation between a user and an assistant about the images that is represented by a list of turns. ## Comparison to other DocVQA datasets | Dataset | # images | # Q/A pairs | # tokens | |----------------------|----------|-------------|------------| | *Document visual question answering* | | **Docmatix** | **2,444,750**| **9,500,000** | **390,000,000**| | DocVQA | 10,189 | 39,463 | 337,829 | | TextCaps | 21,953 | 21,953 | 389,658 | | TextVQA | 21,953 | 34,602 | 181,918 | | ST-VQA | 17,247 | 23,121 | 127,846 | | OCR-VQA | 165,746 | 801,579 | 6,073,824 | | VisualMRC | 3,027 | 11,988 | 168,828 | | IAM | 5,663 | 5,663 | 144,216 | | InfoVQA | 2,118 | 10,074 | 61,048 | | Diagram image-to-text| 300 | 300 | 22,196 | # Citation **BibTeX:** ```bibtex @misc{laurençon2024building, title={Building and better understanding vision-language models: insights and future directions.}, author={Hugo Laurençon and Andrés Marafioti and Victor Sanh and Léo Tronchon}, year={2024}, eprint={2408.12637}, archivePrefix={arXiv}, primaryClass={cs.CV} } ```

HuggingFaceH4/Bespoke-Stratos-17k

HuggingFaceH4

--- dataset_info: features: - name: system dtype: string - name: conversations list: - name: from dtype: string - name: value dtype: string - name: messages list: - name: content dtype: string - name: role dtype: string splits: - name: train num_bytes: 595877505.594255 num_examples: 16610 - name: test num_bytes: 3587462.405745063 num_examples: 100 download_size: 253238353 dataset_size: 599464968.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* --- # Dataset card for Bespoke-Stratos-17k This dataset is a TRL-compatible version of [bespokelabs/Bespoke-Stratos-17k](https://huggingface.co/datasets/bespokelabs/Bespoke-Stratos-17k). Please refer to the source dataset for details.

mteb/sts13-sts

mteb

--- language: - en ---

google/IFEval

google

--- license: apache-2.0 task_categories: - text-generation language: - en pretty_name: IFEval --- # Dataset Card for IFEval <!-- Provide a quick summary of the dataset. --> ## Dataset Description - **Repository:** https://github.com/google-research/google-research/tree/master/instruction_following_eval - **Paper:** https://huggingface.co/papers/2311.07911 - **Leaderboard:** https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard - **Point of Contact:** [Le Hou]([email protected]) ### Dataset Summary This dataset contains the prompts used in the [Instruction-Following Eval (IFEval) benchmark](https://arxiv.org/abs/2311.07911) for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run: ```python from datasets import load_dataset ifeval = load_dataset("google/IFEval") ``` ### Supported Tasks and Leaderboards The IFEval dataset is designed for evaluating chat or instruction fine-tuned language models and is one of the core benchmarks used in the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard). ### Languages The data in IFEval are in English (BCP-47 en). ## Dataset Structure ### Data Instances An example of the `train` split looks as follows: ``` { "key": 1000, "prompt": 'Write a 300+ word summary of the wikipedia page "https://en.wikipedia.org/wiki/Raymond_III,_Count_of_Tripoli". Do not use any commas and highlight at least 3 sections that has titles in markdown format, for example *highlighted section part 1*, *highlighted section part 2*, *highlighted section part 3*.', "instruction_id_list": [ "punctuation:no_comma", "detectable_format:number_highlighted_sections", "length_constraints:number_words", ], "kwargs": [ { "num_highlights": None, "relation": None, "num_words": None, "num_placeholders": None, "prompt_to_repeat": None, "num_bullets": None, "section_spliter": None, "num_sections": None, "capital_relation": None, "capital_frequency": None, "keywords": None, "num_paragraphs": None, "language": None, "let_relation": None, "letter": None, "let_frequency": None, "end_phrase": None, "forbidden_words": None, "keyword": None, "frequency": None, "num_sentences": None, "postscript_marker": None, "first_word": None, "nth_paragraph": None, }, { "num_highlights": 3, "relation": None, "num_words": None, "num_placeholders": None, "prompt_to_repeat": None, "num_bullets": None, "section_spliter": None, "num_sections": None, "capital_relation": None, "capital_frequency": None, "keywords": None, "num_paragraphs": None, "language": None, "let_relation": None, "letter": None, "let_frequency": None, "end_phrase": None, "forbidden_words": None, "keyword": None, "frequency": None, "num_sentences": None, "postscript_marker": None, "first_word": None, "nth_paragraph": None, }, { "num_highlights": None, "relation": "at least", "num_words": 300, "num_placeholders": None, "prompt_to_repeat": None, "num_bullets": None, "section_spliter": None, "num_sections": None, "capital_relation": None, "capital_frequency": None, "keywords": None, "num_paragraphs": None, "language": None, "let_relation": None, "letter": None, "let_frequency": None, "end_phrase": None, "forbidden_words": None, "keyword": None, "frequency": None, "num_sentences": None, "postscript_marker": None, "first_word": None, "nth_paragraph": None, }, ], } ``` ### Data Fields The data fields are as follows: * `key`: A unique ID for the prompt. * `prompt`: Describes the task the model should perform. * `instruction_id_list`: An array of verifiable instructions. See Table 1 of the paper for the full set with their descriptions. * `kwargs`: An array of arguments used to specify each verifiable instruction in `instruction_id_list`. ### Data Splits | | train | |---------------|------:| | IFEval | 541 | ### Licensing Information The dataset is available under the [Apache 2.0 license](https://www.apache.org/licenses/LICENSE-2.0). ### Citation Information ``` @misc{zhou2023instructionfollowingevaluationlargelanguage, title={Instruction-Following Evaluation for Large Language Models}, author={Jeffrey Zhou and Tianjian Lu and Swaroop Mishra and Siddhartha Brahma and Sujoy Basu and Yi Luan and Denny Zhou and Le Hou}, year={2023}, eprint={2311.07911}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2311.07911}, } ```

stochastic/random_streetview_images_pano_v0.0.2

stochastic

--- annotations_creators: - expert-generated language: [] language_creators: - expert-generated license: - mit multilinguality: - multilingual pretty_name: panoramic, street view images of random places on Earth size_categories: - 10K<n<100K source_datasets: - original tags: [] task_categories: - image-classification task_ids: - multi-label-image-classification --- # Dataset Card for panoramic street view images (v.0.0.2) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** - **Paper:** - **Leaderboard:** - **Point of Contact:** ### Dataset Summary The random streetview images dataset are labeled, panoramic images scraped from randomstreetview.com. Each image shows a location accessible by Google Streetview that has been roughly combined to provide ~360 degree view of a single location. The dataset was designed with the intent to geolocate an image purely based on its visual content. ### Supported Tasks and Leaderboards None as of now! ### Languages labels: Addresses are written in a combination of English and the official language of country they belong to. images: There are some images with signage that can contain a language. Albeit, they are less common. ## Dataset Structure For now, images exist exclusively in the `train` split and it is at the user's discretion to split the dataset how they please. ### Data Instances For each instance, there is: - timestamped file name: '{YYYYMMDD}_{address}.jpg` - the image - the country iso-alpha2 code - the latitude - the longitude - the address Fore more examples see the [dataset viewer](https://huggingface.co/datasets/stochastic/random_streetview_images_pano_v0.0.2/viewer/stochastic--random_streetview_images_pano_v0.0.2/train) ``` { filename: '20221001_Jarše Slovenia_46.1069942_14.9378597.jpg' country_iso_alpha2 : 'SI' latitude: '46.028223' longitude: '14.345106' address: 'Jarše Slovenia_46.1069942_14.9378597' } ``` ### Data Fields - country_iso_alpha2: a unique 2 character code for each country in the world following the ISO 3166 standard - latitude: the angular distance of a place north or south of the earth's equator - longitude: the angular distance of a place east or west of the standard meridian of the Earth - address: the physical address written from most micro -> macro order (Street, Neighborhood, City, State, Country) ### Data Splits 'train': all images are currently contained in the 'train' split ## Dataset Creation ### Curation Rationale Google StreetView Images [requires money per image scraped](https://developers.google.com/maps/documentation/streetview/usage-and-billing). This dataset provides about 10,000 of those images for free. ### Source Data #### Who are the source image producers? Google Street View provide the raw image, this dataset combined various cuts of the images into a panoramic. [More Information Needed] ### Annotations #### Annotation process The address, latitude, and longitude are all scraped from the API response. While portions of the data has been manually validated, the assurance in accuracy is based on the correctness of the API response. ### Personal and Sensitive Information While Google Street View does blur out images and license plates to the best of their ability, it is not guaranteed as can been seen in some photos. Please review [Google's documentation](https://www.google.com/streetview/policy/) for more information ## Considerations for Using the Data ### Social Impact of Dataset This dataset was designed after inspiration from playing the popular online game, [geoguessr.com[(geoguessr.com). We ask that users of this dataset consider if their geolocation based application will harm or jeopardize any fair institution or system. ### Discussion of Biases Out of the ~195 countries that exists, this dataset only contains images from about 55 countries. Each country has an average of 175 photos, with some countries having slightly less. The 55 countries are: ["ZA","KR","AR","BW","GR","SK","HK","NL","PE","AU","KH","LT","NZ","RO","MY","SG","AE","FR","ES","IT","IE","LV","IL","JP","CH","AD","CA","RU","NO","SE","PL","TW","CO","BD","HU","CL","IS","BG","GB","US","SI","BT","FI","BE","EE","SZ","UA","CZ","BR","DK","ID","MX","DE","HR","PT","TH"] In terms of continental representation: | continent | Number of Countries Represented | |:-----------------------| -------------------------------:| | Europe | 30 | | Asia | 13 | | South America | 5 | | Africa | 3 | | North America | 3 | | Oceania | 2 | This is not a fair representation of the world and its various climates, neighborhoods, and overall place. But it's a start! ### Other Known Limitations As per [Google's policy](https://www.google.com/streetview/policy/): __"Street View imagery shows only what our cameras were able to see on the day that they passed by the location. Afterwards, it takes months to process them. This means that content you see could be anywhere from a few months to a few years old."__ ### Licensing Information MIT License ### Citation Information ### Contributions Thanks to [@WinsonTruong](https://github.com/WinsonTruong) and [@ David Hrachovy](https://github.com/dayweek) for helping developing this dataset. This dataset was developed for a Geolocator project with the aforementioned developers, [@samhita-alla](https://github.com/samhita-alla) and [@yiyixuxu](https://github.com/yiyixuxu). Thanks to [FSDL](https://fullstackdeeplearning.com) for a wonderful class and online cohort.

ptb-text-only/ptb_text_only

ptb-text-only

--- annotations_creators: - expert-generated language_creators: - found language: - en license: - other license_details: LDC User Agreement for Non-Members multilinguality: - monolingual size_categories: - 10K<n<100K source_datasets: - original task_categories: - text-generation - fill-mask task_ids: - language-modeling - masked-language-modeling paperswithcode_id: null pretty_name: Penn Treebank dataset_info: features: - name: sentence dtype: string config_name: penn_treebank splits: - name: train num_bytes: 5143706 num_examples: 42068 - name: test num_bytes: 453710 num_examples: 3761 - name: validation num_bytes: 403156 num_examples: 3370 download_size: 5951345 dataset_size: 6000572 --- # Dataset Card for Penn Treebank ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** https://catalog.ldc.upenn.edu/LDC99T42 - **Repository:** 'https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.train.txt', 'https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.valid.txt', 'https://raw.githubusercontent.com/wojzaremba/lstm/master/data/ptb.test.txt' - **Paper:** https://www.aclweb.org/anthology/J93-2004.pdf - **Leaderboard:** [Needs More Information] - **Point of Contact:** [Needs More Information] ### Dataset Summary This is the Penn Treebank Project: Release 2 CDROM, featuring a million words of 1989 Wall Street Journal material. The rare words in this version are already replaced with <unk> token. The numbers are replaced with <N> token. ### Supported Tasks and Leaderboards Language Modelling ### Languages The text in the dataset is in American English ## Dataset Structure ### Data Instances [Needs More Information] ### Data Fields [Needs More Information] ### Data Splits [Needs More Information] ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases [Needs More Information] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators [Needs More Information] ### Licensing Information Dataset provided for research purposes only. Please check dataset license for additional information. ### Citation Information @article{marcus-etal-1993-building, title = "Building a Large Annotated Corpus of {E}nglish: The {P}enn {T}reebank", author = "Marcus, Mitchell P. and Santorini, Beatrice and Marcinkiewicz, Mary Ann", journal = "Computational Linguistics", volume = "19", number = "2", year = "1993", url = "https://www.aclweb.org/anthology/J93-2004", pages = "313--330", } ### Contributions Thanks to [@harshalmittal4](https://github.com/harshalmittal4) for adding this dataset.

lmms-lab/GQA

lmms-lab

--- license: mit dataset_info: - config_name: challenge_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: challenge num_bytes: 261636425.25 num_examples: 1590 download_size: 261271928 dataset_size: 261636425.25 - config_name: challenge_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: isBalanced dtype: bool splits: - name: challenge num_bytes: 50797705 num_examples: 713449 download_size: 19869828 dataset_size: 50797705 - config_name: challenge_balanced_images features: - name: id dtype: string - name: image dtype: image splits: - name: challenge num_bytes: 261636425.25 num_examples: 1590 download_size: 261333538 dataset_size: 261636425.25 - config_name: challenge_balanced_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: isBalanced dtype: bool splits: - name: challenge num_bytes: 3523973 num_examples: 50726 download_size: 1787024 dataset_size: 3523973 - config_name: submission_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: submission num_bytes: 2314978438.875 num_examples: 15545 download_size: 2309217874 dataset_size: 2314978438.875 - config_name: submission_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: isBalanced dtype: bool splits: - name: submission num_bytes: 298875520 num_examples: 4237524 download_size: 121458425 dataset_size: 298875520 - config_name: test_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: test num_bytes: 492571840.875 num_examples: 2993 download_size: 491611526 dataset_size: 492571840.875 - config_name: test_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: isBalanced dtype: bool splits: - name: test num_bytes: 95588974 num_examples: 1340048 download_size: 39561711 dataset_size: 95588974 - config_name: test_balanced_images features: - name: id dtype: string - name: image dtype: image splits: - name: test num_bytes: 491210370.625 num_examples: 2987 download_size: 490293506 dataset_size: 491210370.625 - config_name: test_balanced_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: isBalanced dtype: bool splits: - name: test num_bytes: 6622775 num_examples: 95336 download_size: 3401070 dataset_size: 6622775 - config_name: testdev_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: testdev num_bytes: 65779269.0 num_examples: 398 download_size: 65670255 dataset_size: 65779269.0 - config_name: testdev_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: testdev num_bytes: 86970760 num_examples: 172174 download_size: 23385535 dataset_size: 86970760 - config_name: testdev_balanced_images features: - name: id dtype: string - name: image dtype: image splits: - name: testdev num_bytes: 65779269.0 num_examples: 398 download_size: 65647745 dataset_size: 65779269.0 - config_name: testdev_balanced_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: testdev num_bytes: 6113469 num_examples: 12578 download_size: 2090335 dataset_size: 6113469 - config_name: train_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: train num_bytes: 10509758457.0 num_examples: 74256 download_size: 10480239090 dataset_size: 10509758457.0 - config_name: train_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: train num_bytes: 6891129609 num_examples: 14305356 download_size: 1874173198 dataset_size: 6891129609 - config_name: train_balanced_images features: - name: id dtype: string - name: image dtype: image splits: - name: train num_bytes: 10200292415.5 num_examples: 72140 download_size: 10171627271 dataset_size: 10200292415.5 - config_name: train_balanced_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: train num_bytes: 460429581 num_examples: 943000 download_size: 183979778 dataset_size: 460429581 - config_name: val_all_images features: - name: id dtype: string - name: image dtype: image splits: - name: val num_bytes: 1494990904.5 num_examples: 10564 download_size: 1490744689 dataset_size: 1494990904.5 - config_name: val_all_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: val num_bytes: 967338322 num_examples: 2011853 download_size: 266476025 dataset_size: 967338322 - config_name: val_balanced_images features: - name: id dtype: string - name: image dtype: image splits: - name: val num_bytes: 1447074448.75 num_examples: 10234 download_size: 1443033919 dataset_size: 1447074448.75 - config_name: val_balanced_instructions features: - name: id dtype: string - name: imageId dtype: string - name: question dtype: string - name: answer dtype: string - name: fullAnswer dtype: string - name: isBalanced dtype: bool - name: groups struct: - name: global dtype: string - name: local dtype: string - name: entailed dtype: string - name: equivalent dtype: string - name: types struct: - name: structural dtype: string - name: semantic dtype: string - name: detailed dtype: string - name: annotations sequence: - name: question struct: - name: objectId dtype: string - name: value dtype: string - name: answer struct: - name: objectId dtype: string - name: value dtype: string - name: fullAnswer struct: - name: objectId dtype: string - name: value dtype: string - name: semantic list: - name: operation dtype: string - name: argument dtype: string - name: dependencies sequence: int32 - name: semanticStr dtype: string splits: - name: val num_bytes: 64498952 num_examples: 132062 download_size: 25794272 dataset_size: 64498952 configs: - config_name: challenge_all_images data_files: - split: challenge path: challenge_all_images/challenge-* - config_name: challenge_all_instructions data_files: - split: challenge path: challenge_all_instructions/challenge-* - config_name: challenge_balanced_images data_files: - split: challenge path: challenge_balanced_images/challenge-* - config_name: challenge_balanced_instructions data_files: - split: challenge path: challenge_balanced_instructions/challenge-* - config_name: submission_all_images data_files: - split: submission path: submission_all_images/submission-* - config_name: submission_all_instructions data_files: - split: submission path: submission_all_instructions/submission-* - config_name: test_all_images data_files: - split: test path: test_all_images/test-* - config_name: test_all_instructions data_files: - split: test path: test_all_instructions/test-* - config_name: test_balanced_images data_files: - split: test path: test_balanced_images/test-* - config_name: test_balanced_instructions data_files: - split: test path: test_balanced_instructions/test-* - config_name: testdev_all_images data_files: - split: testdev path: testdev_all_images/testdev-* - config_name: testdev_all_instructions data_files: - split: testdev path: testdev_all_instructions/testdev-* - config_name: testdev_balanced_images data_files: - split: testdev path: testdev_balanced_images/testdev-* - config_name: testdev_balanced_instructions data_files: - split: testdev path: testdev_balanced_instructions/testdev-* - config_name: train_all_images data_files: - split: train path: train_all_images/train-* - config_name: train_all_instructions data_files: - split: train path: train_all_instructions/train-* - config_name: train_balanced_images data_files: - split: train path: train_balanced_images/train-* - config_name: train_balanced_instructions data_files: - split: train path: train_balanced_instructions/train-* - config_name: val_all_images data_files: - split: val path: val_all_images/val-* - config_name: val_all_instructions data_files: - split: val path: val_all_instructions/val-* - config_name: val_balanced_images data_files: - split: val path: val_balanced_images/val-* - config_name: val_balanced_instructions data_files: - split: val path: val_balanced_instructions/val-* --- <p align="center" width="100%"> <img src="https://i.postimg.cc/g0QRgMVv/WX20240228-113337-2x.png" width="100%" height="80%"> </p> # Large-scale Multi-modality Models Evaluation Suite > Accelerating the development of large-scale multi-modality models (LMMs) with `lmms-eval` 🏠 [Homepage](https://lmms-lab.github.io/) | 📚 [Documentation](docs/README.md) | 🤗 [Huggingface Datasets](https://huggingface.co/lmms-lab) # This Dataset This is a formatted version of [GQA](hhttps://cs.stanford.edu/people/dorarad/gqa/about.html). It is used in our `lmms-eval` pipeline to allow for one-click evaluations of large multi-modality models. ``` @inproceedings{hudson2019gqa, title={Gqa: A new dataset for real-world visual reasoning and compositional question answering}, author={Hudson, Drew A and Manning, Christopher D}, booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition}, pages={6700--6709}, year={2019} } ```

