Datasets:

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XeTute/Pakistani-Developer

XeTute

--- license: mit task_categories: - question-answering - text-generation - text2text-generation language: - en tags: - conversational - alpaca - pakistan - pakistani - developer - coder - programming - js - javascript - python - c++ - cpp - general - synthetic size_categories: - 1K<n<10K formats: - json --- # Pakistani Developer > [!TIP] > Data Synthetically generated using [XeTute/Synthetic-Data-Generation](https://github.com/XeTute/Synthetic-Data-Generation) The Pakistani-Developer dataset contains exactly 1024 input-output pairs in the JSON-Alpaca format. Topics are: - Pakistan: Culature - Religion: Islam - Basic STEM: Mathematics, Physics, et cetera - Programming / Scripting: JavaScript, Python, C++ and maybe some other, well known languages We understand that this dataset is not especially large, but it can be used to fine-tune a model smaller than ~20B parameters to improve its performance on the topics mentioned above. The entire dataset was generated by Qwen/Qwen2.5-32B-Instruct. **To improve the model's performance on especially one of the topics above, please consider using a specialized dataset in combination to this one:** - For Pakistan (only 131 samples): [XeTute/Pakistan-China-Alpaca](https://huggingface.co/datasets/XeTute/Pakistan-China-Alpaca) - For Islam: No (English-Language) datasets currently exist on HuggingFace, we're working on one - For STEM: [anothy1/fineweb-edu-cleaned-simplified](https://huggingface.co/datasets/anothy1/fineweb-edu-cleaned-simplified) - Programming / Scripting: [sahil2801/CodeAlpaca-20k](https://huggingface.co/datasets/sahil2801/CodeAlpaca-20k) **Happy coding!** --- # Our Apps & Socials [Chat with our Assistant](https://xetute.com/) | [Support us Financially](https://ko-fi.com/XeTute) | [Visit our GitHub](https://github.com/XeTute) Long live the Islamic Republic of Pakistan; Glory to the Islamic Republic of Pakistan 🇵🇰 

HoangHa/Pensez-v0.1-formatted

HoangHa

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: source dtype: string - name: token_count dtype: int64 splits: - name: train num_bytes: 31099692 num_examples: 2000 download_size: 14501308 dataset_size: 31099692 configs: - config_name: default data_files: - split: train path: data/train-* ---

ryzentm/turkmence_all_data

ryzentm

--- dataset_info: features: - name: instruction dtype: string - name: input dtype: string - name: response dtype: string splits: - name: train num_bytes: 75481407.0 num_examples: 502200 - name: test num_bytes: 8386823.0 num_examples: 55800 download_size: 33698033 dataset_size: 83868230.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

sunyiyou/s1K_no_aime

sunyiyou

--- dataset_info: features: - name: solution dtype: string - name: question dtype: string - name: cot_type dtype: string - name: source_type dtype: string - name: metadata dtype: string - name: cot dtype: 'null' - name: thinking_trajectories sequence: string - name: attempt dtype: string - name: text dtype: string splits: - name: train num_bytes: 22645622 num_examples: 713 download_size: 9046522 dataset_size: 22645622 configs: - config_name: default data_files: - split: train path: data/train-* ---