mlfoundations/MINT-1T-PDF-CC-2024-10

mlfoundations

--- license: cc-by-4.0 task_categories: - image-to-text - text-generation language: - en tags: - multimodal pretty_name: MINT-1T size_categories: - 100B<n<1T --- <h1 align="center"> 🍃 MINT-1T:<br>Scaling Open-Source Multimodal Data by 10x:<br> A Multimodal Dataset with One Trillion Tokens </h1> 🍃 MINT-1T is an open-source **M**ultimodal **INT**erleaved dataset with 1 trillion text tokens and 3.4 billion images, a 10x scale-up from existing open-source datasets. Additionally, we include previously untapped sources such as PDFs and ArXiv papers. 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. 🍃 MINT-1T is created by a team from the University of Washington in collaboration with Salesforce Research, other academic institutions including Stanford University, University of Texas at Austin, and University of California Berkeley. You are currently viewing a subset of the PDF portion of 🍃 MINT-1T associated with CommonCrawl dump `CC-2024-10`. For other PDF, HTML, and ArXiv subsets, refer to the [🍃 MINT-1T collection](https://huggingface.co/collections/mlfoundations/mint-1t-6690216ca4d0df7e518dde1c).  ## Updates ### 9/19/24 We have removed roughly 10% of the PDF samples as there was a mismatch between the frames in the TIFF images and the document metadata. ### 8/8/24 We have become aware that the image hashes in the PDF subset of MINT-1T do not match the images in the documents. We want to emphasize that the images for each document are correct, and only the image hashes in the documents' metadata are mislabeled. ## Dataset Details ### Dataset Sources - **Repository**: https://github.com/mlfoundations/MINT-1T - **Paper:** https://arxiv.org/abs/2406.11271 - **Blog:** https://blog.salesforceairesearch.com/mint-1t/ ## Uses ### Direct Use <!-- This section describes suitable use cases for the dataset. --> 🍃 MINT-1T is designed to facilitate research in multimodal pretraining. The dataset can be used for training multimodal models that can reson about interleaved text and images sequences such as [Idefics2](https://huggingface.co/HuggingFaceM4/idefics2-8b), [XGen-MM](https://huggingface.co/Salesforce/xgen-mm-phi3-mini-instruct-r-v1), and [Chameleon](https://huggingface.co/facebook/chameleon-30b). ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> 🍃 MINT-1T was built to make research into large multimodal models more accessible. Using the dataset to train models that ingest or generate personally identifying information (such as images of people’s faces and other sensitive content) as well as military applications are all inappropriate use cases of 🍃 MINT-1T. ## Dataset Creation ### Curation Rationale 🍃 MINT-1T was created to address a significant gap in the open-source domain by providing a large-scale multimodal interleaved dataset for pre-training large multimodal models. This dataset aims to be a valuable resource for the research community, facilitating open science in multimodal pretraining. ### Source Data The dataset is a comprehensive collection of multimodal documents from various sources: - HTML documents: Filtered from CommonCrawl WARC dumps spanning from 2017 to 2024 - PDF documents: Extracted from CommonCrawl WAT dumps covering 2023 to 2024 - ArXiv documents: A subset of papers from the ArXiv repository In total, 🍃 MINT-1T contains 1056.8 million documents, broken down as follows: - 1029.4 million HTML documents - 24.0 million PDF documents - 0.6 million ArXiv documents #### Data Collection and Processing The data collection and processing involved several steps: 1. Document Extraction: - HTML documents were parsed from CommonCrawl WARC files - PDF documents were extracted from CommonCrawl WAT files - ArXiv papers were directly sourced from ArXiv S3 buckets 2. Filtering Process: - Applied text quality filters to ensure content relevance and readability - Removed duplicate content at both paragraph and document levels - Filtered out undesirable content based on predefined criteria - Verified image availability and quality for HTML documents - Limited PDF size to 50MB and 50 pages to manage dataset size and quality 3. Image Processing: - Used NSFW image detection to remove pornographic or otherwise undesirable images - Removed images smaller than 150 pixels or larger than 20,000 pixels - Adjusted aspect ratio thresholds for HTML (2:1) and PDF (3:1) to preserve scientific figures 4. Text Processing: - Used fasttext for language identification, focusing on English content - Masked personally identifiable information such as email addresses and IP addresses - Applied paragraph and document-level deduplication using Bloom filters 5. PDF Specific Processing: - Used PyMuPDF for parsing PDFs and extracting reading order - Clustered text blocks based on columns and ordered from top left to bottom right 6. ArXiv Specific Processing: - Used TexSoup to parse LaTeX source code and interleave images with text - Cleaned up LaTeX code by removing imports, bibliography, tables, and citation tags Various open-source tools were utilized in this process, including fasttext, [PyMuPDF](https://github.com/pymupdf/PyMuPDF), and [DCLM](https://www.datacomp.ai/dclm/) and [bff](https://github.com/revbucket/bff) for deduplication and content filtering. #### Personal and Sensitive Information Despite sourcing from public web data, significant efforts were made to minimize the inclusion of personal and sensitive information: - Email addresses and IP addresses were masked to protect privacy - An NSFW image classifierto remove inappropriate visual content - URLs containing substrings associated with undesirable or sensitive content were filtered out However, users should be aware that as the data originates from the public web, it may still contain some sensitive or personal information. The dataset creators acknowledge this limitation and advise users to exercise caution and potentially apply additional filtering based on their specific use cases. ## Bias, Risks, and Limitations Several potential biases, risks, and limitations have been identified: 1. Data Bias: As the dataset is sourced from web crawls, it may inherit biases present in online content. 2. Content Risks: Despite extensive filtering, there's a possibility that some offensive, insensitive, or inappropriate content may remain in the dataset. 3. Image Availability: The dataset relies on external image URLs, which may become unavailable over time due to link rot, potentially affecting the dataset's long-term usability. 4. PDF Parsing Limitations: The current method for extracting reading order from PDFs may not always accurately capture the intended flow, especially for documents with complex layouts. 5. Potential Legal and Ethical Concerns: While efforts were made to respect robots.txt files and remove sensitive information, there may still be content that individuals did not explicitly consent to include. ### Recommendations Given these considerations, the following recommendations are provided: 1. Additional Filtering: Users are strongly encouraged to apply additional filtering based on their specific use case and ethical considerations. 2. Inappropriate Use Cases: The dataset is not recommended for applications involving the processing or generation of personally identifying information, nor for military applications. 3. Legal Compliance: Users should independently verify compliance with applicable laws before employing MINT-1T for commercial purposes. 4. Bias Awareness: Researchers and developers should be cognizant of potential biases in the dataset and consider their impact on model training and outputs. ## License We release 🍃 MINT-1T under a CC-BY-4.0 license, designating it primarily as a research artifact. While the dataset is freely available, users are responsible for ensuring its legal use in commercial settings. Users must independently verify compliance with applicable laws before employing MINT-1T for commercial purposes. ## Citation ``` @article{awadalla2024mint1t, title={MINT-1T: Scaling Open-Source Multimodal Data by 10x: A Multimodal Dataset with One Trillion Tokens}, author={Anas Awadalla and Le Xue and Oscar Lo and Manli Shu and Hannah Lee and Etash Kumar Guha and Matt Jordan and Sheng Shen and Mohamed Awadalla and Silvio Savarese and Caiming Xiong and Ran Xu and Yejin Choi and Ludwig Schmidt}, year={2024} } ```

asahi417/seamless-align-enA-esA.speaker-embedding.hubert-xl

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11746773654 num_examples: 2178 download_size: 11781544893 dataset_size: 11746773654 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11307338436 num_examples: 2228 download_size: 11341290257 dataset_size: 11307338436 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8904860486 num_examples: 2123 download_size: 8933746388 dataset_size: 8904860486 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8895621885 num_examples: 2123 download_size: 8924456769 dataset_size: 8895621885 - config_name: subset_102 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8640163870 num_examples: 2048 download_size: 8668862607 dataset_size: 8640163870 - config_name: subset_103 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8961420966 num_examples: 2082 download_size: 8990061075 dataset_size: 8961420966 - config_name: subset_104 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8976813498 num_examples: 2145 download_size: 9005760839 dataset_size: 8976813498 - config_name: subset_105 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8940344650 num_examples: 2129 download_size: 8969237447 dataset_size: 8940344650 - config_name: subset_106 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8799046787 num_examples: 2085 download_size: 8827709482 dataset_size: 8799046787 - config_name: subset_107 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8767571436 num_examples: 2102 download_size: 8796009483 dataset_size: 8767571436 - config_name: subset_108 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8996873761 num_examples: 2143 download_size: 9025863460 dataset_size: 8996873761 - config_name: subset_109 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8829602699 num_examples: 2104 download_size: 8857544194 dataset_size: 8829602699 - config_name: subset_11 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11303808414 num_examples: 2233 download_size: 11337546008 dataset_size: 11303808414 - config_name: subset_110 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8755759500 num_examples: 2088 download_size: 8783313768 dataset_size: 8755759500 - config_name: subset_111 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - 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name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8950674233 num_examples: 2124 download_size: 8979445797 dataset_size: 8950674233 - config_name: subset_95 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9158178699 num_examples: 2160 download_size: 9188356092 dataset_size: 9158178699 - config_name: subset_96 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9004804846 num_examples: 2132 download_size: 9034711320 dataset_size: 9004804846 - config_name: subset_97 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 9231165192 num_examples: 2163 download_size: 9261293967 dataset_size: 9231165192 - config_name: subset_98 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8706637274 num_examples: 2045 download_size: 8735273034 dataset_size: 8706637274 - config_name: subset_99 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: esA.id dtype: string - name: esA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: esA.audio.speaker_embedding sequence: float32 - name: esA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 8891359546 num_examples: 2070 download_size: 8920128045 dataset_size: 8891359546 configs: - config_name: subset_1 data_files: - split: train path: subset_1/train-* - config_name: subset_10 data_files: - split: train path: subset_10/train-* - 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config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

SammyLim/MUG-VOS

SammyLim

--- license: cc-by-4.0 ---

mlabonne/FineTome-100k

mlabonne

--- dataset_info: features: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: source dtype: string - name: score dtype: float64 splits: - name: train num_bytes: 239650960.7474458 num_examples: 100000 download_size: 116531415 dataset_size: 239650960.7474458 configs: - config_name: default data_files: - split: train path: data/train-* --- # FineTome-100k  The FineTome dataset is a subset of [arcee-ai/The-Tome](https://huggingface.co/datasets/arcee-ai/The-Tome) (without arcee-ai/qwen2-72b-magpie-en), re-filtered using [HuggingFaceFW/fineweb-edu-classifier](https://huggingface.co/HuggingFaceFW/fineweb-edu-classifier). It was made for my article ["Fine-tune Llama 3.1 Ultra-Efficiently with Unsloth"](https://huggingface.co/blog/mlabonne/sft-llama3).

MohamedRashad/arabic-books

MohamedRashad

--- license: gpl-3.0 task_categories: - text-generation language: - ar pretty_name: Arabic Books size_categories: - 1K<n<10K tags: - arabic - ocr - books - text-extraction - language-modeling - vision-transformers --- # Arabic Books ## Dataset Summary The `arabic-books` dataset contains **8,500 rows of text**, each representing the full text of a single Arabic book. These texts were extracted using the [arabic-large-nougat](https://huggingface.co/MohamedRashad/arabic-large-nougat) model, showcasing the model’s capabilities in Arabic OCR and text extraction. The dataset spans a total of **1.1 billion tokens**, calculated using the GPT-4 tokenizer. This dataset is a **testimony to the quality** of the Arabic Nougat models and their effectiveness in extracting structured text from complex Arabic documents. ## Research Context The dataset is part of the **Arabic Nougat** research project and supports the findings of the research paper: **[Arabic-Nougat: Fine-Tuning Vision Transformers for Arabic OCR and Markdown Extraction](https://huggingface.co/papers/2411.17835)**. ## Purpose This dataset is intended to: - Demonstrate the performance of Arabic Nougat models. - Serve as a resource for developing **Arabic language models** and advancing research in **Arabic NLP**. ## Licensing This dataset is released under the **GPL-3.0 License**, enabling its open-source availability for further research and development. ## Citation If you use this dataset, please cite the corresponding research paper: ```bibtex @misc{rashad2024arabicnougatfinetuningvisiontransformers, title={Arabic-Nougat: Fine-Tuning Vision Transformers for Arabic OCR and Markdown Extraction}, author={Mohamed Rashad}, year={2024}, eprint={2411.17835}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2411.17835}, } ```

gzzyyxy/layout_diffusion_hypersim

gzzyyxy

--- license: apache-2.0 dataset_info: features: - name: scene_id dtype: string - name: id dtype: string - name: target dtype: image - name: source dtype: string - name: source_image dtype: image - name: labels dtype: array2_d: shape: - 768 - 1024 dtype: int32 - name: cond_depths dtype: array2_d: shape: - 768 - 1024 dtype: float32 - name: extrin dtype: array2_d: shape: - 4 - 4 dtype: float32 - name: intrin dtype: array2_d: shape: - 4 - 4 dtype: float32 - name: depth dtype: string - name: item_id dtype: string - name: prompt dtype: string splits: - name: train num_bytes: 174198915504.862 num_examples: 24383 download_size: 80765512483 dataset_size: 174198915504.862 configs: - config_name: default data_files: - split: train path: data/train-* ---

lerobot/fmb

lerobot

--- license: cc-by-4.0 task_categories: - robotics tags: - LeRobot configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** https://functional-manipulation-benchmark.github.io/ - **Paper:** https://arxiv.org/abs/2401.08553 - **License:** cc-by-4.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "unknown", "total_episodes": 1804, "total_frames": 338188, "total_tasks": 24, "total_videos": 7216, "total_chunks": 2, "chunks_size": 1000, "fps": 10, "splits": { "train": "0:1804" }, "data_path": "data/chunk-{episode_chunk:03d}/episode_{episode_index:06d}.parquet", "video_path": "videos/chunk-{episode_chunk:03d}/{video_key}/episode_{episode_index:06d}.mp4", "features": { "observation.images.image_side_1": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 10.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.image_side_2": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 10.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.image_wrist_1": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 10.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.image_wrist_2": { "dtype": "video", "shape": [ 256, 256, 3 ], "names": [ "height", "width", "channel" ], "video_info": { "video.fps": 10.0, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "language_instruction": { "dtype": "string", "shape": [ 1 ], "names": null }, "observation.state": { "dtype": "float32", "shape": [ 8 ], "names": { "motors": [ "motor_0", "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6", "motor_7" ] } }, "action": { "dtype": "float32", "shape": [ 7 ], "names": { "motors": [ "motor_0", "motor_1", "motor_2", "motor_3", "motor_4", "motor_5", "motor_6" ] } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "next.reward": { "dtype": "float32", "shape": [ 1 ], "names": null }, "next.done": { "dtype": "bool", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex @article{luo2024fmb, title={FMB: a Functional Manipulation Benchmark for Generalizable Robotic Learning}, author={Luo, Jianlan and Xu, Charles and Liu, Fangchen and Tan, Liam and Lin, Zipeng and Wu, Jeffrey and Abbeel, Pieter and Levine, Sergey}, journal={arXiv preprint arXiv:2401.08553}, year={2024} } ```