guerwan/github-issues

guerwan

--- annotations_creators: - no-annotation language: - en language_creators: - found license: - unknown multilinguality: - monolingual pretty_name: Hugging Face Github Issues size_categories: - 1K<n<10K source_datasets: [] tags: [] task_categories: - text-classification - text-retrieval task_ids: - multi-class-classification - multi-label-classification - document-retrieval dataset_info: features: - name: url dtype: string - name: repository_url dtype: string - name: labels_url dtype: string - name: comments_url dtype: string - name: events_url dtype: string - name: html_url dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: number dtype: int64 - name: title dtype: string - name: user struct: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: user_view_type dtype: string - name: site_admin dtype: bool - name: labels list: - name: id dtype: int64 - name: node_id dtype: string - name: url dtype: string - name: name dtype: string - name: color dtype: string - name: default dtype: bool - name: description dtype: string - name: state dtype: string - name: locked dtype: bool - name: assignee struct: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: user_view_type dtype: string - name: site_admin dtype: bool - name: assignees list: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: user_view_type dtype: string - name: site_admin dtype: bool - name: comments_nb dtype: int64 - name: created_at dtype: timestamp[s] - name: updated_at dtype: timestamp[s] - name: closed_at dtype: timestamp[s] - name: author_association dtype: string - name: sub_issues_summary struct: - name: total dtype: int64 - name: completed dtype: int64 - name: percent_completed dtype: int64 - name: body dtype: string - name: closed_by struct: - name: login dtype: string - name: id dtype: int64 - name: node_id dtype: string - name: avatar_url dtype: string - name: gravatar_id dtype: string - name: url dtype: string - name: html_url dtype: string - name: followers_url dtype: string - name: following_url dtype: string - name: gists_url dtype: string - name: starred_url dtype: string - name: subscriptions_url dtype: string - name: organizations_url dtype: string - name: repos_url dtype: string - name: events_url dtype: string - name: received_events_url dtype: string - name: type dtype: string - name: user_view_type dtype: string - name: site_admin dtype: bool - name: reactions struct: - name: url dtype: string - name: total_count dtype: int64 - name: '+1' dtype: int64 - name: '-1' dtype: int64 - name: laugh dtype: int64 - name: hooray dtype: int64 - name: confused dtype: int64 - name: heart dtype: int64 - name: rocket dtype: int64 - name: eyes dtype: int64 - name: timeline_url dtype: string - name: state_reason dtype: string - name: draft dtype: bool - name: pull_request struct: - name: url dtype: string - name: html_url dtype: string - name: diff_url dtype: string - name: patch_url dtype: string - name: merged_at dtype: timestamp[s] - name: is_pull_request dtype: bool - name: comments sequence: string splits: - name: train num_bytes: 44697794 num_examples: 7351 download_size: 12222976 dataset_size: 44697794 configs: - config_name: default data_files: - split: train path: data/train-* --- # 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]