Zaid/mmlu-random-D

Zaid

--- dataset_info: - config_name: abstract_algebra features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 21316 num_examples: 100 - name: validation num_bytes: 2232 num_examples: 11 - name: dev num_bytes: 918 num_examples: 5 download_size: 17175 dataset_size: 24466 - config_name: all features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 6967453 num_examples: 14042 - name: validation num_bytes: 763484 num_examples: 1531 - name: dev num_bytes: 125353 num_examples: 285 download_size: 3987560 dataset_size: 7856290 - config_name: anatomy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 34594 num_examples: 135 - name: validation num_bytes: 3282 num_examples: 14 - name: dev num_bytes: 1010 num_examples: 5 download_size: 28913 dataset_size: 38886 - config_name: astronomy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 48735 num_examples: 152 - name: validation num_bytes: 5223 num_examples: 16 - name: dev num_bytes: 2129 num_examples: 5 download_size: 39371 dataset_size: 56087 - config_name: business_ethics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 35140 num_examples: 100 - name: validation num_bytes: 3235 num_examples: 11 - name: dev num_bytes: 2273 num_examples: 5 download_size: 31636 dataset_size: 40648 - config_name: clinical_knowledge features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 68572 num_examples: 265 - name: validation num_bytes: 7290 num_examples: 29 - name: dev num_bytes: 1308 num_examples: 5 download_size: 51595 dataset_size: 77170 - config_name: college_biology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 51521 num_examples: 144 - name: validation num_bytes: 5111 num_examples: 16 - name: dev num_bytes: 1615 num_examples: 5 download_size: 42960 dataset_size: 58247 - config_name: college_chemistry features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 26796 num_examples: 100 - name: validation num_bytes: 2484 num_examples: 8 - name: dev num_bytes: 1424 num_examples: 5 download_size: 26817 dataset_size: 30704 - config_name: college_computer_science features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 45429 num_examples: 100 - name: validation num_bytes: 4959 num_examples: 11 - name: dev num_bytes: 2893 num_examples: 5 download_size: 40995 dataset_size: 53281 - config_name: college_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 26999 num_examples: 100 - name: validation num_bytes: 2909 num_examples: 11 - name: dev num_bytes: 1596 num_examples: 5 download_size: 26807 dataset_size: 31504 - config_name: college_medicine features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 85845 num_examples: 173 - name: validation num_bytes: 8337 num_examples: 22 - name: dev num_bytes: 1758 num_examples: 5 download_size: 56271 dataset_size: 95940 - config_name: college_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 32107 num_examples: 102 - name: validation num_bytes: 3687 num_examples: 11 - name: dev num_bytes: 1495 num_examples: 5 download_size: 29502 dataset_size: 37289 - config_name: computer_security features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 29212 num_examples: 100 - name: validation num_bytes: 4768 num_examples: 11 - name: dev num_bytes: 1194 num_examples: 5 download_size: 30167 dataset_size: 35174 - config_name: conceptual_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 45867 num_examples: 235 - name: validation num_bytes: 5034 num_examples: 26 - name: dev num_bytes: 1032 num_examples: 5 download_size: 34887 dataset_size: 51933 - config_name: econometrics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 48359 num_examples: 114 - name: validation num_bytes: 5147 num_examples: 12 - name: dev num_bytes: 1712 num_examples: 5 download_size: 36018 dataset_size: 55218 - config_name: electrical_engineering features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 28900 num_examples: 145 - name: validation num_bytes: 3307 num_examples: 16 - name: dev num_bytes: 1090 num_examples: 5 download_size: 26719 dataset_size: 33297 - config_name: elementary_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 79924 num_examples: 378 - name: validation num_bytes: 10042 num_examples: 41 - name: dev num_bytes: 1558 num_examples: 5 download_size: 54899 dataset_size: 91524 - config_name: formal_logic features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 51789 num_examples: 126 - name: validation num_bytes: 6464 num_examples: 14 - name: dev num_bytes: 1825 num_examples: 5 download_size: 32818 dataset_size: 60078 - config_name: global_facts features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 19991 num_examples: 100 - name: validation num_bytes: 2013 num_examples: 10 - name: dev num_bytes: 1297 num_examples: 5 download_size: 19296 dataset_size: 23301 - config_name: high_school_biology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 116850 num_examples: 310 - name: validation num_bytes: 11746 num_examples: 32 - name: dev num_bytes: 1776 num_examples: 5 download_size: 78207 dataset_size: 130372 - config_name: high_school_chemistry features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 63527 num_examples: 203 - name: validation num_bytes: 7630 num_examples: 22 - name: dev num_bytes: 1333 num_examples: 5 download_size: 45776 dataset_size: 72490 - config_name: high_school_computer_science features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 47664 num_examples: 100 - name: validation num_bytes: 3619 num_examples: 9 - name: dev num_bytes: 3066 num_examples: 5 download_size: 39051 dataset_size: 54349 - config_name: high_school_european_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 275568 num_examples: 165 - name: validation num_bytes: 30196 num_examples: 18 - name: dev num_bytes: 11712 num_examples: 5 download_size: 196187 dataset_size: 317476 - config_name: high_school_geography features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 46972 num_examples: 198 - name: validation num_bytes: 4870 num_examples: 22 - name: dev num_bytes: 1516 num_examples: 5 download_size: 38167 dataset_size: 53358 - config_name: high_school_government_and_politics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 73589 num_examples: 193 - name: validation num_bytes: 7870 num_examples: 21 - name: dev num_bytes: 1962 num_examples: 5 download_size: 52709 dataset_size: 83421 - config_name: high_school_macroeconomics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 129375 num_examples: 390 - name: validation num_bytes: 14298 num_examples: 43 - name: dev num_bytes: 1466 num_examples: 5 download_size: 68739 dataset_size: 145139 - config_name: high_school_mathematics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 62132 num_examples: 270 - name: validation num_bytes: 6536 num_examples: 29 - name: dev num_bytes: 1420 num_examples: 5 download_size: 45161 dataset_size: 70088 - config_name: high_school_microeconomics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 82831 num_examples: 238 - name: validation num_bytes: 8321 num_examples: 26 - name: dev num_bytes: 1436 num_examples: 5 download_size: 49862 dataset_size: 92588 - config_name: high_school_physics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 62999 num_examples: 151 - name: validation num_bytes: 7150 num_examples: 17 - name: dev num_bytes: 1592 num_examples: 5 download_size: 45477 dataset_size: 71741 - config_name: high_school_psychology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 173565 num_examples: 545 - name: validation num_bytes: 18817 num_examples: 60 - name: dev num_bytes: 2023 num_examples: 5 download_size: 113176 dataset_size: 194405 - config_name: high_school_statistics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 116306 num_examples: 216 - name: validation num_bytes: 10583 num_examples: 23 - name: dev num_bytes: 2646 num_examples: 5 download_size: 74889 dataset_size: 129535 - config_name: high_school_us_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 302026 num_examples: 204 - name: validation num_bytes: 32266 num_examples: 22 - name: dev num_bytes: 8982 num_examples: 5 download_size: 200004 dataset_size: 343274 - config_name: high_school_world_history features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 385478 num_examples: 237 - name: validation num_bytes: 46243 num_examples: 26 - name: dev num_bytes: 5015 num_examples: 5 download_size: 250096 dataset_size: 436736 - config_name: human_aging features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 49431 num_examples: 223 - name: validation num_bytes: 5040 num_examples: 23 - name: dev num_bytes: 1071 num_examples: 5 download_size: 41078 dataset_size: 55542 - config_name: human_sexuality features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 34587 num_examples: 131 - name: validation num_bytes: 2637 num_examples: 12 - name: dev num_bytes: 1160 num_examples: 5 download_size: 32475 dataset_size: 38384 - config_name: international_law features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 56060 num_examples: 121 - name: validation num_bytes: 6734 num_examples: 13 - name: dev num_bytes: 2511 num_examples: 5 download_size: 41611 dataset_size: 65305 - config_name: jurisprudence features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 35810 num_examples: 108 - name: validation num_bytes: 3904 num_examples: 11 - name: dev num_bytes: 1376 num_examples: 5 download_size: 33493 dataset_size: 41090 - config_name: logical_fallacies features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 53528 num_examples: 163 - name: validation num_bytes: 5469 num_examples: 18 - name: dev num_bytes: 1666 num_examples: 5 download_size: 33750 dataset_size: 60663 - config_name: machine_learning features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 36108 num_examples: 112 - name: validation num_bytes: 3440 num_examples: 11 - name: dev num_bytes: 2411 num_examples: 5 download_size: 31123 dataset_size: 41959 - config_name: management features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 21432 num_examples: 103 - name: validation num_bytes: 1962 num_examples: 11 - name: dev num_bytes: 956 num_examples: 5 download_size: 22820 dataset_size: 24350 - config_name: marketing features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 66055 num_examples: 234 - name: validation num_bytes: 7707 num_examples: 25 - name: dev num_bytes: 1534 num_examples: 5 download_size: 49659 dataset_size: 75296 - config_name: medical_genetics features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 22852 num_examples: 100 - name: validation num_bytes: 3213 num_examples: 11 - name: dev num_bytes: 1177 num_examples: 5 download_size: 25747 dataset_size: 27242 - config_name: miscellaneous features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 161003 num_examples: 783 - name: validation num_bytes: 15780 num_examples: 86 - name: dev num_bytes: 772 num_examples: 5 download_size: 114887 dataset_size: 177555 - config_name: moral_disputes features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 114034 num_examples: 346 - name: validation num_bytes: 13092 num_examples: 38 - name: dev num_bytes: 1833 num_examples: 5 download_size: 75948 dataset_size: 128959 - config_name: moral_scenarios features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 391019 num_examples: 895 - name: validation num_bytes: 44226 num_examples: 100 - name: dev num_bytes: 2141 num_examples: 5 download_size: 110527 dataset_size: 437386 - config_name: nutrition features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 96376 num_examples: 306 - name: validation num_bytes: 8853 num_examples: 33 - name: dev num_bytes: 2138 num_examples: 5 download_size: 68962 dataset_size: 107367 - config_name: philosophy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 84415 num_examples: 311 - name: validation num_bytes: 9648 num_examples: 34 - name: dev num_bytes: 1046 num_examples: 5 download_size: 61848 dataset_size: 95109 - config_name: prehistory features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 94118 num_examples: 324 - name: validation num_bytes: 10763 num_examples: 35 - name: dev num_bytes: 1936 num_examples: 5 download_size: 68915 dataset_size: 106817 - config_name: professional_accounting features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 132152 num_examples: 282 - name: validation num_bytes: 15197 num_examples: 31 - name: dev num_bytes: 2271 num_examples: 5 download_size: 87270 dataset_size: 149620 - config_name: professional_law features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 1922430 num_examples: 1534 - name: validation num_bytes: 206907 num_examples: 170 - name: dev num_bytes: 6698 num_examples: 5 download_size: 1167820 dataset_size: 2136035 - config_name: professional_medicine features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 224349 num_examples: 272 - name: validation num_bytes: 24610 num_examples: 31 - name: dev num_bytes: 3920 num_examples: 5 download_size: 153239 dataset_size: 252879 - config_name: professional_psychology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 242411 num_examples: 612 - name: validation num_bytes: 30952 num_examples: 69 - name: dev num_bytes: 2390 num_examples: 5 download_size: 159276 dataset_size: 275753 - config_name: public_relations features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 30948 num_examples: 110 - name: validation num_bytes: 4794 num_examples: 12 - name: dev num_bytes: 1584 num_examples: 5 download_size: 31405 dataset_size: 37326 - config_name: security_studies features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 209732 num_examples: 245 - name: validation num_bytes: 23165 num_examples: 27 - name: dev num_bytes: 5423 num_examples: 5 download_size: 140017 dataset_size: 238320 - config_name: sociology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 68844 num_examples: 201 - name: validation num_bytes: 7458 num_examples: 22 - name: dev num_bytes: 1666 num_examples: 5 download_size: 56407 dataset_size: 77968 - config_name: us_foreign_policy features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 30531 num_examples: 100 - name: validation num_bytes: 3483 num_examples: 11 - name: dev num_bytes: 1704 num_examples: 5 download_size: 28993 dataset_size: 35718 - config_name: virology features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 40739 num_examples: 166 - name: validation num_bytes: 5667 num_examples: 18 - name: dev num_bytes: 1144 num_examples: 5 download_size: 38179 dataset_size: 47550 - config_name: world_religions features: - name: question dtype: string - name: subject dtype: string - name: choices sequence: string - name: answer dtype: class_label: names: '0': A '1': B '2': C '3': D splits: - name: test num_bytes: 28511 num_examples: 171 - name: validation num_bytes: 3114 num_examples: 19 - name: dev num_bytes: 753 num_examples: 5 download_size: 27099 dataset_size: 32378 configs: - config_name: abstract_algebra data_files: - split: test path: abstract_algebra/test-* - split: validation path: abstract_algebra/validation-* - split: dev path: abstract_algebra/dev-* - config_name: all data_files: - split: test path: all/test-* - split: validation path: all/validation-* - split: dev path: all/dev-* - config_name: anatomy data_files: - split: test path: anatomy/test-* - split: validation path: anatomy/validation-* - split: dev path: anatomy/dev-* - config_name: astronomy data_files: - split: test path: astronomy/test-* - split: validation path: astronomy/validation-* - split: dev path: astronomy/dev-* - config_name: business_ethics data_files: - split: test path: business_ethics/test-* - split: validation path: business_ethics/validation-* - split: dev path: business_ethics/dev-* - config_name: clinical_knowledge data_files: - split: test path: clinical_knowledge/test-* - split: validation path: clinical_knowledge/validation-* - split: dev path: clinical_knowledge/dev-* - config_name: college_biology data_files: - split: test path: college_biology/test-* - split: validation path: college_biology/validation-* - split: dev path: college_biology/dev-* - config_name: college_chemistry data_files: - split: test path: college_chemistry/test-* - split: validation path: college_chemistry/validation-* - split: dev path: college_chemistry/dev-* - config_name: college_computer_science data_files: - split: test path: college_computer_science/test-* - split: validation path: college_computer_science/validation-* - split: dev path: college_computer_science/dev-* - config_name: college_mathematics data_files: - split: test path: college_mathematics/test-* - split: validation path: college_mathematics/validation-* - split: dev path: college_mathematics/dev-* - config_name: college_medicine data_files: - split: test path: college_medicine/test-* - split: validation path: college_medicine/validation-* - split: dev path: college_medicine/dev-* - config_name: college_physics data_files: - split: test path: college_physics/test-* - split: validation path: college_physics/validation-* - split: dev path: college_physics/dev-* - config_name: computer_security data_files: - split: test path: computer_security/test-* - split: validation path: computer_security/validation-* - split: dev path: computer_security/dev-* - config_name: conceptual_physics data_files: - split: test path: conceptual_physics/test-* - split: validation path: conceptual_physics/validation-* - split: dev path: conceptual_physics/dev-* - config_name: econometrics data_files: - split: test path: econometrics/test-* - split: validation path: econometrics/validation-* - split: dev path: econometrics/dev-* - config_name: electrical_engineering data_files: - split: test path: electrical_engineering/test-* - split: validation path: electrical_engineering/validation-* - split: dev path: electrical_engineering/dev-* - config_name: elementary_mathematics data_files: - split: test path: elementary_mathematics/test-* - split: validation path: elementary_mathematics/validation-* - split: dev path: elementary_mathematics/dev-* - config_name: formal_logic data_files: - split: test path: formal_logic/test-* - split: validation path: formal_logic/validation-* - split: dev path: formal_logic/dev-* - config_name: global_facts data_files: - split: test path: global_facts/test-* - split: validation path: global_facts/validation-* - split: dev path: global_facts/dev-* - config_name: high_school_biology data_files: - split: test path: high_school_biology/test-* - split: validation path: high_school_biology/validation-* - split: dev path: high_school_biology/dev-* - config_name: high_school_chemistry data_files: - split: test path: high_school_chemistry/test-* - split: validation path: high_school_chemistry/validation-* - split: dev path: high_school_chemistry/dev-* - config_name: high_school_computer_science data_files: - split: test path: high_school_computer_science/test-* - split: validation path: high_school_computer_science/validation-* - split: dev path: high_school_computer_science/dev-* - config_name: high_school_european_history data_files: - split: test path: high_school_european_history/test-* - split: validation path: high_school_european_history/validation-* - split: dev path: high_school_european_history/dev-* - config_name: high_school_geography data_files: - split: test path: high_school_geography/test-* - split: validation path: high_school_geography/validation-* - split: dev path: high_school_geography/dev-* - config_name: high_school_government_and_politics data_files: - split: test path: high_school_government_and_politics/test-* - split: validation path: high_school_government_and_politics/validation-* - split: dev path: high_school_government_and_politics/dev-* - config_name: high_school_macroeconomics data_files: - split: test path: high_school_macroeconomics/test-* - split: validation path: high_school_macroeconomics/validation-* - split: dev path: high_school_macroeconomics/dev-* - config_name: high_school_mathematics data_files: - split: test path: high_school_mathematics/test-* - split: validation path: high_school_mathematics/validation-* - split: dev path: high_school_mathematics/dev-* - config_name: high_school_microeconomics data_files: - split: test path: high_school_microeconomics/test-* - split: validation path: high_school_microeconomics/validation-* - split: dev path: high_school_microeconomics/dev-* - config_name: high_school_physics data_files: - split: test path: high_school_physics/test-* - split: validation path: high_school_physics/validation-* - split: dev path: high_school_physics/dev-* - config_name: high_school_psychology data_files: - split: test path: high_school_psychology/test-* - split: validation path: high_school_psychology/validation-* - split: dev path: high_school_psychology/dev-* - config_name: high_school_statistics data_files: - split: test path: high_school_statistics/test-* - split: validation path: high_school_statistics/validation-* - split: dev path: high_school_statistics/dev-* - config_name: high_school_us_history data_files: - split: test path: high_school_us_history/test-* - split: validation path: high_school_us_history/validation-* - split: dev path: high_school_us_history/dev-* - config_name: high_school_world_history data_files: - split: test path: high_school_world_history/test-* - split: validation path: high_school_world_history/validation-* - split: dev path: high_school_world_history/dev-* - config_name: human_aging data_files: - split: test path: human_aging/test-* - split: validation path: human_aging/validation-* - split: dev path: human_aging/dev-* - config_name: human_sexuality data_files: - split: test path: human_sexuality/test-* - split: validation path: human_sexuality/validation-* - split: dev path: human_sexuality/dev-* - config_name: international_law data_files: - split: test path: international_law/test-* - split: validation path: international_law/validation-* - split: dev path: international_law/dev-* - config_name: jurisprudence data_files: - split: test path: jurisprudence/test-* - split: validation path: jurisprudence/validation-* - split: dev path: jurisprudence/dev-* - config_name: logical_fallacies data_files: - split: test path: logical_fallacies/test-* - split: validation path: logical_fallacies/validation-* - split: dev path: logical_fallacies/dev-* - config_name: machine_learning data_files: - split: test path: machine_learning/test-* - split: validation path: machine_learning/validation-* - split: dev path: machine_learning/dev-* - config_name: management data_files: - split: test path: management/test-* - split: validation path: management/validation-* - split: dev path: management/dev-* - config_name: marketing data_files: - split: test path: marketing/test-* - split: validation path: marketing/validation-* - split: dev path: marketing/dev-* - config_name: medical_genetics data_files: - split: test path: medical_genetics/test-* - split: validation path: medical_genetics/validation-* - split: dev path: medical_genetics/dev-* - config_name: miscellaneous data_files: - split: test path: miscellaneous/test-* - split: validation path: miscellaneous/validation-* - split: dev path: miscellaneous/dev-* - config_name: moral_disputes data_files: - split: test path: moral_disputes/test-* - split: validation path: moral_disputes/validation-* - split: dev path: moral_disputes/dev-* - config_name: moral_scenarios data_files: - split: test path: moral_scenarios/test-* - split: validation path: moral_scenarios/validation-* - split: dev path: moral_scenarios/dev-* - config_name: nutrition data_files: - split: test path: nutrition/test-* - split: validation path: nutrition/validation-* - split: dev path: nutrition/dev-* - config_name: philosophy data_files: - split: test path: philosophy/test-* - split: validation path: philosophy/validation-* - split: dev path: philosophy/dev-* - config_name: prehistory data_files: - split: test path: prehistory/test-* - split: validation path: prehistory/validation-* - split: dev path: prehistory/dev-* - config_name: professional_accounting data_files: - split: test path: professional_accounting/test-* - split: validation path: professional_accounting/validation-* - split: dev path: professional_accounting/dev-* - config_name: professional_law data_files: - split: test path: professional_law/test-* - split: validation path: professional_law/validation-* - split: dev path: professional_law/dev-* - config_name: professional_medicine data_files: - split: test path: professional_medicine/test-* - split: validation path: professional_medicine/validation-* - split: dev path: professional_medicine/dev-* - config_name: professional_psychology data_files: - split: test path: professional_psychology/test-* - split: validation path: professional_psychology/validation-* - split: dev path: professional_psychology/dev-* - config_name: public_relations data_files: - split: test path: public_relations/test-* - split: validation path: public_relations/validation-* - split: dev path: public_relations/dev-* - config_name: security_studies data_files: - split: test path: security_studies/test-* - split: validation path: security_studies/validation-* - split: dev path: security_studies/dev-* - config_name: sociology data_files: - split: test path: sociology/test-* - split: validation path: sociology/validation-* - split: dev path: sociology/dev-* - config_name: us_foreign_policy data_files: - split: test path: us_foreign_policy/test-* - split: validation path: us_foreign_policy/validation-* - split: dev path: us_foreign_policy/dev-* - config_name: virology data_files: - split: test path: virology/test-* - split: validation path: virology/validation-* - split: dev path: virology/dev-* - config_name: world_religions data_files: - split: test path: world_religions/test-* - split: validation path: world_religions/validation-* - split: dev path: world_religions/dev-* ---