quickmt/quickmt-train.de-en

quickmt

--- license: cc-by-4.0 dataset_info: features: - name: de dtype: string - name: en dtype: string - name: sco dtype: float64 splits: - name: train num_bytes: 123972692242 num_examples: 523199100 download_size: 86204251840 dataset_size: 123972692242 configs: - config_name: default data_files: - split: train path: data/train-* --- # `quickmt` de-en Training Corpus Contains the following datasets downloaded with `mtdata` after deduplication and [basic filtering](https://github.com/quickmt/quickmt/blob/main/quickmt/scripts/clean.py) with `quickmt`: * Statmt-commoncrawl_wmt13-1-deu-eng * Statmt-europarl_wmt13-7-deu-eng * Statmt-news_commentary_wmt18-13-deu-eng * Statmt-europarl-9-deu-eng * Statmt-europarl-7-deu-eng * Statmt-news_commentary-14-deu-eng * Statmt-news_commentary-15-deu-eng * Statmt-news_commentary-16-deu-eng * Statmt-news_commentary-17-deu-eng * Statmt-news_commentary-18-deu-eng * Statmt-news_commentary-18.1-deu-eng * Statmt-newstest_deen-2014-deu-eng * Statmt-newstest_ende-2015-eng-deu * Statmt-newstest_deen-2015-deu-eng * Statmt-newstest_deen-2016-deu-eng * Statmt-newstest_ende-2016-eng-deu * Statmt-newstest_ende-2017-eng-deu * Statmt-newstest_deen-2017-deu-eng * Statmt-newstest_ende-2018-eng-deu * Statmt-newstest_deen-2018-deu-eng * Statmt-newstest_deen-2019-deu-eng * Statmt-newstest_ende-2019-eng-deu * Statmt-newstest-2009-eng-deu * Statmt-newstest-2010-eng-deu * Statmt-newstest-2011-eng-deu * Statmt-newstest-2012-eng-deu * Statmt-newstest-2013-eng-deu * Statmt-newstest_deen-2020-deu-eng * Statmt-newstest_ende-2020-eng-deu * Statmt-newstestb_deen-2020-deu-eng * Statmt-newstestb_ende-2020-eng-deu * Statmt-newstest_deen-2021-deu-eng * Statmt-newstest_ende-2021-eng-deu * Statmt-europarl-10-deu-eng * Tilde-eesc-2017-deu-eng * Tilde-ema-2016-deu-eng * Tilde-airbaltic-1-deu-eng * Tilde-czechtourism-1-deu-eng * Tilde-ecb-2017-deu-eng * Tilde-rapid-2016-deu-eng * Tilde-rapid-2019-deu-eng * Facebook-wikimatrix-1-deu-eng * Lindat-khresmoi_summary_test-2-deu-eng * Lindat-khresmoi_summary_dev-2-deu-eng * Neulab-tedtalks_train-1-eng-deu * Neulab-tedtalks_test-1-eng-deu * Neulab-tedtalks_dev-1-eng-deu * ELRC-swedish_labour_part2-1-deu-eng * ELRC-rights_arrested-1-deu-eng * ELRC-swedish_labour_part1-1-deu-eng * ELRC-swedish_social_security-1-deu-eng * ELRC-swedish_work_environment-1-deu-eng * ELRC-federal_constitutional_law_austria-1-deu_DE-eng_GB * ELRC-bmvi_publications-1-deu_DE-eng_GB * ELRC-bmvi_website-1-deu_DE-eng_GB * ELRC-bmi_brochure_civil_protection-1-deu_DE-eng_GB * ELRC-bmi_brochures_2016-1-deu_DE-eng_GB * ELRC-bmi_brochures_2011_2015-1-deu_DE-eng_GB * ELRC-sip-1-deu_LU-eng * ELRC-luxembourg.lu-1-deu-eng * ELRC-federal_foreign_berlin-1-deu_DE-eng_GB * ELRC-presidency-1-deu-eng * ELRC-by_presidency_council_held_by_austria_2006-1-deu-eng * ELRC-by_presidency_council_held_by_luxembourg_2015-1-deu-eng * ELRC-charter_values_citizenship_integration-1-deu-eng * ELRC-euipo_law-1-deu-eng * ELRC-information_portal_german_state_chancellery-1-deu_DE-eng * ELRC-german_foreign_office_2016-1-deu_DE-eng_GB * ELRC-german_foreign_office_2017-1-deu_DE-eng_GB * ELRC-german_foreign_office_2018-1-deu_DE-eng_GB * ELRC-euipo_list-1-deu-eng * ELRC-cordis_news-1-deu-eng * ELRC-cordis_results_brief-1-deu-eng * ELRC-energy_report_city_vienna-1-deu_AT-eng_GB * ELRC-austrian_research_technology_report_2015-1-deu_AT-eng_GB * ELRC-2017_activity_report_hohe_tauern_park-1-deu_AT-eng_GB * ELRC-vienna_environmental_report2004_2005-1-deu_AT-eng_GB * ELRC-euipo_2017-1-deu-eng * ELRC-portal_oficial_turismo_españa_www.spain.info-1-deu_DE-eng_GB * ELRC-artigos_visitportugal_2007-1-deu-eng * ELRC-localidades_2007-1-deu-eng * ELRC-museus_2007-1-deu-eng * ELRC-arquitectura_2007-1-deu-eng * ELRC-património_açores_2006-1-deu-eng * ELRC-monumentos_2007-1-deu-eng * ELRC-parques_e_reservas_2007-1-deu-eng * ELRC-praias_2007-1-deu-eng * ELRC-emea-1-deu-eng * ELRC-vaccination-1-deu-eng * ELRC-eu_publications_medical_v2-1-deu-eng * ELRC-wikipedia_health-1-deu-eng * ELRC-antibiotic-1-deu-eng * ELRC-europarl_covid-1-deu-eng * ELRC-ec_europa_covid-1-deu-eng * ELRC-eur_lex_covid-1-deu-eng * ELRC-presscorner_covid-1-deu-eng * ELRC-development_funds_regional_policy-1-deu-eng * ELRC-customer_support_mt_test_set-1-deu-eng * ELRC-scipar-1-deu-eng * ELRC-information_crime_victims_processed-1-eng-deu * ELRC-web_acquired_data_related_to_scientific_research-1-eng-deu * ELRC-hrw_dataset_v1-1-eng-deu * ELRC-cef_data_marketplace-1-eng-deu * EU-ecdc-1-eng-deu * EU-eac_forms-1-deu-eng * EU-eac_reference-1-deu-eng * EU-dcep-1-deu-eng * LinguaTools-wikititles-2014-deu-eng * OPUS-books-v1-deu-eng * OPUS-dgt-v2019-deu-eng * OPUS-dgt-v4-deu-eng * OPUS-ecb-v1-deu-eng * OPUS-ecdc-v20160316-deu-eng * OPUS-elitr_eca-v1-deu-eng * OPUS-elra_w0143-v1-deu-eng * OPUS-elra_w0197-v1-deu-eng_GB * OPUS-elra_w0198-v1-deu-eng_GB * OPUS-elra_w0199-v1-deu-eng_GB * OPUS-elra_w0200-v1-deu-eng_GB * OPUS-elra_w0201-v1-deu-eng * OPUS-elra_w0301-v1-deu-eng * OPUS-elrc_1077_euipo_law-v1-deu-eng * OPUS-elrc_1086_information_portal_g-v1-deu-eng * OPUS-elrc_1088_german_foreign_offic-v1-deu-eng * OPUS-elrc_1089_german_foreign_offic-v1-deu-eng * OPUS-elrc_1090_german_foreign_offic-v1-deu-eng * OPUS-elrc_1092_euipo_list-v1-deu-eng * OPUS-elrc_1117_cordis_news-v1-deu-eng * OPUS-elrc_1121_cordis_results_brief-v1-deu-eng * OPUS-elrc_1238_energy_report_city-v1-deu-eng * OPUS-elrc_1240_austrian_research_te-v1-deu-eng * OPUS-elrc_1241_2017_activity_report-v1-deu-eng * OPUS-elrc_1243_vienna_environmental-v1-deu-eng * OPUS-elrc_2014_euipo_2017-v1-deu-eng * OPUS-elrc_2410_portal_oficial_turis-v1-deu-eng * OPUS-elrc_2612_artigos_visitportuga-v1-deu-eng * OPUS-elrc_2614_localidades_2007-v1-deu-eng * OPUS-elrc_2616_museus_2007-v1-deu-eng * OPUS-elrc_2622_arquitectura_2007-v1-deu-eng * OPUS-elrc_2623_patrimnio_aores_2006-v1-deu-eng * OPUS-elrc_2638_monumentos_2007-v1-deu-eng * OPUS-elrc_2639_parques_e_reservas-v1-deu-eng * OPUS-elrc_2641_praias_2007-v1-deu-eng * OPUS-elrc_2714_emea-v1-deu-eng * OPUS-elrc_2736_vaccination-v1-deu-eng * OPUS-elrc_2875_eu_publications_medi-v1-deu-eng * OPUS-elrc_3063_wikipedia_health-v1-deu-eng * OPUS-elrc_3202_antibiotic-v1-deu-eng * OPUS-elrc_3293_europarl_covid-v1-deu-eng * OPUS-elrc_3464_ec_europa_covid-v1-deu-eng * OPUS-elrc_3565_eur_lex_covid-v1-deu-eng * OPUS-elrc_3606_presscorner_covid-v1-deu-eng * OPUS-elrc_3852_development_funds_re-v1-deu-eng * OPUS-elrc_401_swedish_labour_part2-v1-deu-eng * OPUS-elrc_403_rights_arrested-v1-deu-eng * OPUS-elrc_406_swedish_labour_part1-v1-deu-eng * OPUS-elrc_416_swedish_social_secur-v1-deu-eng * OPUS-elrc_417_swedish_work_environ-v1-deu-eng * OPUS-elrc_4992_customer_support_mt-v1-deu-eng * OPUS-elrc_5067_scipar-v1-deu-eng * OPUS-elrc_5220_information_crime_vi-v1-deu-eng * OPUS-elrc_621_federal_constitution-v1-deu-eng * OPUS-elrc_630_bmvi_publications-v1-deu-eng * OPUS-elrc_631_bmvi_website-v1-deu-eng * OPUS-elrc_632_bmi_brochure_civil-v1-deu-eng * OPUS-elrc_633_bmi_brochures_2016-v1-deu-eng * OPUS-elrc_634_bmi_brochures_2011-v1-deu-eng * OPUS-elrc_637_sip-v1-deu-eng * OPUS-elrc_638_luxembourg.lu-v1-deu-eng * OPUS-elrc_642_federal_foreign_berl-v1-deu-eng * OPUS-elrc_774_presidency-v1-deu-eng * OPUS-elrc_775_by_presidency_counci-v1-deu-eng * OPUS-elrc_776_by_presidency_counci-v1-deu-eng * OPUS-elrc_832_charter_values_citiz-v1-deu-eng * OPUS-elrc_arquitectura_2007-v1-deu-eng * OPUS-elrc_artigos_visitportuga-v1-deu-eng * OPUS-elrc_cordis_news-v1-deu-eng * OPUS-elrc_cordis_results-v1-deu-eng * OPUS-elrc_ec_europa-v1-deu-eng * OPUS-elrc_emea-v1-deu-eng * OPUS-elrc_euipo_2017-v1-deu-eng * OPUS-elrc_euipo_law-v1-deu-eng * OPUS-elrc_euipo_list-v1-deu-eng * OPUS-elrc_europarl_covid-v1-deu-eng * OPUS-elrc_eur_lex-v1-deu-eng * OPUS-elrc_eu_publications-v1-deu-eng * OPUS-elrc_federal_foreign-v1-deu-eng_GB * OPUS-elrc_german_foreign-v1-deu-eng_GB * OPUS-elrc_information_portal-v1-deu-eng * OPUS-elrc_localidades_2007-v1-deu-eng * OPUS-elrc_museus_2007-v1-deu-eng * OPUS-elrc_parques_e-v1-deu-eng * OPUS-elrc_patrimnio_aores-v1-deu-eng * OPUS-elrc_praias_2007-v1-deu-eng * OPUS-elrc_swedish_labour-v1-deu-eng * OPUS-elrc_termitur-v1-deu-eng * OPUS-elrc_antibiotic-v1-deu-eng * OPUS-elrc_presscorner_covid-v1-deu-eng * OPUS-elrc_vaccination-v1-deu-eng * OPUS-elrc_wikipedia_health-v1-deu-eng * OPUS-elrc_2682-v1-deu-eng * OPUS-elrc_2922-v1-deu-eng * OPUS-elrc_2923-v1-deu-eng * OPUS-elrc_3382-v1-deu-eng * OPUS-emea-v3-deu-eng * OPUS-eubookshop-v2-deu-eng * OPUS-euconst-v1-deu-eng * OPUS-europat-v1-deu-eng * OPUS-europat-v2-deu-eng * OPUS-europat-v3-deu-eng * OPUS-europarl-v3-deu-eng * OPUS-europarl-v7-deu-eng * OPUS-europarl-v8-deu-eng * OPUS-gnome-v1-deu-eng * OPUS-globalvoices-v2015-deu-eng * OPUS-globalvoices-v2017q3-deu-eng * OPUS-globalvoices-v2018q4-deu-eng * OPUS-jrc_acquis-v3.0-deu-eng * OPUS-kde4-v2-deu-eng * OPUS-kdedoc-v1-deu-eng_GB * OPUS-mpc1-v1-deu-eng * OPUS-multiun-v1-deu-eng * OPUS-nllb-v1-deu-eng * OPUS-neulab_tedtalks-v1-deu-eng * OPUS-news_commentary-v11-deu-eng * OPUS-news_commentary-v14-deu-eng * OPUS-news_commentary-v16-deu-eng * OPUS-news_commentary-v9.0-deu-eng * OPUS-news_commentary-v9.1-deu-eng * OPUS-openoffice-v2-deu-eng * OPUS-openoffice-v3-deu-eng_GB * OPUS-opensubtitles-v1-deu-eng * OPUS-opensubtitles-v2016-deu-eng * OPUS-opensubtitles-v2018-deu-eng * OPUS-php-v1-deu-eng * OPUS-paracrawl-v9-deu-eng * OPUS-qed-v2.0a-deu-eng * OPUS-rf-v1-deu-eng * OPUS-salome-v1-deu-eng * OPUS-stanfordnlp_nmt-v1.0-eng-deu * OPUS-ted2013-v1.1-deu-eng * OPUS-ted2020-v1-deu-eng * OPUS-tanzil-v1-deu-eng * OPUS-tatoeba-v2-deu-eng * OPUS-tatoeba-v20190709-deu-eng * OPUS-tatoeba-v20200531-deu-eng * OPUS-tatoeba-v20201109-deu-eng * OPUS-tatoeba-v20210310-deu-eng * OPUS-tatoeba-v20210722-deu-eng * OPUS-tatoeba-v20220303-deu-eng * OPUS-tatoeba-v20230412-deu-eng * OPUS-tildemodel-v2018-deu-eng * OPUS-ubuntu-v14.10-deu-eng * OPUS-wmt_news-v2014-deu-eng * OPUS-wmt_news-v2019-deu-eng * OPUS-wikimatrix-v1-deu-eng * OPUS-wikipedia-v1.0-deu-eng * OPUS-bible_uedin-v1-deu-eng * OPUS-tldr_pages-v20230829-deu-eng