EdinburghNLP/xsum

EdinburghNLP

--- annotations_creators: - found language_creators: - found language: - en license: - unknown multilinguality: - monolingual pretty_name: Extreme Summarization (XSum) paperswithcode_id: xsum size_categories: - 100K<n<1M source_datasets: - original task_categories: - summarization task_ids: - news-articles-summarization train-eval-index: - config: default task: summarization task_id: summarization splits: train_split: train eval_split: test col_mapping: document: text summary: target metrics: - type: rouge name: Rouge dataset_info: features: - name: document dtype: string - name: summary dtype: string - name: id dtype: string splits: - name: train num_bytes: 479206608 num_examples: 204045 - name: validation num_bytes: 26292901 num_examples: 11332 - name: test num_bytes: 26756165 num_examples: 11334 download_size: 257302866 dataset_size: 532255674 --- # Dataset Card for "xsum" ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** - **Repository:** https://github.com/EdinburghNLP/XSum - **Paper:** [Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization](https://arxiv.org/abs/1808.08745) - **Point of Contact:** [Shashi Narayan](mailto:[email protected]) - **Size of downloaded dataset files:** 257.30 MB - **Size of the generated dataset:** 532.26 MB - **Total amount of disk used:** 789.56 MB ### Dataset Summary Extreme Summarization (XSum) Dataset. There are three features: - document: Input news article. - summary: One sentence summary of the article. - id: BBC ID of the article. ### Supported Tasks and Leaderboards [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Languages [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Dataset Structure ### Data Instances #### default - **Size of downloaded dataset files:** 257.30 MB - **Size of the generated dataset:** 532.26 MB - **Total amount of disk used:** 789.56 MB An example of 'validation' looks as follows. ``` { "document": "some-body", "id": "29750031", "summary": "some-sentence" } ``` ### Data Fields The data fields are the same among all splits. #### default - `document`: a `string` feature. - `summary`: a `string` feature. - `id`: a `string` feature. ### Data Splits | name |train |validation|test | |-------|-----:|---------:|----:| |default|204045| 11332|11334| ## Dataset Creation ### Curation Rationale [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Source Data #### Initial Data Collection and Normalization [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the source language producers? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Annotations #### Annotation process [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) #### Who are the annotators? [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Personal and Sensitive Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Discussion of Biases [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Other Known Limitations [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ## Additional Information ### Dataset Curators [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Licensing Information [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards) ### Citation Information ``` @article{Narayan2018DontGM, title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization}, author={Shashi Narayan and Shay B. Cohen and Mirella Lapata}, journal={ArXiv}, year={2018}, volume={abs/1808.08745} } ``` ### Contributions Thanks to [@thomwolf](https://github.com/thomwolf), [@lewtun](https://github.com/lewtun), [@mariamabarham](https://github.com/mariamabarham), [@jbragg](https://github.com/jbragg), [@lhoestq](https://github.com/lhoestq), [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