adrlau/openscad-vision0

adrlau

--- dataset_info: features: - name: user dtype: string - name: assistant dtype: string - name: images list: image splits: - name: train num_bytes: 411093434.0 num_examples: 500 download_size: 407223777 dataset_size: 411093434.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

obiwan96/obiwan96open_web_math_qav3_none

obiwan96

--- dataset_info: features: - name: query dtype: string - name: completion dtype: string splits: - name: train num_bytes: 544854393.5281566 num_examples: 143360 - name: test num_bytes: 28679347.4718434 num_examples: 7546 download_size: 228600184 dataset_size: 573533741.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

adrlau/openscad-vision1

adrlau

--- dataset_info: features: - name: user dtype: string - name: assistant dtype: string - name: images list: image splits: - name: train num_bytes: 411092848.0 num_examples: 500 download_size: 407222253 dataset_size: 411092848.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

embodied-ai/piper_shirt_hanging_test_louis_Sat22_test

embodied-ai

--- license: apache-2.0 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:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "piper_ros", "total_episodes": 5, "total_frames": 16063, "total_tasks": 1, "total_videos": 20, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:5" }, "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": { "action": { "dtype": "float32", "shape": [ 14 ], "names": [ "left_waist", "left_shoulder", "left_elbow", "left_forearm_roll", "left_wrist_angle", "left_wrist_rotate", "left_gripper", "right_waist", "right_shoulder", "right_elbow", "right_forearm_roll", "right_wrist_angle", "right_wrist_rotate", "right_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 14 ], "names": [ "left_waist", "left_shoulder", "left_elbow", "left_forearm_roll", "left_wrist_angle", "left_wrist_rotate", "left_gripper", "right_waist", "right_shoulder", "right_elbow", "right_forearm_roll", "right_wrist_angle", "right_wrist_rotate", "right_gripper" ] }, "observation.images.cam_high": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_low": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_left_wrist": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_wrist": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

JimboDDjh/MoneyEgg007

JimboDDjh

--- license: unknown ---

garavv/NL2linux

garavv

--- dataset_info: features: - name: input dtype: string - name: output dtype: string - name: instruction dtype: string splits: - name: train num_bytes: 23057842 num_examples: 40550 download_size: 3221373 dataset_size: 23057842 configs: - config_name: default data_files: - split: train path: data/train-* ---

zijian2022/moss_test

zijian2022

--- license: apache-2.0 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:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "koch", "total_episodes": 4, "total_frames": 1192, "total_tasks": 1, "total_videos": 8, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:4" }, "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": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.camera_front": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.camera_top": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