asahi417/seamless-align-enA-frA.speaker-embedding.hubert-xl

asahi417

--- dataset_info: - config_name: subset_1 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11955579968 num_examples: 2343 download_size: 11991093037 dataset_size: 11955579968 - config_name: subset_10 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 11317113378 num_examples: 2334 download_size: 11351497820 dataset_size: 11317113378 - config_name: subset_100 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 10428107562 num_examples: 2309 download_size: 10460770910 dataset_size: 10428107562 - config_name: subset_101 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 10363930546 num_examples: 2322 download_size: 10396625318 dataset_size: 10363930546 - config_name: subset_102 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 10279156575 num_examples: 2291 download_size: 10311855742 dataset_size: 10279156575 - config_name: subset_103 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 10422395365 num_examples: 2321 download_size: 10455237447 dataset_size: 10422395365 - config_name: subset_104 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - name: frA.id dtype: string - name: frA.laser_score dtype: float64 - name: frA.audio.speaker_embedding sequence: float32 - name: frA.audio.speaker_embedding.full sequence: sequence: float32 - name: enA.audio.speaker_embedding sequence: float32 - name: enA.audio.speaker_embedding.full sequence: sequence: float32 splits: - name: train num_bytes: 10297763679 num_examples: 2314 download_size: 10330495704 dataset_size: 10297763679 - config_name: subset_105 features: - name: line_no dtype: int64 - name: enA.id dtype: string - name: enA.laser_score dtype: float64 - 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split: train path: subset_219/train-* - config_name: subset_22 data_files: - split: train path: subset_22/train-* - config_name: subset_220 data_files: - split: train path: subset_220/train-* - config_name: subset_221 data_files: - split: train path: subset_221/train-* - config_name: subset_222 data_files: - split: train path: subset_222/train-* - config_name: subset_223 data_files: - split: train path: subset_223/train-* - config_name: subset_224 data_files: - split: train path: subset_224/train-* - config_name: subset_225 data_files: - split: train path: subset_225/train-* - config_name: subset_226 data_files: - split: train path: subset_226/train-* - config_name: subset_227 data_files: - split: train path: subset_227/train-* - config_name: subset_228 data_files: - split: train path: subset_228/train-* - config_name: subset_229 data_files: - split: train path: subset_229/train-* - config_name: subset_23 data_files: - split: train path: subset_23/train-* - config_name: subset_230 data_files: - split: train path: subset_230/train-* - config_name: subset_231 data_files: - split: train path: subset_231/train-* - config_name: subset_232 data_files: - split: train path: subset_232/train-* - config_name: subset_233 data_files: - split: train path: subset_233/train-* - config_name: subset_234 data_files: - split: train path: subset_234/train-* - config_name: subset_235 data_files: - split: train path: subset_235/train-* - config_name: subset_236 data_files: - split: train path: subset_236/train-* - config_name: subset_237 data_files: - split: train path: subset_237/train-* - config_name: subset_238 data_files: - split: train path: subset_238/train-* - config_name: subset_239 data_files: - split: train path: subset_239/train-* - config_name: subset_24 data_files: - split: train path: subset_24/train-* - config_name: subset_240 data_files: - split: train path: subset_240/train-* - config_name: subset_241 data_files: - split: train path: subset_241/train-* - config_name: subset_242 data_files: - split: train path: subset_242/train-* - config_name: subset_243 data_files: - split: train path: subset_243/train-* - config_name: subset_244 data_files: - split: train path: subset_244/train-* - config_name: subset_245 data_files: - split: train path: subset_245/train-* - config_name: subset_246 data_files: - split: train path: subset_246/train-* - config_name: subset_247 data_files: - split: train path: subset_247/train-* - config_name: subset_248 data_files: - split: train path: subset_248/train-* - config_name: subset_249 data_files: - split: train path: subset_249/train-* - config_name: subset_25 data_files: - split: train path: subset_25/train-* - config_name: subset_250 data_files: - split: train path: subset_250/train-* - config_name: subset_251 data_files: - split: train path: subset_251/train-* - config_name: subset_252 data_files: - split: train path: subset_252/train-* - config_name: subset_253 data_files: - split: train path: subset_253/train-* - config_name: subset_254 data_files: - split: train path: subset_254/train-* - config_name: subset_255 data_files: - split: train path: subset_255/train-* - config_name: subset_256 data_files: - split: train path: subset_256/train-* - config_name: subset_257 data_files: - split: train path: subset_257/train-* - config_name: subset_258 data_files: - split: train path: subset_258/train-* - config_name: subset_259 data_files: - split: train path: subset_259/train-* - config_name: subset_26 data_files: - split: train path: subset_26/train-* - config_name: subset_260 data_files: - split: train path: subset_260/train-* - config_name: subset_261 data_files: - split: train path: subset_261/train-* - config_name: subset_262 data_files: - split: train path: subset_262/train-* - config_name: subset_263 data_files: - split: train path: subset_263/train-* - config_name: subset_264 data_files: - split: train path: subset_264/train-* - config_name: subset_265 data_files: - split: train path: subset_265/train-* - config_name: subset_266 data_files: - split: train path: subset_266/train-* - config_name: subset_267 data_files: - split: train path: subset_267/train-* - config_name: subset_268 data_files: - split: train path: subset_268/train-* - config_name: subset_269 data_files: - split: train path: subset_269/train-* - config_name: subset_27 data_files: - split: train path: subset_27/train-* - config_name: subset_270 data_files: - split: train path: subset_270/train-* - config_name: subset_271 data_files: - split: train path: subset_271/train-* - config_name: subset_272 data_files: - split: train path: subset_272/train-* - config_name: subset_273 data_files: - split: train path: subset_273/train-* - config_name: subset_274 data_files: - split: train path: subset_274/train-* - config_name: subset_275 data_files: - split: train path: subset_275/train-* - config_name: subset_276 data_files: - split: train path: subset_276/train-* - config_name: subset_277 data_files: - split: train path: subset_277/train-* - config_name: subset_278 data_files: - split: train path: subset_278/train-* - config_name: subset_279 data_files: - split: train path: subset_279/train-* - config_name: subset_28 data_files: - split: train path: subset_28/train-* - config_name: subset_280 data_files: - split: train path: subset_280/train-* - config_name: subset_281 data_files: - split: train path: subset_281/train-* - config_name: subset_282 data_files: - split: train path: subset_282/train-* - config_name: subset_283 data_files: - split: train path: subset_283/train-* - config_name: subset_284 data_files: - split: train path: subset_284/train-* - config_name: subset_285 data_files: - split: train path: subset_285/train-* - config_name: subset_286 data_files: - split: train path: subset_286/train-* - config_name: subset_287 data_files: - split: train path: subset_287/train-* - config_name: subset_288 data_files: - split: train path: subset_288/train-* - config_name: subset_289 data_files: - split: train path: subset_289/train-* - config_name: subset_29 data_files: - split: train path: subset_29/train-* - config_name: subset_290 data_files: - split: train path: subset_290/train-* - config_name: subset_291 data_files: - split: train path: subset_291/train-* - config_name: subset_292 data_files: - split: train path: subset_292/train-* - config_name: subset_293 data_files: - split: train path: subset_293/train-* - config_name: subset_294 data_files: - split: train path: subset_294/train-* - config_name: subset_295 data_files: - split: train path: subset_295/train-* - config_name: subset_296 data_files: - split: train path: subset_296/train-* - config_name: subset_297 data_files: - split: train path: subset_297/train-* - config_name: subset_298 data_files: - split: train path: subset_298/train-* - config_name: subset_299 data_files: - split: train path: subset_299/train-* - config_name: subset_3 data_files: - split: train path: subset_3/train-* - config_name: subset_30 data_files: - split: train path: subset_30/train-* - config_name: subset_300 data_files: - split: train path: subset_300/train-* - config_name: subset_301 data_files: - split: train path: subset_301/train-* - config_name: subset_302 data_files: - split: train path: subset_302/train-* - config_name: subset_303 data_files: - split: train path: subset_303/train-* - config_name: subset_304 data_files: - split: train path: subset_304/train-* - config_name: subset_305 data_files: - split: train path: subset_305/train-* - config_name: subset_306 data_files: - split: train path: subset_306/train-* - config_name: subset_307 data_files: - split: train path: subset_307/train-* - config_name: subset_308 data_files: - split: train path: subset_308/train-* - config_name: subset_309 data_files: - split: train path: subset_309/train-* - config_name: subset_31 data_files: - split: train path: subset_31/train-* - config_name: subset_310 data_files: - split: train path: subset_310/train-* - config_name: subset_311 data_files: - split: train path: subset_311/train-* - config_name: subset_312 data_files: - split: train path: subset_312/train-* - config_name: subset_313 data_files: - split: train path: subset_313/train-* - config_name: subset_314 data_files: - split: train path: subset_314/train-* - config_name: subset_315 data_files: - split: train path: subset_315/train-* - config_name: subset_316 data_files: - split: train path: subset_316/train-* - config_name: subset_317 data_files: - split: train path: subset_317/train-* - config_name: subset_318 data_files: - split: train path: subset_318/train-* - config_name: subset_319 data_files: - split: train path: subset_319/train-* - config_name: subset_32 data_files: - split: train path: subset_32/train-* - config_name: subset_320 data_files: - split: train path: subset_320/train-* - config_name: subset_321 data_files: - split: train path: subset_321/train-* - config_name: subset_322 data_files: - split: train path: subset_322/train-* - config_name: subset_323 data_files: - split: train path: subset_323/train-* - config_name: subset_324 data_files: - split: train path: subset_324/train-* - config_name: subset_325 data_files: - split: train path: subset_325/train-* - config_name: subset_326 data_files: - split: train path: subset_326/train-* - config_name: subset_327 data_files: - split: train path: subset_327/train-* - config_name: subset_328 data_files: - split: train path: subset_328/train-* - config_name: subset_329 data_files: - split: train path: subset_329/train-* - config_name: subset_33 data_files: - split: train path: subset_33/train-* - config_name: subset_330 data_files: - split: train path: subset_330/train-* - config_name: subset_331 data_files: - split: train path: subset_331/train-* - config_name: subset_332 data_files: - split: train path: subset_332/train-* - config_name: subset_333 data_files: - split: train path: subset_333/train-* - config_name: subset_334 data_files: - split: train path: subset_334/train-* - config_name: subset_335 data_files: - split: train path: subset_335/train-* - config_name: subset_336 data_files: - split: train path: subset_336/train-* - config_name: subset_337 data_files: - split: train path: subset_337/train-* - config_name: subset_338 data_files: - split: train path: subset_338/train-* - config_name: subset_339 data_files: - split: train path: subset_339/train-* - config_name: subset_34 data_files: - split: train path: subset_34/train-* - config_name: subset_340 data_files: - split: train path: subset_340/train-* - config_name: subset_341 data_files: - split: train path: subset_341/train-* - config_name: subset_342 data_files: - split: train path: subset_342/train-* - config_name: subset_343 data_files: - split: train path: subset_343/train-* - config_name: subset_344 data_files: - split: train path: subset_344/train-* - config_name: subset_345 data_files: - split: train path: subset_345/train-* - config_name: subset_346 data_files: - split: train path: subset_346/train-* - config_name: subset_347 data_files: - split: train path: subset_347/train-* - config_name: subset_348 data_files: - split: train path: subset_348/train-* - config_name: subset_349 data_files: - split: train path: subset_349/train-* - config_name: subset_35 data_files: - split: train path: subset_35/train-* - config_name: subset_350 data_files: - split: train path: subset_350/train-* - config_name: subset_351 data_files: - split: train path: subset_351/train-* - config_name: subset_352 data_files: - split: train path: subset_352/train-* - config_name: subset_353 data_files: - split: train path: subset_353/train-* - config_name: subset_354 data_files: - split: train path: subset_354/train-* - config_name: subset_355 data_files: - split: train path: subset_355/train-* - config_name: subset_356 data_files: - split: train path: subset_356/train-* - config_name: subset_357 data_files: - split: train path: subset_357/train-* - config_name: subset_358 data_files: - split: train path: subset_358/train-* - config_name: subset_359 data_files: - split: train path: subset_359/train-* - config_name: subset_36 data_files: - split: train path: subset_36/train-* - config_name: subset_360 data_files: - split: train path: subset_360/train-* - config_name: subset_361 data_files: - split: train path: subset_361/train-* - config_name: subset_362 data_files: - split: train path: subset_362/train-* - config_name: subset_363 data_files: - split: train path: subset_363/train-* - config_name: subset_364 data_files: - split: train path: subset_364/train-* - config_name: subset_365 data_files: - split: train path: subset_365/train-* - config_name: subset_366 data_files: - split: train path: subset_366/train-* - config_name: subset_367 data_files: - split: train path: subset_367/train-* - config_name: subset_368 data_files: - split: train path: subset_368/train-* - config_name: subset_369 data_files: - split: train path: subset_369/train-* - config_name: subset_37 data_files: - split: train path: subset_37/train-* - config_name: subset_370 data_files: - split: train path: subset_370/train-* - config_name: subset_371 data_files: - split: train path: subset_371/train-* - config_name: subset_372 data_files: - split: train path: subset_372/train-* - config_name: subset_373 data_files: - split: train path: subset_373/train-* - config_name: subset_374 data_files: - split: train path: subset_374/train-* - config_name: subset_375 data_files: - split: train path: subset_375/train-* - config_name: subset_376 data_files: - split: train path: subset_376/train-* - config_name: subset_377 data_files: - split: train path: subset_377/train-* - config_name: subset_378 data_files: - split: train path: subset_378/train-* - config_name: subset_379 data_files: - split: train path: subset_379/train-* - config_name: subset_38 data_files: - split: train path: subset_38/train-* - config_name: subset_380 data_files: - split: train path: subset_380/train-* - config_name: subset_381 data_files: - split: train path: subset_381/train-* - config_name: subset_382 data_files: - split: train path: subset_382/train-* - config_name: subset_383 data_files: - split: train path: subset_383/train-* - config_name: subset_384 data_files: - split: train path: subset_384/train-* - config_name: subset_385 data_files: - split: train path: subset_385/train-* - config_name: subset_386 data_files: - split: train path: subset_386/train-* - config_name: subset_387 data_files: - split: train path: subset_387/train-* - config_name: subset_388 data_files: - split: train path: subset_388/train-* - config_name: subset_389 data_files: - split: train path: subset_389/train-* - config_name: subset_39 data_files: - split: train path: subset_39/train-* - config_name: subset_390 data_files: - split: train path: subset_390/train-* - config_name: subset_391 data_files: - split: train path: subset_391/train-* - config_name: subset_392 data_files: - split: train path: subset_392/train-* - config_name: subset_393 data_files: - split: train path: subset_393/train-* - config_name: subset_394 data_files: - split: train path: subset_394/train-* - config_name: subset_395 data_files: - split: train path: subset_395/train-* - config_name: subset_396 data_files: - split: train path: subset_396/train-* - config_name: subset_397 data_files: - split: train path: subset_397/train-* - config_name: subset_398 data_files: - split: train path: subset_398/train-* - config_name: subset_399 data_files: - split: train path: subset_399/train-* - config_name: subset_4 data_files: - split: train path: subset_4/train-* - config_name: subset_40 data_files: - split: train path: subset_40/train-* - config_name: subset_400 data_files: - split: train path: subset_400/train-* - config_name: subset_401 data_files: - split: train path: subset_401/train-* - config_name: subset_402 data_files: - split: train path: subset_402/train-* - config_name: subset_403 data_files: - split: train path: subset_403/train-* - config_name: subset_404 data_files: - split: train path: subset_404/train-* - config_name: subset_405 data_files: - split: train path: subset_405/train-* - config_name: subset_406 data_files: - split: train path: subset_406/train-* - config_name: subset_407 data_files: - split: train path: subset_407/train-* - config_name: subset_408 data_files: - split: train path: subset_408/train-* - config_name: subset_409 data_files: - split: train path: subset_409/train-* - config_name: subset_41 data_files: - split: train path: subset_41/train-* - config_name: subset_410 data_files: - split: train path: subset_410/train-* - config_name: subset_411 data_files: - split: train path: subset_411/train-* - config_name: subset_412 data_files: - split: train path: subset_412/train-* - config_name: subset_413 data_files: - split: train path: subset_413/train-* - config_name: subset_414 data_files: - split: train path: subset_414/train-* - config_name: subset_415 data_files: - split: train path: subset_415/train-* - config_name: subset_416 data_files: - split: train path: subset_416/train-* - config_name: subset_417 data_files: - split: train path: subset_417/train-* - config_name: subset_418 data_files: - split: train path: subset_418/train-* - config_name: subset_419 data_files: - split: train path: subset_419/train-* - config_name: subset_42 data_files: - split: train path: subset_42/train-* - config_name: subset_420 data_files: - split: train path: subset_420/train-* - config_name: subset_421 data_files: - split: train path: subset_421/train-* - config_name: subset_422 data_files: - split: train path: subset_422/train-* - config_name: subset_423 data_files: - split: train path: subset_423/train-* - config_name: subset_424 data_files: - split: train path: subset_424/train-* - config_name: subset_425 data_files: - split: train path: subset_425/train-* - config_name: subset_426 data_files: - split: train path: subset_426/train-* - config_name: subset_427 data_files: - split: train path: subset_427/train-* - config_name: subset_428 data_files: - split: train path: subset_428/train-* - config_name: subset_429 data_files: - split: train path: subset_429/train-* - config_name: subset_43 data_files: - split: train path: subset_43/train-* - config_name: subset_430 data_files: - split: train path: subset_430/train-* - config_name: subset_431 data_files: - split: train path: subset_431/train-* - config_name: subset_432 data_files: - split: train path: subset_432/train-* - config_name: subset_433 data_files: - split: train path: subset_433/train-* - config_name: subset_434 data_files: - split: train path: subset_434/train-* - config_name: subset_435 data_files: - split: train path: subset_435/train-* - config_name: subset_436 data_files: - split: train path: subset_436/train-* - config_name: subset_437 data_files: - split: train path: subset_437/train-* - config_name: subset_438 data_files: - split: train path: subset_438/train-* - config_name: subset_439 data_files: - split: train path: subset_439/train-* - config_name: subset_44 data_files: - split: train path: subset_44/train-* - config_name: subset_440 data_files: - split: train path: subset_440/train-* - config_name: subset_441 data_files: - split: train path: subset_441/train-* - config_name: subset_442 data_files: - split: train path: subset_442/train-* - config_name: subset_443 data_files: - split: train path: subset_443/train-* - config_name: subset_444 data_files: - split: train path: subset_444/train-* - config_name: subset_445 data_files: - split: train path: subset_445/train-* - config_name: subset_446 data_files: - split: train path: subset_446/train-* - config_name: subset_447 data_files: - split: train path: subset_447/train-* - config_name: subset_448 data_files: - split: train path: subset_448/train-* - config_name: subset_449 data_files: - split: train path: subset_449/train-* - config_name: subset_45 data_files: - split: train path: subset_45/train-* - config_name: subset_450 data_files: - split: train path: subset_450/train-* - config_name: subset_451 data_files: - split: train path: subset_451/train-* - config_name: subset_452 data_files: - split: train path: subset_452/train-* - config_name: subset_453 data_files: - split: train path: subset_453/train-* - config_name: subset_454 data_files: - split: train path: subset_454/train-* - config_name: subset_455 data_files: - split: train path: subset_455/train-* - config_name: subset_456 data_files: - split: train path: subset_456/train-* - config_name: subset_457 data_files: - split: train path: subset_457/train-* - config_name: subset_458 data_files: - split: train path: subset_458/train-* - config_name: subset_459 data_files: - split: train path: subset_459/train-* - config_name: subset_46 data_files: - split: train path: subset_46/train-* - config_name: subset_460 data_files: - split: train path: subset_460/train-* - config_name: subset_461 data_files: - split: train path: subset_461/train-* - config_name: subset_462 data_files: - split: train path: subset_462/train-* - config_name: subset_463 data_files: - split: train path: subset_463/train-* - config_name: subset_464 data_files: - split: train path: subset_464/train-* - config_name: subset_465 data_files: - split: train path: subset_465/train-* - config_name: subset_466 data_files: - split: train path: subset_466/train-* - config_name: subset_467 data_files: - split: train path: subset_467/train-* - config_name: subset_468 data_files: - split: train path: subset_468/train-* - config_name: subset_469 data_files: - split: train path: subset_469/train-* - config_name: subset_47 data_files: - split: train path: subset_47/train-* - config_name: subset_470 data_files: - split: train path: subset_470/train-* - config_name: subset_471 data_files: - split: train path: subset_471/train-* - config_name: subset_472 data_files: - split: train path: subset_472/train-* - config_name: subset_473 data_files: - split: train path: subset_473/train-* - config_name: subset_474 data_files: - split: train path: subset_474/train-* - config_name: subset_475 data_files: - split: train path: subset_475/train-* - config_name: subset_476 data_files: - split: train path: subset_476/train-* - config_name: subset_477 data_files: - split: train path: subset_477/train-* - config_name: subset_478 data_files: - split: train path: subset_478/train-* - config_name: subset_479 data_files: - split: train path: subset_479/train-* - config_name: subset_48 data_files: - split: train path: subset_48/train-* - config_name: subset_480 data_files: - split: train path: subset_480/train-* - config_name: subset_481 data_files: - split: train path: subset_481/train-* - config_name: subset_482 data_files: - split: train path: subset_482/train-* - config_name: subset_483 data_files: - split: train path: subset_483/train-* - config_name: subset_484 data_files: - split: train path: subset_484/train-* - config_name: subset_485 data_files: - split: train path: subset_485/train-* - config_name: subset_486 data_files: - split: train path: subset_486/train-* - config_name: subset_487 data_files: - split: train path: subset_487/train-* - config_name: subset_488 data_files: - split: train path: subset_488/train-* - config_name: subset_489 data_files: - split: train path: subset_489/train-* - config_name: subset_49 data_files: - split: train path: subset_49/train-* - config_name: subset_490 data_files: - split: train path: subset_490/train-* - config_name: subset_491 data_files: - split: train path: subset_491/train-* - config_name: subset_492 data_files: - split: train path: subset_492/train-* - config_name: subset_493 data_files: - split: train path: subset_493/train-* - config_name: subset_494 data_files: - split: train path: subset_494/train-* - config_name: subset_495 data_files: - split: train path: subset_495/train-* - config_name: subset_496 data_files: - split: train path: subset_496/train-* - config_name: subset_497 data_files: - split: train path: subset_497/train-* - config_name: subset_498 data_files: - split: train path: subset_498/train-* - config_name: subset_499 data_files: - split: train path: subset_499/train-* - config_name: subset_5 data_files: - split: train path: subset_5/train-* - config_name: subset_50 data_files: - split: train path: subset_50/train-* - config_name: subset_500 data_files: - split: train path: subset_500/train-* - config_name: subset_501 data_files: - split: train path: subset_501/train-* - config_name: subset_502 data_files: - split: train path: subset_502/train-* - config_name: subset_503 data_files: - split: train path: subset_503/train-* - config_name: subset_504 data_files: - split: train path: subset_504/train-* - config_name: subset_505 data_files: - split: train path: subset_505/train-* - config_name: subset_506 data_files: - split: train path: subset_506/train-* - config_name: subset_507 data_files: - split: train path: subset_507/train-* - config_name: subset_508 data_files: - split: train path: subset_508/train-* - config_name: subset_509 data_files: - split: train path: subset_509/train-* - config_name: subset_51 data_files: - split: train path: subset_51/train-* - config_name: subset_510 data_files: - split: train path: subset_510/train-* - config_name: subset_511 data_files: - split: train path: subset_511/train-* - config_name: subset_512 data_files: - split: train path: subset_512/train-* - config_name: subset_513 data_files: - split: train path: subset_513/train-* - config_name: subset_514 data_files: - split: train path: subset_514/train-* - config_name: subset_515 data_files: - split: train path: subset_515/train-* - config_name: subset_516 data_files: - split: train path: subset_516/train-* - config_name: subset_517 data_files: - split: train path: subset_517/train-* - config_name: subset_518 data_files: - split: train path: subset_518/train-* - config_name: subset_519 data_files: - split: train path: subset_519/train-* - config_name: subset_52 data_files: - split: train path: subset_52/train-* - config_name: subset_520 data_files: - split: train path: subset_520/train-* - config_name: subset_521 data_files: - split: train path: subset_521/train-* - config_name: subset_522 data_files: - split: train path: subset_522/train-* - config_name: subset_523 data_files: - split: train path: subset_523/train-* - config_name: subset_524 data_files: - split: train path: subset_524/train-* - config_name: subset_525 data_files: - split: train path: subset_525/train-* - config_name: subset_526 data_files: - split: train path: subset_526/train-* - config_name: subset_527 data_files: - split: train path: subset_527/train-* - config_name: subset_528 data_files: - split: train path: subset_528/train-* - config_name: subset_529 data_files: - split: train path: subset_529/train-* - config_name: subset_53 data_files: - split: train path: subset_53/train-* - config_name: subset_530 data_files: - split: train path: subset_530/train-* - config_name: subset_531 data_files: - split: train path: subset_531/train-* - config_name: subset_532 data_files: - split: train path: subset_532/train-* - config_name: subset_533 data_files: - split: train path: subset_533/train-* - config_name: subset_534 data_files: - split: train path: subset_534/train-* - config_name: subset_535 data_files: - split: train path: subset_535/train-* - config_name: subset_536 data_files: - split: train path: subset_536/train-* - config_name: subset_537 data_files: - split: train path: subset_537/train-* - config_name: subset_538 data_files: - split: train path: subset_538/train-* - config_name: subset_539 data_files: - split: train path: subset_539/train-* - config_name: subset_54 data_files: - split: train path: subset_54/train-* - config_name: subset_540 data_files: - split: train path: subset_540/train-* - config_name: subset_541 data_files: - split: train path: subset_541/train-* - config_name: subset_542 data_files: - split: train path: subset_542/train-* - config_name: subset_543 data_files: - split: train path: subset_543/train-* - config_name: subset_544 data_files: - split: train path: subset_544/train-* - config_name: subset_545 data_files: - split: train path: subset_545/train-* - config_name: subset_546 data_files: - split: train path: subset_546/train-* - config_name: subset_547 data_files: - split: train path: subset_547/train-* - config_name: subset_548 data_files: - split: train path: subset_548/train-* - config_name: subset_549 data_files: - split: train path: subset_549/train-* - config_name: subset_55 data_files: - split: train path: subset_55/train-* - config_name: subset_550 data_files: - split: train path: subset_550/train-* - config_name: subset_551 data_files: - split: train path: subset_551/train-* - config_name: subset_552 data_files: - split: train path: subset_552/train-* - config_name: subset_553 data_files: - split: train path: subset_553/train-* - config_name: subset_554 data_files: - split: train path: subset_554/train-* - config_name: subset_555 data_files: - split: train path: subset_555/train-* - config_name: subset_556 data_files: - split: train path: subset_556/train-* - config_name: subset_557 data_files: - split: train path: subset_557/train-* - config_name: subset_558 data_files: - split: train path: subset_558/train-* - config_name: subset_559 data_files: - split: train path: subset_559/train-* - config_name: subset_56 data_files: - split: train path: subset_56/train-* - config_name: subset_560 data_files: - split: train path: subset_560/train-* - config_name: subset_561 data_files: - split: train path: subset_561/train-* - config_name: subset_562 data_files: - split: train path: subset_562/train-* - config_name: subset_563 data_files: - split: train path: subset_563/train-* - config_name: subset_564 data_files: - split: train path: subset_564/train-* - config_name: subset_565 data_files: - split: train path: subset_565/train-* - config_name: subset_566 data_files: - split: train path: subset_566/train-* - config_name: subset_567 data_files: - split: train path: subset_567/train-* - config_name: subset_568 data_files: - split: train path: subset_568/train-* - config_name: subset_569 data_files: - split: train path: subset_569/train-* - config_name: subset_57 data_files: - split: train path: subset_57/train-* - config_name: subset_570 data_files: - split: train path: subset_570/train-* - config_name: subset_571 data_files: - split: train path: subset_571/train-* - config_name: subset_572 data_files: - split: train path: subset_572/train-* - config_name: subset_573 data_files: - split: train path: subset_573/train-* - config_name: subset_574 data_files: - split: train path: subset_574/train-* - config_name: subset_575 data_files: - split: train path: subset_575/train-* - config_name: subset_576 data_files: - split: train path: subset_576/train-* - config_name: subset_577 data_files: - split: train path: subset_577/train-* - config_name: subset_578 data_files: - split: train path: subset_578/train-* - config_name: subset_579 data_files: - split: train path: subset_579/train-* - config_name: subset_58 data_files: - split: train path: subset_58/train-* - config_name: subset_580 data_files: - split: train path: subset_580/train-* - config_name: subset_581 data_files: - split: train path: subset_581/train-* - config_name: subset_582 data_files: - split: train path: subset_582/train-* - config_name: subset_583 data_files: - split: train path: subset_583/train-* - config_name: subset_584 data_files: - split: train path: subset_584/train-* - config_name: subset_585 data_files: - split: train path: subset_585/train-* - config_name: subset_586 data_files: - split: train path: subset_586/train-* - config_name: subset_587 data_files: - split: train path: subset_587/train-* - config_name: subset_588 data_files: - split: train path: subset_588/train-* - config_name: subset_589 data_files: - split: train path: subset_589/train-* - config_name: subset_59 data_files: - split: train path: subset_59/train-* - config_name: subset_590 data_files: - split: train path: subset_590/train-* - config_name: subset_591 data_files: - split: train path: subset_591/train-* - config_name: subset_592 data_files: - split: train path: subset_592/train-* - config_name: subset_593 data_files: - split: train path: subset_593/train-* - config_name: subset_594 data_files: - split: train path: subset_594/train-* - config_name: subset_595 data_files: - split: train path: subset_595/train-* - config_name: subset_596 data_files: - split: train path: subset_596/train-* - config_name: subset_597 data_files: - split: train path: subset_597/train-* - config_name: subset_598 data_files: - split: train path: subset_598/train-* - config_name: subset_599 data_files: - split: train path: subset_599/train-* - config_name: subset_6 data_files: - split: train path: subset_6/train-* - config_name: subset_60 data_files: - split: train path: subset_60/train-* - config_name: subset_600 data_files: - split: train path: subset_600/train-* - config_name: subset_61 data_files: - split: train path: subset_61/train-* - config_name: subset_62 data_files: - split: train path: subset_62/train-* - config_name: subset_63 data_files: - split: train path: subset_63/train-* - config_name: subset_64 data_files: - split: train path: subset_64/train-* - config_name: subset_65 data_files: - split: train path: subset_65/train-* - config_name: subset_66 data_files: - split: train path: subset_66/train-* - config_name: subset_67 data_files: - split: train path: subset_67/train-* - config_name: subset_68 data_files: - split: train path: subset_68/train-* - config_name: subset_69 data_files: - split: train path: subset_69/train-* - config_name: subset_7 data_files: - split: train path: subset_7/train-* - config_name: subset_70 data_files: - split: train path: subset_70/train-* - config_name: subset_71 data_files: - split: train path: subset_71/train-* - config_name: subset_72 data_files: - split: train path: subset_72/train-* - config_name: subset_73 data_files: - split: train path: subset_73/train-* - config_name: subset_74 data_files: - split: train path: subset_74/train-* - config_name: subset_75 data_files: - split: train path: subset_75/train-* - config_name: subset_76 data_files: - split: train path: subset_76/train-* - config_name: subset_77 data_files: - split: train path: subset_77/train-* - config_name: subset_78 data_files: - split: train path: subset_78/train-* - config_name: subset_79 data_files: - split: train path: subset_79/train-* - config_name: subset_8 data_files: - split: train path: subset_8/train-* - config_name: subset_80 data_files: - split: train path: subset_80/train-* - config_name: subset_81 data_files: - split: train path: subset_81/train-* - config_name: subset_82 data_files: - split: train path: subset_82/train-* - config_name: subset_83 data_files: - split: train path: subset_83/train-* - config_name: subset_84 data_files: - split: train path: subset_84/train-* - config_name: subset_85 data_files: - split: train path: subset_85/train-* - config_name: subset_86 data_files: - split: train path: subset_86/train-* - config_name: subset_87 data_files: - split: train path: subset_87/train-* - config_name: subset_88 data_files: - split: train path: subset_88/train-* - config_name: subset_89 data_files: - split: train path: subset_89/train-* - config_name: subset_9 data_files: - split: train path: subset_9/train-* - config_name: subset_90 data_files: - split: train path: subset_90/train-* - config_name: subset_91 data_files: - split: train path: subset_91/train-* - config_name: subset_92 data_files: - split: train path: subset_92/train-* - config_name: subset_93 data_files: - split: train path: subset_93/train-* - config_name: subset_94 data_files: - split: train path: subset_94/train-* - config_name: subset_95 data_files: - split: train path: subset_95/train-* - config_name: subset_96 data_files: - split: train path: subset_96/train-* - config_name: subset_97 data_files: - split: train path: subset_97/train-* - config_name: subset_98 data_files: - split: train path: subset_98/train-* - config_name: subset_99 data_files: - split: train path: subset_99/train-* ---

CohereForAI/Global-MMLU

CohereForAI

--- dataset_info: - config_name: am features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 209505 num_examples: 285 - name: test num_bytes: 12085768 num_examples: 14042 download_size: 10260448 dataset_size: 12295273 - config_name: ar features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 202343 num_examples: 285 - name: test num_bytes: 11621977 num_examples: 14042 download_size: 9817049 dataset_size: 11824320 - config_name: bn features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 301875 num_examples: 285 - name: test num_bytes: 18061158 num_examples: 14042 download_size: 12524784 dataset_size: 18363033 - config_name: cs features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 149807 num_examples: 285 - name: test num_bytes: 8607308 num_examples: 14042 download_size: 8640151 dataset_size: 8757115 - config_name: de features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 162406 num_examples: 285 - name: test num_bytes: 9575360 num_examples: 14042 download_size: 9187953 dataset_size: 9737766 - config_name: el features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 254308 num_examples: 285 - name: test num_bytes: 14502137 num_examples: 14042 download_size: 12288940 dataset_size: 14756445 - config_name: en features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 146364 num_examples: 285 - name: test num_bytes: 8440632 num_examples: 14042 download_size: 7912429 dataset_size: 8586996 - config_name: es features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 160633 num_examples: 285 - name: test num_bytes: 9399724 num_examples: 14042 download_size: 8752720 dataset_size: 9560357 - config_name: fa features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 202609 num_examples: 285 - name: test num_bytes: 11611890 num_examples: 14042 download_size: 9564082 dataset_size: 11814499 - config_name: fil features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 165182 num_examples: 285 - name: test num_bytes: 9510179 num_examples: 14042 download_size: 8564879 dataset_size: 9675361 - config_name: fr features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 166173 num_examples: 285 - name: test num_bytes: 9858873 num_examples: 14042 download_size: 9202595 dataset_size: 10025046 - config_name: ha features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 147406 num_examples: 285 - name: test num_bytes: 8445707 num_examples: 14042 download_size: 7665529 dataset_size: 8593113 - config_name: he features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 178912 num_examples: 285 - name: test num_bytes: 10248592 num_examples: 14042 download_size: 8818618 dataset_size: 10427504 - config_name: hi features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 308254 num_examples: 285 - name: test num_bytes: 17970478 num_examples: 14042 download_size: 12407854 dataset_size: 18278732 - config_name: id features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 154692 num_examples: 285 - name: test num_bytes: 8886643 num_examples: 14042 download_size: 7793365 dataset_size: 9041335 - config_name: ig features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 157376 num_examples: 285 - name: test num_bytes: 9221405 num_examples: 14042 download_size: 7644102 dataset_size: 9378781 - config_name: it features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 157547 num_examples: 285 - name: test num_bytes: 9374481 num_examples: 14042 download_size: 8873034 dataset_size: 9532028 - config_name: ja features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 167646 num_examples: 285 - name: test num_bytes: 9830716 num_examples: 14042 download_size: 8826164 dataset_size: 9998362 - config_name: ko features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 160572 num_examples: 285 - name: test num_bytes: 9454859 num_examples: 14042 download_size: 8640457 dataset_size: 9615431 - config_name: ky features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 235001 num_examples: 285 - name: test num_bytes: 13483934 num_examples: 14042 download_size: 11148813 dataset_size: 13718935 - config_name: lt features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 148917 num_examples: 285 - name: test num_bytes: 8504949 num_examples: 14042 download_size: 8416467 dataset_size: 8653866 - config_name: mg features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 161992 num_examples: 285 - name: test num_bytes: 9337415 num_examples: 14042 download_size: 8011427 dataset_size: 9499407 - config_name: ms features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 152549 num_examples: 285 - name: test num_bytes: 8823844 num_examples: 14042 download_size: 7783581 dataset_size: 8976393 - config_name: ne features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 294790 num_examples: 285 - name: test num_bytes: 16972110 num_examples: 14042 download_size: 11895818 dataset_size: 17266900 - config_name: nl features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 158122 num_examples: 285 - name: test num_bytes: 9099176 num_examples: 14042 download_size: 8565959 dataset_size: 9257298 - config_name: ny features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 151315 num_examples: 285 - name: test num_bytes: 8686819 num_examples: 14042 download_size: 7822699 dataset_size: 8838134 - config_name: pl features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 157290 num_examples: 285 - name: test num_bytes: 8980730 num_examples: 14042 download_size: 8981270 dataset_size: 9138020 - config_name: pt features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 154592 num_examples: 285 - name: test num_bytes: 8983299 num_examples: 14042 download_size: 8517588 dataset_size: 9137891 - config_name: ro features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 158311 num_examples: 285 - name: test num_bytes: 9163189 num_examples: 14042 download_size: 8773232 dataset_size: 9321500 - config_name: ru features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 246059 num_examples: 285 - name: test num_bytes: 14059847 num_examples: 14042 download_size: 11904365 dataset_size: 14305906 - config_name: si features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 297843 num_examples: 285 - name: test num_bytes: 17374939 num_examples: 14042 download_size: 12790098 dataset_size: 17672782 - config_name: sn features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 147355 num_examples: 285 - name: test num_bytes: 8507368 num_examples: 14042 download_size: 7962672 dataset_size: 8654723 - config_name: so features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 156282 num_examples: 285 - name: test num_bytes: 9033243 num_examples: 14042 download_size: 8706693 dataset_size: 9189525 - config_name: sr features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 221580 num_examples: 285 - name: test num_bytes: 12695546 num_examples: 14042 download_size: 10748391 dataset_size: 12917126 - config_name: sv features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 147893 num_examples: 285 - name: test num_bytes: 8549708 num_examples: 14042 download_size: 8181997 dataset_size: 8697601 - config_name: sw features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 147069 num_examples: 285 - name: test num_bytes: 8653210 num_examples: 14042 download_size: 7932986 dataset_size: 8800279 - config_name: te features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 315724 num_examples: 285 - name: test num_bytes: 18170058 num_examples: 14042 download_size: 12631358 dataset_size: 18485782 - config_name: tr features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 153426 num_examples: 285 - name: test num_bytes: 8833244 num_examples: 14042 download_size: 8351339 dataset_size: 8986670 - config_name: uk features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 229888 num_examples: 285 - name: test num_bytes: 13233771 num_examples: 14042 download_size: 11347842 dataset_size: 13463659 - config_name: vi features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 185712 num_examples: 285 - name: test num_bytes: 10604332 num_examples: 14042 download_size: 8971266 dataset_size: 10790044 - config_name: yo features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 153810 num_examples: 285 - name: test num_bytes: 10694916 num_examples: 14042 download_size: 9303668 dataset_size: 10848726 - config_name: zh features: - name: sample_id dtype: string - name: subject dtype: string - name: subject_category dtype: string - name: question dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: answer dtype: string - name: required_knowledge dtype: string - name: time_sensitive dtype: string - name: reference dtype: string - name: culture dtype: string - name: region dtype: string - name: country dtype: string - name: cultural_sensitivity_label dtype: string - name: is_annotated dtype: bool splits: - name: dev num_bytes: 127577 num_examples: 285 - name: test num_bytes: 7393764 num_examples: 14042 download_size: 7322261 dataset_size: 7521341 configs: - config_name: am data_files: - split: test path: am/test-* - split: dev path: am/dev-* - config_name: ar data_files: - split: test path: ar/test-* - split: dev path: ar/dev-* - config_name: bn data_files: - split: test path: bn/test-* - split: dev path: bn/dev-* - config_name: cs data_files: - split: test path: cs/test-* - split: dev path: cs/dev-* - config_name: de data_files: - split: test path: de/test-* - split: dev path: de/dev-* - config_name: el data_files: - split: test path: el/test-* - split: dev path: el/dev-* - config_name: en data_files: - split: test path: en/test-* - split: dev path: en/dev-* - config_name: es data_files: - split: test path: es/test-* - split: dev path: es/dev-* - config_name: fa data_files: - split: test path: fa/test-* - split: dev path: fa/dev-* - config_name: fil data_files: - split: test path: fil/test-* - split: dev path: fil/dev-* - config_name: fr data_files: - split: test path: fr/test-* - split: dev path: fr/dev-* - config_name: ha data_files: - split: test path: ha/test-* - split: dev path: ha/dev-* - config_name: he data_files: - split: test path: he/test-* - split: dev path: he/dev-* - config_name: hi data_files: - split: test path: hi/test-* - split: dev path: hi/dev-* - config_name: id data_files: - split: test path: id/test-* - split: dev path: id/dev-* - config_name: ig data_files: - split: test path: ig/test-* - split: dev path: ig/dev-* - config_name: it data_files: - split: test path: it/test-* - split: dev path: it/dev-* - config_name: ja data_files: - split: test path: ja/test-* - split: dev path: ja/dev-* - config_name: ko data_files: - split: test path: ko/test-* - split: dev path: ko/dev-* - config_name: ky data_files: - split: test path: ky/test-* - split: dev path: ky/dev-* - config_name: lt data_files: - split: test path: lt/test-* - split: dev path: lt/dev-* - config_name: mg data_files: - split: test path: mg/test-* - split: dev path: mg/dev-* - config_name: ms data_files: - split: test path: ms/test-* - split: dev path: ms/dev-* - config_name: ne data_files: - split: test path: ne/test-* - split: dev path: ne/dev-* - config_name: nl data_files: - split: test path: nl/test-* - split: dev path: nl/dev-* - config_name: ny data_files: - split: test path: ny/test-* - split: dev path: ny/dev-* - config_name: pl data_files: - split: test path: pl/test-* - split: dev path: pl/dev-* - config_name: pt data_files: - split: test path: pt/test-* - split: dev path: pt/dev-* - config_name: ro data_files: - split: test path: ro/test-* - split: dev path: ro/dev-* - config_name: ru data_files: - split: test path: ru/test-* - split: dev path: ru/dev-* - config_name: si data_files: - split: test path: si/test-* - split: dev path: si/dev-* - config_name: sn data_files: - split: test path: sn/test-* - split: dev path: sn/dev-* - config_name: so data_files: - split: test path: so/test-* - split: dev path: so/dev-* - config_name: sr data_files: - split: test path: sr/test-* - split: dev path: sr/dev-* - config_name: sv data_files: - split: test path: sv/test-* - split: dev path: sv/dev-* - config_name: sw data_files: - split: test path: sw/test-* - split: dev path: sw/dev-* - config_name: te data_files: - split: test path: te/test-* - split: dev path: te/dev-* - config_name: tr data_files: - split: test path: tr/test-* - split: dev path: tr/dev-* - config_name: uk data_files: - split: test path: uk/test-* - split: dev path: uk/dev-* - config_name: vi data_files: - split: test path: vi/test-* - split: dev path: vi/dev-* - config_name: yo data_files: - split: test path: yo/test-* - split: dev path: yo/dev-* - config_name: zh data_files: - split: test path: zh/test-* - split: dev path: zh/dev-* tags: - argilla language: - en - ar - bn - es - fr - hi - ru - de - id - it - ja - ko - pt - zh - yo - nl - ro - uk - vi - tr - pl - fa - cs - he - el - ms - fil - te - si - ne - ky - sv - lt - sr - mg - so - ha - am - sn - ig - ny - sw ---  # Dataset Summary [Global-MMLU](https://arxiv.org/abs/2412.03304) 🌍 is a multilingual evaluation set spanning 42 languages, including English. This dataset combines machine translations for [MMLU](https://huggingface.co/datasets/cais/mmlu) questions along with professional translations and crowd-sourced post-edits. It also includes cultural sensitivity annotations for a subset of the questions (2850 questions per language) and classifies them as *Culturally Sensitive* (CS) 🗽 or *Culturally Agnostic* (CA) ⚖️. These annotations were collected as part of an open science initiative led by Cohere For AI in collaboration with many external collaborators from both industry and academia. - **Curated by:** Professional annotators and contributors of [Cohere For AI Community](https://cohere.com/research). - **Language(s):** 42 languages. - **License:** [Apache 2.0](https://opensource.org/license/apache-2-0) **Note:** We also provide a "lite" version of Global MMLU called ["Global-MMLU-Lite"](https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite). This datatset is more balanced containing 200 samples each for CA and CS subsets for each language. And provides coverage for 15 languages with human translations. ### **Global-MMLU Dataset Family:** | Name | Explanation | |------|--------------| | [Global-MMLU](https://huggingface.co/datasets/CohereForAI/Global-MMLU) | Full Global-MMLU set with translations for all 14K samples including CS and CA subsets| | [Global-MMLU-Lite](https://huggingface.co/datasets/CohereForAI/Global-MMLU-Lite) | Lite version of Global-MMLU with human translated samples in 15 languages and containing 200 samples each for CS and CA subsets per language.| ## Load with Datasets To load this dataset with `datasets`, you'll first need to install it using `pip install datasets` and then use the following code: ```python from datasets import load_dataset # load HF dataset global_mmlu = load_dataset("CohereForAI/Global-MMLU", 'en') # can also be used as pandas dataframe global_mmlu.set_format("pandas") global_mmlu_test = global_mmlu['test'][:] global_mmlu_dev = global_mmlu['dev'][:] ``` <details> <summary> additional details </summary> The columns corresponding to annotations collected from our cultural bias study (i.e. 'required_knowledge', 'time_sensitive', 'reference', 'culture', 'region', 'country') contain a list of values representing annotations from different annotators. However, to avoid conversion issues to HF dataset, these columns are provided as string in the final dataset. You can convert these columns back to list of values for easier manipulation as follows: ```python import ast # convert string values to list global_mmlu_df['required_knowledge'] = global_mmlu_df['required_knowledge'].apply(lamda x: ast.literal_eval(x)) ``` </details> <br> ## Data Fields The data fields are the same among all splits. Brief description of each field is provided below. <details> <summary> data field description </summary> - `sample_id`: A unique identifier for the question. - `subject`: The main topic the question falls under. - `subject_category`: The high-level category the subject falls under i.e. STEM/Humanities/Social Sciences/Medical/Business/Other. - `question`: translated question from MMLU - `option_a`: one of the possible option choices - `option_b`: one of the possible option choices - `option_c`: one of the possible option choices - `option_d`: one of the possible option choices - `answer': the correct answer (A/B/C/D) - `required_knowledge`: annotator votes for knowledge needed to answer the question correctly. Possible values include: "cultural", "regional", "dialect" or "none" - `time_sensitive`: annotator votes indicating if the question's answer is time-dependent. Possible values include: Yes/No - `reference`: annotations for which part of the question contains cultural/regional/dialect references. The different items in the list are annotations from different annotators. - `culture`: annotations for which culture does the question belong to. The different items in the list correspond to annotations from different annotators. - `region`: Geographic region the question is relevant to. Each item in the list correspond to annotations from different annotators. - `country`: Specific country the question pertains to. Each item in the list correspond to annotations from different annotators. - `cultural_sensitivity_label`: Label to indicate if question is culturally sensitive (CS) or culturally agnostic (CA) based on annotator votes. - `is_annotated`: True/False flag to indicate if sample contains any annotations from our cultural bias study. </details> <br> ## Data Splits The following are the splits of the data: | Split | No. of instances | Language Coverage | |-------|------------------|-------------------| | test | 589,764 | 42 | | dev | 11,970 | 42 | ## Data Instances An example from `test` set looks as follows: ```json {'sample_id': 'world_religions/test/170' 'subject': 'world_religions', 'subject_category': 'Humanities', 'question': ' The numen of Augustus referred to which of the following characteristics?', 'option_a': 'Divine power', 'option_b': 'Sexual virility', 'option_c': 'Military acumen', 'option_d': 'Philosophical intellect', 'answer': 'A', 'required_knowledge': "['none', 'cultural', 'cultural', 'cultural']", 'time_sensitive': "['No', 'No', 'No', 'No']", 'reference': "['-', '-', {'end': 22, 'label': 'Cultural', 'score': None, 'start': 5}, {'end': 22, 'label': 'Cultural', 'score': None, 'start': 5}]", 'culture': "['Western Culture', 'Western Culture', 'Western Culture']", 'region': "['North America', 'Europe']", 'country': "['Italy']", 'cultural_sensitivity_label': 'CS', 'is_annotated': True, } ``` ## Statistics ### Annotation Types The following is the breakdown of CS🗽, CA⚖️ and MA📝 samples in the final dataset. | Type of Annotation | Instances per language | No. of languages | Total instances |--------------------|------------------------|------------------|----------------| | Culturally Sensitive 🗽 | 792 | 42 | 33,264 | | Culturally Agnostic ⚖️ | 2058 |42 | 86,436 | | MMLU Annotated 📝| 2850 |42 | 119,700 | ### Languages The dataset covers 42 languages: 20 high-resource, 9 mid-resource, and 13 low-resource languages. The following is details about the languages included in the dataset. <details> <summary> Languages Info </summary> | ISO Code | Language | Resources | |----------|----------|-----------| | `am` | Amharic | Low | | `ar` | Arabic (Standard)| High | | `bn` | Bengali | Mid | | `de` | German | High | | `el` | Greek | Mid | | `en` | English | High | | `fil` | Filipino | Mid | | `fr` | French | High | | `ha` | Hausa | Low | | `he` | Hebrew | Mid | | `hi` | Hindi | High | | `ig` | Igbo | Low | | `id` | Indonesian | Mid | | `it` | Italian | High | | `ja` | Japanese | High | | `ky` | Kyrgyz | Low | | `ko` | Korean | Mid | | `lt` | Lithuanian | Mid | | `mg` | Malagasy | Low | | `ms` | Malay | Mid | | `ne` | Nepali | Low | | `nl` | Dutch | High | | `ny` | Chichewa | Low | | `fa` | Persian | High | | `pl` | Polish | High | | `pt` | Portuguese | High | | `ru` | Russian | High | | `si` | Sinhala | Low | | `sn` | Shona | Low | | `so` | Somali | Low | | `es` | Spanish | High | | `sr` | Serbian | High | | `sw` | Swahili | Low | | `sw` | Swedish | High | | `te` | Telugu | Low | | `tr` | Turkish | High | | `uk` | Ukrainian | Mid | | `vi` | Vietnamese | High | | `yo` | Yorùbá | Low | | `zh` | Chinese (Simplified) | High | </details> <br> # Known Limitations A brief overview of limitations of this dataset is provided below. <details> <summary> show limitations </summary> - **Language and dialect coverage:** Global-MMLU focusses on 42 languages. However, this is still only a tiny fraction of the world’s linguistic diversity. Future work is needed to continue to improve evaluations beyond these 42 languages and take into account how technology serves different dialects. - **Uneven distribution of contributions:** The dataset contains translation post-edits from community volunteers, with a 'long tail' of volunteers making only one or two contributions. Similarly, there is a huge gap between languages with the highest number of contributions and ones with the lowest number of contributions. - **Toxic or offensive speech:** Our annotation process did not focus on flagging for toxic,harmful, or offensive speech, so it is possible that Global-MMLU contains some data that could be considered harmful. We believe this is of relatively low risk because of the nature of the original MMLU and the focus on examination material. - **Region Category Assignment:** For the annotation of geographically sensitive questions, we classified regions into six geographic regions (Africa, Asia, Europe, North America, Oceania,and South America). However, based upon discussions we would going forward recommend switching to the taxonomy proposed by the World Bank which is more granular and includes separate designations for Central America and Sub-Saharan Africa. - **Identifying cultural sensitivity does not guarantee cultural inclusion:** While Global-MMLU highlights important limitations in current datasets by identifying gaps in non-Western cultural representation. Future work must prioritize the integration of diverse culturally grounded knowledge to achieve true inclusivity and fairness in multilingual AI evaluation. </details> <br> # Additional Information ## Provenance - **Methods Used:** Professional annotations as well as crowd-sourced through volunteer annotations. - **Methodology Details:** We collected cultural bias annotations as well as post-edits of translations for different mmlu questions. - [Cultural Sensitivity Annotation Platform](https://huggingface.co/spaces/CohereForAI/MMLU-evaluation) - [Translation Quality Annotation Platform](https://huggingface.co/spaces/CohereForAI/review-mmlu-translations) - Dates of Collection: May 2024 - Aug 2024 ## Dataset Version and Maintenance - **Maintenance Status:** Actively Maintained - **Version Details:** - *Current version:* 1.0 - *Last Update:* 12/2024 - *First Release:* 12/2024 ## Authorship - **Publishing Organization:** [Cohere For AI](https://cohere.com/research) - **Industry Type:** Not-for-profit - Tech ## Licensing Information This dataset can be used for any purpose, under the terms of the [Apache 2.0](https://opensource.org/license/apache-2-0) License. ## Additional Details For any additional details, please check our paper, [Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation](https://arxiv.org/abs/2412.03304). ## Citation Information ```bibtex @misc{singh2024globalmmluunderstandingaddressing, title={Global MMLU: Understanding and Addressing Cultural and Linguistic Biases in Multilingual Evaluation}, author={Shivalika Singh and Angelika Romanou and Clémentine Fourrier and David I. Adelani and Jian Gang Ngui and Daniel Vila-Suero and Peerat Limkonchotiwat and Kelly Marchisio and Wei Qi Leong and Yosephine Susanto and Raymond Ng and Shayne Longpre and Wei-Yin Ko and Madeline Smith and Antoine Bosselut and Alice Oh and Andre F. T. Martins and Leshem Choshen and Daphne Ippolito and Enzo Ferrante and Marzieh Fadaee and Beyza Ermis and Sara Hooker}, year={2024}, eprint={2412.03304}, archivePrefix={arXiv}, primaryClass={cs.CL}, url={https://arxiv.org/abs/2412.03304}, } ```

openslr/librispeech_asr

openslr

--- pretty_name: LibriSpeech annotations_creators: - expert-generated language_creators: - crowdsourced - expert-generated language: - en license: - cc-by-4.0 multilinguality: - monolingual paperswithcode_id: librispeech-1 size_categories: - 100K<n<1M source_datasets: - original task_categories: - automatic-speech-recognition - audio-classification task_ids: - speaker-identification dataset_info: - config_name: clean features: - name: file dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: speaker_id dtype: int64 - name: chapter_id dtype: int64 - name: id dtype: string splits: - name: train.100 num_bytes: 6619683041 num_examples: 28539 - name: train.360 num_bytes: 23898214592 num_examples: 104014 - name: validation num_bytes: 359572231 num_examples: 2703 - name: test num_bytes: 367705423 num_examples: 2620 download_size: 30121377654 dataset_size: 31245175287 - config_name: other features: - name: file dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: speaker_id dtype: int64 - name: chapter_id dtype: int64 - name: id dtype: string splits: - name: train.500 num_bytes: 31810256902 num_examples: 148688 - name: validation num_bytes: 337283304 num_examples: 2864 - name: test num_bytes: 352396474 num_examples: 2939 download_size: 31236565377 dataset_size: 32499936680 - config_name: all features: - name: file dtype: string - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: speaker_id dtype: int64 - name: chapter_id dtype: int64 - name: id dtype: string splits: - name: train.clean.100 num_bytes: 6627791685 num_examples: 28539 - name: train.clean.360 num_bytes: 23927767570 num_examples: 104014 - name: train.other.500 num_bytes: 31852502880 num_examples: 148688 - name: validation.clean num_bytes: 359505691 num_examples: 2703 - name: validation.other num_bytes: 337213112 num_examples: 2864 - name: test.clean num_bytes: 368449831 num_examples: 2620 - name: test.other num_bytes: 353231518 num_examples: 2939 download_size: 61357943031 dataset_size: 63826462287 --- # Dataset Card for librispeech_asr ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - **Homepage:** [LibriSpeech ASR corpus](http://www.openslr.org/12) - **Repository:** [Needs More Information] - **Paper:** [LibriSpeech: An ASR Corpus Based On Public Domain Audio Books](https://www.danielpovey.com/files/2015_icassp_librispeech.pdf) - **Leaderboard:** [The 🤗 Speech Bench](https://huggingface.co/spaces/huggingface/hf-speech-bench) - **Point of Contact:** [Daniel Povey](mailto:[email protected]) ### Dataset Summary LibriSpeech is a corpus of approximately 1000 hours of 16kHz read English speech, prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read audiobooks from the LibriVox project, and has been carefully segmented and aligned. ### Supported Tasks and Leaderboards - `automatic-speech-recognition`, `audio-speaker-identification`: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER). The task has an active Hugging Face leaderboard which can be found at https://huggingface.co/spaces/huggingface/hf-speech-bench. The leaderboard ranks models uploaded to the Hub based on their WER. An external leaderboard at https://paperswithcode.com/sota/speech-recognition-on-librispeech-test-clean ranks the latest models from research and academia. ### Languages The audio is in English. There are two configurations: `clean` and `other`. The speakers in the corpus were ranked according to the WER of the transcripts of a model trained on a different dataset, and were divided roughly in the middle, with the lower-WER speakers designated as "clean" and the higher WER speakers designated as "other". ## Dataset Structure ### Data Instances A typical data point comprises the path to the audio file, usually called `file` and its transcription, called `text`. Some additional information about the speaker and the passage which contains the transcription is provided. ``` {'chapter_id': 141231, 'file': '/home/patrick/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/dev_clean/1272/141231/1272-141231-0000.flac', 'audio': {'path': '/home/patrick/.cache/huggingface/datasets/downloads/extracted/b7ded9969e09942ab65313e691e6fc2e12066192ee8527e21d634aca128afbe2/dev_clean/1272/141231/1272-141231-0000.flac', 'array': array([-0.00048828, -0.00018311, -0.00137329, ..., 0.00079346, 0.00091553, 0.00085449], dtype=float32), 'sampling_rate': 16000}, 'id': '1272-141231-0000', 'speaker_id': 1272, 'text': 'A MAN SAID TO THE UNIVERSE SIR I EXIST'} ``` ### Data Fields - file: A path to the downloaded audio file in .flac format. - audio: A dictionary containing the path to the downloaded audio file, the decoded audio array, and the sampling rate. Note that when accessing the audio column: `dataset[0]["audio"]` the audio file is automatically decoded and resampled to `dataset.features["audio"].sampling_rate`. Decoding and resampling of a large number of audio files might take a significant amount of time. Thus it is important to first query the sample index before the `"audio"` column, *i.e.* `dataset[0]["audio"]` should **always** be preferred over `dataset["audio"][0]`. - text: the transcription of the audio file. - id: unique id of the data sample. - speaker_id: unique id of the speaker. The same speaker id can be found for multiple data samples. - chapter_id: id of the audiobook chapter which includes the transcription. ### Data Splits The size of the corpus makes it impractical, or at least inconvenient for some users, to distribute it as a single large archive. Thus the training portion of the corpus is split into three subsets, with approximate size 100, 360 and 500 hours respectively. A simple automatic procedure was used to select the audio in the first two sets to be, on average, of higher recording quality and with accents closer to US English. An acoustic model was trained on WSJ’s si-84 data subset and was used to recognize the audio in the corpus, using a bigram LM estimated on the text of the respective books. We computed the Word Error Rate (WER) of this automatic transcript relative to our reference transcripts obtained from the book texts. The speakers in the corpus were ranked according to the WER of the WSJ model’s transcripts, and were divided roughly in the middle, with the lower-WER speakers designated as "clean" and the higher-WER speakers designated as "other". For "clean", the data is split into train, validation, and test set. The train set is further split into train.100 and train.360 respectively accounting for 100h and 360h of the training data. For "other", the data is split into train, validation, and test set. The train set contains approximately 500h of recorded speech. | | Train.500 | Train.360 | Train.100 | Valid | Test | | ----- | ------ | ----- | ---- | ---- | ---- | | clean | - | 104014 | 28539 | 2703 | 2620| | other | 148688 | - | - | 2864 | 2939 | ## Dataset Creation ### Curation Rationale [Needs More Information] ### Source Data #### Initial Data Collection and Normalization [Needs More Information] #### Who are the source language producers? [Needs More Information] ### Annotations #### Annotation process [Needs More Information] #### Who are the annotators? [Needs More Information] ### Personal and Sensitive Information The dataset consists of people who have donated their voice online. You agree to not attempt to determine the identity of speakers in this dataset. ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators The dataset was initially created by Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur. ### Licensing Information [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/) ### Citation Information ``` @inproceedings{panayotov2015librispeech, title={Librispeech: an ASR corpus based on public domain audio books}, author={Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev}, booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on}, pages={5206--5210}, year={2015}, organization={IEEE} } ``` ### Contributions Thanks to [@patrickvonplaten](https://github.com/patrickvonplaten) for adding this dataset.

MLCommons/unsupervised_peoples_speech

MLCommons

--- language: - eng pretty_name: Unsupervised Peoples Speech tags: - audio - unsupervised task_categories: - automatic-speech-recognition - audio-classification task_ids: - audio-language-identification viewer: false --- # Dataset Card for Unsupervised Peoples Speech ## Table of Contents - [Dataset Card for Unuspervised Peoples Speech](#dataset-card-for-unsupervised-peoples-speech) - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Dataset Structure](#dataset-structure) - [Relevant Statistics](#relevant-statistics) - [Dataset Creation](#dataset-creation) - [Source Data](#source-data) - [Annotations](#annotations) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Additional Information](#additional-information) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description ### Dataset Summary The Unsupervised Peoples Speech Dataset is a compilation of audiofiles extracted from Archive.org that is licensed for academic and commercial usage under CC-BY and CC-BY-SA licenses. It includes more than one million hours of audio with a diverse set of speakers. - **Point of Contact:** [MLCommons Datasets Discord](https://discord.gg/8ZVyxwpv) ## Dataset Structure This dataset is a collection of audio files that have been stored as tar files, each containing a set of audio files. On average, each tar file is 5GB in size. - All tar files are stored in either in the `audio` or `audio2` directories. - The `licenses.jsonl` file contains the license information for each audio file. ## Relevant Statistics #### Duration Distribution Most of the audios range between 1 and 10 minutes in length, with only 14 of them exceeding the 100 hour mark.  #### Sample Rates 99% of the audio in the dataset has a 44.1Khz sample rate, and the remaining audio varies from the more common 16Khz, 24Khz and 48 Khz to custom sample rates.  ## Dataset Creation ### Source Data Data was downloaded via the archive.org API. No data inference was done. No preprocessing was done. ### Annotations No manual annotation is done. We download only source audio. In particular, there is no "forced alignment" or "segmentation" done on this dataset. ## Considerations for Using the Data Our data is downloaded from archive.org. As such, the data is biased towards whatever users decide to upload there. Almost all of our data is American accented English. ## Additional Information ### Licensing Information The source data contains data under CC-BY-SA and CC-BY licenses. We license this dataset under https://creativecommons.org/licenses/by-sa/4.0/ ### Citation Information Please cite ``` @article{USP, author={Daniel Galvez and Ryan Hileman and Rafael Mosquera and Juan Ciro and Kurt Bollacker and Peter Mattson and David Kanter}, title = {Unsupervised People's Speech (The Million Hour Audio Dataset)}, year = {2023}, url = {https://huggingface.co/datasets/MLCommons/peoples_speech}, } ```

TempoFunk/small

TempoFunk

--- task_categories: - text-to-video - text-to-image - video-classification - image-classification language: - en size_categories: - 1K<n<10K license: agpl-3.0 --- # TempoFunk Small 7.8k samples of metadata and encoded latents & prompts of random videos. ## Data format - Video frame latents - Numpy arrays - 120 frames, 512x512 source size - Encoded shape (120, 4, 64, 64) - CLIP (openai) encoded prompts - Video description (as seen in metadata) - Encoded shape (77,768) - Video metadata as JSON (description, tags, categories, source URL, etc.)

mteb/amazon_massive_scenario

mteb

--- configs: - config_name: default data_files: - path: train/*.json.gz split: train - path: test/*.json.gz split: test - path: validation/*.json.gz split: validation - config_name: ta data_files: - path: train/ta.json.gz split: train - path: test/ta.json.gz split: test - path: validation/ta.json.gz split: validation - config_name: is data_files: - path: train/is.json.gz split: train - path: test/is.json.gz split: test - path: validation/is.json.gz split: validation - config_name: pl data_files: - path: train/pl.json.gz split: train - path: test/pl.json.gz split: test - path: validation/pl.json.gz split: validation - config_name: zh-CN data_files: - path: train/zh-CN.json.gz split: train - path: test/zh-CN.json.gz split: test - path: validation/zh-CN.json.gz split: validation - config_name: el data_files: - path: train/el.json.gz split: train - path: test/el.json.gz split: test - path: validation/el.json.gz split: validation - config_name: ru data_files: - path: train/ru.json.gz split: train - path: test/ru.json.gz split: test - path: validation/ru.json.gz split: validation - config_name: te data_files: - path: train/te.json.gz split: train - path: test/te.json.gz split: test - path: validation/te.json.gz split: validation - config_name: cy data_files: - path: train/cy.json.gz split: train - path: test/cy.json.gz split: test - path: validation/cy.json.gz split: validation - config_name: he data_files: - path: train/he.json.gz split: train - path: test/he.json.gz split: test - path: validation/he.json.gz split: validation - config_name: de data_files: - path: train/de.json.gz split: train - path: test/de.json.gz split: test - path: validation/de.json.gz split: validation - config_name: af data_files: - path: train/af.json.gz split: train - path: test/af.json.gz split: test - path: validation/af.json.gz split: validation - config_name: ml data_files: - path: train/ml.json.gz split: train - path: test/ml.json.gz split: test - path: validation/ml.json.gz split: validation - config_name: sl data_files: - path: train/sl.json.gz split: train - path: test/sl.json.gz split: test - path: validation/sl.json.gz split: validation - config_name: vi data_files: - path: train/vi.json.gz split: train - path: test/vi.json.gz split: test - path: validation/vi.json.gz split: validation - config_name: mn data_files: - path: train/mn.json.gz split: train - path: test/mn.json.gz split: test - path: validation/mn.json.gz split: validation - config_name: tl data_files: - path: train/tl.json.gz split: train - path: test/tl.json.gz split: test - path: validation/tl.json.gz split: validation - config_name: it data_files: - path: train/it.json.gz split: train - path: test/it.json.gz split: test - path: validation/it.json.gz split: validation - config_name: jv data_files: - path: train/jv.json.gz split: train - path: test/jv.json.gz split: test - path: validation/jv.json.gz split: validation - config_name: sq data_files: - path: train/sq.json.gz split: train - path: test/sq.json.gz split: test - path: validation/sq.json.gz split: validation - config_name: fa data_files: - path: train/fa.json.gz split: train - path: test/fa.json.gz split: test - path: validation/fa.json.gz split: validation - config_name: nb data_files: - path: train/nb.json.gz split: train - path: test/nb.json.gz split: test - path: validation/nb.json.gz split: validation - config_name: km data_files: - path: train/km.json.gz split: train - path: test/km.json.gz split: test - path: validation/km.json.gz split: validation - config_name: th data_files: - path: train/th.json.gz split: train - path: test/th.json.gz split: test - path: validation/th.json.gz split: validation - config_name: ja data_files: - path: train/ja.json.gz split: train - path: test/ja.json.gz split: test - path: validation/ja.json.gz split: validation - config_name: hi data_files: - path: train/hi.json.gz split: train - path: test/hi.json.gz split: test - path: validation/hi.json.gz split: validation - config_name: id data_files: - path: train/id.json.gz split: train - path: test/id.json.gz split: test - path: validation/id.json.gz split: validation - config_name: kn data_files: - path: train/kn.json.gz split: train - path: test/kn.json.gz split: test - path: validation/kn.json.gz split: validation - config_name: fi data_files: - path: train/fi.json.gz split: train - path: test/fi.json.gz split: test - path: validation/fi.json.gz split: validation - config_name: ur data_files: - path: train/ur.json.gz split: train - path: test/ur.json.gz split: test - path: validation/ur.json.gz split: validation - config_name: my data_files: - path: train/my.json.gz split: train - path: test/my.json.gz split: test - path: validation/my.json.gz split: validation - config_name: lv data_files: - path: train/lv.json.gz split: train - path: test/lv.json.gz split: test - path: validation/lv.json.gz split: validation - config_name: fr data_files: - path: train/fr.json.gz split: train - path: test/fr.json.gz split: test - path: validation/fr.json.gz split: validation - config_name: ko data_files: - path: train/ko.json.gz split: train - path: test/ko.json.gz split: test - path: validation/ko.json.gz split: validation - config_name: sw data_files: - path: train/sw.json.gz split: train - path: test/sw.json.gz split: test - path: validation/sw.json.gz split: validation - config_name: sv data_files: - path: train/sv.json.gz split: train - path: test/sv.json.gz split: test - path: validation/sv.json.gz split: validation - config_name: nl data_files: - path: train/nl.json.gz split: train - path: test/nl.json.gz split: test - path: validation/nl.json.gz split: validation - config_name: da data_files: - path: train/da.json.gz split: train - path: test/da.json.gz split: test - path: validation/da.json.gz split: validation - config_name: ar data_files: - path: train/ar.json.gz split: train - path: test/ar.json.gz split: test - path: validation/ar.json.gz split: validation - config_name: ms data_files: - path: train/ms.json.gz split: train - path: test/ms.json.gz split: test - path: validation/ms.json.gz split: validation - config_name: en data_files: - path: train/en.json.gz split: train - path: test/en.json.gz split: test - path: validation/en.json.gz split: validation - config_name: am data_files: - path: train/am.json.gz split: train - path: test/am.json.gz split: test - path: validation/am.json.gz split: validation - config_name: pt data_files: - path: train/pt.json.gz split: train - path: test/pt.json.gz split: test - path: validation/pt.json.gz split: validation - config_name: ka data_files: - path: train/ka.json.gz split: train - path: test/ka.json.gz split: test - path: validation/ka.json.gz split: validation - config_name: ro data_files: - path: train/ro.json.gz split: train - path: test/ro.json.gz split: test - path: validation/ro.json.gz split: validation - config_name: tr data_files: - path: train/tr.json.gz split: train - path: test/tr.json.gz split: test - path: validation/tr.json.gz split: validation - config_name: hu data_files: - path: train/hu.json.gz split: train - path: test/hu.json.gz split: test - path: validation/hu.json.gz split: validation - config_name: zh-TW data_files: - path: train/zh-TW.json.gz split: train - path: test/zh-TW.json.gz split: test - path: validation/zh-TW.json.gz split: validation - config_name: bn data_files: - path: train/bn.json.gz split: train - path: test/bn.json.gz split: test - path: validation/bn.json.gz split: validation - config_name: hy data_files: - path: train/hy.json.gz split: train - path: test/hy.json.gz split: test - path: validation/hy.json.gz split: validation - config_name: es data_files: - path: train/es.json.gz split: train - path: test/es.json.gz split: test - path: validation/es.json.gz split: validation - config_name: az data_files: - path: train/az.json.gz split: train - path: test/az.json.gz split: test - path: validation/az.json.gz split: validation ---

andstor/methods2test_small

andstor

--- language: - en license: mit task_categories: - text-generation configs: - config_name: fm data_files: - split: train path: data/fm/train-* - split: test path: data/fm/test-* - split: validation path: data/fm/validation-* - config_name: fm_indented data_files: - split: train path: data/fm_indented/train-* - split: test path: data/fm_indented/test-* - split: validation path: data/fm_indented/validation-* - config_name: fm+t data_files: - split: train path: data/fm+t/train-* - split: test path: data/fm+t/test-* - split: validation path: data/fm+t/validation-* - config_name: fm+fc data_files: - split: train path: data/fm+fc/train-* - split: test path: data/fm+fc/test-* - split: validation path: data/fm+fc/validation-* - config_name: fm+fc+t+tc data_files: - split: train path: data/fm+fc+t+tc/train-* - split: test path: data/fm+fc+t+tc/test-* - split: validation path: data/fm+fc+t+tc/validation-* - config_name: fm+fc+c data_files: - split: train path: data/fm+fc+c/train-* - split: test path: data/fm+fc+c/test-* - split: validation path: data/fm+fc+c/validation-* - config_name: fm+fc+c+t+tc data_files: - split: train path: data/fm+fc+c+t+tc/train-* - split: test path: data/fm+fc+c+t+tc/test-* - split: validation path: data/fm+fc+c+t+tc/validation-* - config_name: fm+fc+c+m data_files: - split: train path: data/fm+fc+c+m/train-* - split: test path: data/fm+fc+c+m/test-* - split: validation path: data/fm+fc+c+m/validation-* - config_name: fm+fc+c+m+t+tc data_files: - split: train path: data/fm+fc+c+m+t+tc/train-* - split: test path: data/fm+fc+c+m+t+tc/test-* - split: validation path: data/fm+fc+c+m+t+tc/validation-* - config_name: fm+fc+c+m+f data_files: - split: train path: data/fm+fc+c+m+f/train-* - split: test path: data/fm+fc+c+m+f/test-* - split: validation path: data/fm+fc+c+m+f/validation-* - config_name: fm+fc+c+m+f+t+tc data_files: - split: train path: data/fm+fc+c+m+f+t+tc/train-* - split: test path: data/fm+fc+c+m+f+t+tc/test-* - split: validation path: data/fm+fc+c+m+f+t+tc/validation-* - config_name: t data_files: - split: train path: data/t/train-* - split: test path: data/t/test-* - split: validation path: data/t/validation-* - config_name: t_indented data_files: - split: train path: data/t_indented/train-* - split: test path: data/t_indented/test-* - split: validation path: data/t_indented/validation-* - config_name: t+tc data_files: - split: train path: data/t+tc/train-* - split: test path: data/t+tc/test-* - split: validation path: data/t+tc/validation-* dataset_info: - config_name: fm features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 4696431 num_examples: 7440 - name: test num_bytes: 642347 num_examples: 1017 - name: validation num_bytes: 662917 num_examples: 953 download_size: 2633268 dataset_size: 6001695 - config_name: fm+fc features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 5387123 num_examples: 7440 - name: test num_bytes: 738049 num_examples: 1017 - name: validation num_bytes: 757167 num_examples: 953 download_size: 2925807 dataset_size: 6882339 - config_name: fm+fc+c features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 5906873 num_examples: 7440 - name: test num_bytes: 820149 num_examples: 1017 - name: validation num_bytes: 824441 num_examples: 953 download_size: 3170873 dataset_size: 7551463 - config_name: fm+fc+c+m features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 11930672 num_examples: 7440 - name: test num_bytes: 1610045 num_examples: 1017 - name: validation num_bytes: 1553249 num_examples: 953 download_size: 5406454 dataset_size: 15093966 - config_name: fm+fc+c+m+f features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 12722890 num_examples: 7440 - name: test num_bytes: 1713683 num_examples: 1017 - name: validation num_bytes: 1654607 num_examples: 953 download_size: 5753116 dataset_size: 16091180 - config_name: fm+fc+c+m+f+t+tc features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 18332635 num_examples: 7440 - name: test num_bytes: 2461169 num_examples: 1017 - name: validation num_bytes: 2510969 num_examples: 953 download_size: 8280985 dataset_size: 23304773 - config_name: fm+fc+c+m+t+tc features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 17537661 num_examples: 7440 - name: test num_bytes: 2357359 num_examples: 1017 - name: validation num_bytes: 2409506 num_examples: 953 download_size: 8178222 dataset_size: 22304526 - config_name: fm+fc+c+t+tc features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 11445562 num_examples: 7440 - name: test num_bytes: 1565365 num_examples: 1017 - name: validation num_bytes: 1676986 num_examples: 953 download_size: 5944482 dataset_size: 14687913 - config_name: fm+fc+t+tc features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 10923038 num_examples: 7440 - name: test num_bytes: 1483265 num_examples: 1017 - name: validation num_bytes: 1609296 num_examples: 953 download_size: 5715335 dataset_size: 14015599 - config_name: fm+t features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 8889443 num_examples: 7440 - name: test num_bytes: 1207763 num_examples: 1017 - name: validation num_bytes: 1336798 num_examples: 953 download_size: 4898458 dataset_size: 11434004 - config_name: fm_indented features: - name: id dtype: string - name: text dtype: string splits: - name: train num_bytes: 5054397 num_examples: 7440 - name: test num_bytes: 692948 num_examples: 1017 - name: validation num_bytes: 714462 num_examples: 953 download_size: 2703115 dataset_size: 6461807 - config_name: t features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 4316096 num_examples: 7440 - name: test num_bytes: 582266 num_examples: 1017 - name: validation num_bytes: 689647 num_examples: 953 download_size: 2434024 dataset_size: 5588009 - config_name: t+tc features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 5648321 num_examples: 7440 - name: test num_bytes: 761386 num_examples: 1017 - name: validation num_bytes: 867350 num_examples: 953 download_size: 3024686 dataset_size: 7277057 - config_name: t_indented features: - name: id dtype: string - name: source dtype: string - name: target dtype: string splits: - name: train num_bytes: 4606253 num_examples: 7440 - name: test num_bytes: 623576 num_examples: 1017 - name: validation num_bytes: 734221 num_examples: 953 download_size: 2496661 dataset_size: 5964050 tags: - unit test - java - code pretty_name: Methods2Test Small --- ## Dataset Description Microsoft created the `methods2test` dataset, consisting of Java Junit test cases with their corresponding focal methods. It contains 780k pairs of JUnit test cases and focal methods which were extracted from a total of 91K Java open-source projects hosted on GitHub. This is a smaller subset of the assembled version of the `methods2test` dataset. It provides convenient access to the different context levels based on the raw source code (e.g. newlines are preserved). The test cases and associated classes are also made available. The subset is created by randomly selecting only one sample from each of the 91k projects. The mapping between test case and focal methods is based on heuristics rules and Java developer's best practice. More information can be found here: - [methods2test Github repo](https://github.com/microsoft/methods2test) - [Methods2Test: A dataset of focal methods mapped to test cases](https://arxiv.org/pdf/2203.12776.pdf) ## Dataset Schema ``` t: <TEST_CASE> t+tc: <TEST_CLASS_NAME> <TEST_CASE> fm: <FOCAL_METHOD> fm+t: <FOCAL_METHOD> fm+fc: <FOCAL_CLASS_NAME> <FOCAL_METHOD> fm+fc: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <TEST_CLASS_NAME> <TEST_CASE> fm+fc+c: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> fm+fc+c: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> <TEST_CLASS_NAME> <TEST_CASE> fm+fc+c+m: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> <METHOD_SIGNATURES> fm+fc+c+m: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> <METHOD_SIGNATURES> <TEST_CLASS_NAME> <TEST_CASE> fm+fc+c+m+f: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> <METHOD_SIGNATURES> <FIELDS> fm+fc+c+m+f+t+tc: <FOCAL_CLASS_NAME> <FOCAL_METHOD> <CONTRSUCTORS> <METHOD_SIGNATURES> <FIELDS> <TEST_CLASS_NAME> <TEST_CASE> ``` ## Focal Context - fm: this representation incorporates exclusively the source code of the focal method. Intuitively, this contains the most important information for generating accurate test cases for the given method. - fm+fc: this representation adds the focal class name, which can provide meaningful semantic information to the model. - fm+fc+c: this representation adds the signatures of the constructor methods of the focal class. The idea behind this augmentation is that the test case may require instantiating an object of the focal class in order to properly test the focal method. - fm+fc+c+m: this representation adds the signatures of the other public methods in the focal class. The rationale that motivated this inclusion is that the test case may need to invoke other auxiliary methods within the class (e.g., getters, setters) to set up or tear down the testing environment. - fm+fc+c+m+f: this representation adds the public fields of the focal class. The motivation is that test cases may need to inspect the status of the public fields to properly test a focal method. The test case along with the class name is also provided for each focal context.  The different levels of focal contexts are the following: ``` fm: focal method fm+fc: focal method + focal class name fm+fc+c: focal method + focal class name + constructor signatures fm+fc+c+m: focal method + focal class name + constructor signatures + public method signatures fm+fc+c+m+f: focal method + focal class name + constructor signatures + public method signatures + public fields ```

common-canvas/commoncatalog-cc-by

common-canvas

--- license: cc-by-4.0 dataset_info: features: - name: jpg dtype: image - name: blip2_caption dtype: string - name: caption dtype: string - name: licensename dtype: string - name: licenseurl dtype: string - name: width dtype: int32 - name: height dtype: int32 - name: original_width dtype: int32 - name: original_height dtype: int32 - name: photoid dtype: int64 - name: uid dtype: string - name: unickname dtype: string - name: datetaken dtype: timestamp[us] - name: dateuploaded dtype: int64 - name: capturedevice dtype: string - name: title dtype: string - name: usertags dtype: string - name: machinetags dtype: string - name: longitude dtype: float64 - name: latitude dtype: float64 - name: accuracy dtype: int64 - name: pageurl dtype: string - name: downloadurl dtype: string - name: serverid dtype: int64 - name: farmid dtype: int64 - name: secret dtype: string - name: secretoriginal dtype: string - name: ext dtype: string - name: url dtype: string - name: key dtype: string - name: status dtype: string - name: error_message dtype: string - name: exif dtype: string - name: sha256 dtype: string - name: description dtype: string task_categories: - text-to-image language: - en --- # Dataset Card for CommonCatalog CC-BY This dataset is a large collection of high-resolution Creative Common images (composed of different licenses, see paper Table 1 in the Appendix) collected in 2014 from users of Yahoo Flickr. The dataset contains images of up to 4k resolution, making this one of the highest resolution captioned image datasets. ## Dataset Details ### Dataset Description We provide captions synthetic captions to approximately 100 million high resolution images collected from Yahoo Flickr Creative Commons (YFCC). - **Curated by:** Aaron Gokaslan - **Language(s) (NLP):** en - **License:** See relevant yaml tag / dataset name. ### Dataset Sources <!-- Provide the basic links for the dataset. --> - **Repository:** https://github.com/mosaicml/diffusion - **Paper:** https://arxiv.org/abs/2310.16825 - **Demo:** See CommonCanvas Gradios ## Uses We use CommonCatalog to train a family latent diffusion models called CommonCanvas. The goal is to produce a model that is competitive with Stable Diffusion 2, but to do so using an easily accessible dataset of known provenance. Doing so makes replicating the model significantly easier, and provides a clearer mechanism for applying training-data attribution techniques. ### Direct Use Training text-to-image models Training image-to-text models ### Out-of-Scope Use <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. --> * Crafting content that is offensive or injurious towards individuals, including negative portrayals of their living conditions, cultural backgrounds, religious beliefs, etc. * Deliberately creating or spreading content that is discriminatory or reinforces harmful stereotypes. * Falsely representing individuals without their permission. * Generating sexual content that may be seen by individuals without their consent. * Producing or disseminating false or misleading information. * Creating content that depicts extreme violence or bloodshed. * Distributing content that modifies copyrighted or licensed material in a way that breaches its usage terms. ## Dataset Structure The dataset is divided into 10 subsets each containing parquets about 4GB each. Each subfolder within contains a resolution range of the images and their respective aspect ratios. The dataset is also divided along images licensed for commercial use (C) and those that are not (NC). ## Dataset Creation ### Curation Rationale Creating a standardized, accessible dataset with synthetic caption and releasing it so other people can train on a common dataset for open source image generation. ### Source Data Yahoo Flickr Creative Commons 100M Dataset and Synthetically Generated Caption Data. #### Data Collection and Processing All synthetic captions were generated with BLIP2. See paper for more details. #### Who are the source data producers? <!-- This section describes the people or systems who originally created the data. It should also include self-reported demographic or identity information for the source data creators if this information is available. --> Users of Flickr ## Bias, Risks, and Limitations See Yahoo Flickr Creative Commons 100M dataset for more information. The information was collected circa 2014 and known to have a bias towards internet connected Western countries. Some areas such as the global south lack representation. ## Citation **BibTeX:** ``` @article{gokaslan2023commoncanvas, title={CommonCanvas: An Open Diffusion Model Trained with Creative-Commons Images}, author={Gokaslan, Aaron and Cooper, A Feder and Collins, Jasmine and Seguin, Landan and Jacobson, Austin and Patel, Mihir and Frankle, Jonathan and Stephenson, Cory and Kuleshov, Volodymyr}, journal={arXiv preprint arXiv:2310.16825}, year={2023} } ``` ## Dataset Card Authors [Aaron Gokaslan](https://huggingface.co/Skylion007) ## Dataset Card Contact [Aaron Gokaslan](https://huggingface.co/Skylion007)