EuskadIA/dictionnaire_gastromomique_basque

EuskadIA

--- language: - fr - eu viewer: false task_categories: - translation multilinguality: - multilingual --- > [!NOTE] > Dataset origin: https://www.vitoria-gasteiz.org/wb021/http/contenidosEstaticos/adjuntos/es/94/14/49414.pdf

zaringleb/eval_so100_cube_5_eval_1_60k

zaringleb

--- license: apache-2.0 task_categories: - robotics tags: - LeRobot - so100 configs: - config_name: default data_files: data/*/*.parquet --- This dataset was created using [LeRobot](https://github.com/huggingface/lerobot). ## Dataset Description - **Homepage:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "so100", "total_episodes": 20, "total_frames": 5960, "total_tasks": 1, "total_videos": 20, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:20" }, "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": { "action": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 6 ], "names": [ "main_shoulder_pan", "main_shoulder_lift", "main_elbow_flex", "main_wrist_flex", "main_wrist_roll", "main_gripper" ] }, "observation.images.cam_high": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "av1", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

Ahmed3310/llama3_sdxl_prompt_generator

Ahmed3310

--- dataset_info: features: - name: prompt dtype: string splits: - name: train num_bytes: 74856 num_examples: 101 download_size: 16885 dataset_size: 74856 configs: - config_name: default data_files: - split: train path: data/train-* ---

MikeGreen2710/hn_feb_0_ppbs

MikeGreen2710

--- dataset_info: features: - name: week_period dtype: string - name: weighted_mean_price dtype: float64 - name: variance_street_index dtype: float64 - name: count_example dtype: float64 - name: posterior_price dtype: float64 - name: observation_weight dtype: float64 - name: smoothed_price dtype: float64 - name: posterior_weight dtype: float64 - name: observation_reliable dtype: float64 - name: smoothed_price_lower dtype: float64 - name: smoothed_price_upper dtype: float64 - name: city dtype: string - name: district dtype: string - name: ward dtype: string - name: street dtype: string - name: mean_street_index dtype: float64 - name: final_mean_price dtype: float64 splits: - name: train num_bytes: 9800518 num_examples: 50197 download_size: 2926333 dataset_size: 9800518 configs: - config_name: default data_files: - split: train path: data/train-* ---

hieunguyen1053/luatvietnam_embedding

hieunguyen1053

--- dataset_info: - config_name: articles_mix_not_have_clause features: - name: DocId dtype: int64 - name: ArticleContent dtype: string - name: ArticleId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 109370122 num_examples: 9431 download_size: 27270198 dataset_size: 109370122 - config_name: articles_not_have_clause features: - name: DocId dtype: int64 - name: ArticleContent dtype: string - name: ArticleId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 755094125 num_examples: 72073 download_size: 187988221 dataset_size: 755094125 - config_name: clause_mix_not_have_point features: - name: DocId dtype: int64 - name: ArticleId dtype: string - name: ClauseContent dtype: string - name: Prefix dtype: string - name: ClauseId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 941429358 num_examples: 98671 download_size: 232065215 dataset_size: 941429358 - config_name: clause_not_have_point features: - name: DocId dtype: int64 - name: ArticleId dtype: string - name: ClauseContent dtype: string - name: Prefix dtype: string - name: ClauseId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 3248277920 num_examples: 341998 download_size: 803470116 dataset_size: 3248277920 - config_name: point features: - name: DocId dtype: int64 - name: ArticleId dtype: string - name: Prefix dtype: string - name: ClauseId dtype: string - name: PointContent dtype: string - name: PointId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 3491676519 num_examples: 354719 download_size: 831506443 dataset_size: 3491676519 - config_name: point_mix features: - name: DocId dtype: int64 - name: ArticleId dtype: string - name: Prefix dtype: string - name: ClauseId dtype: string - name: PointContent dtype: string - name: PointId dtype: string - name: text dtype: string - name: num_tokens dtype: int64 - name: embedding sequence: float64 splits: - name: train num_bytes: 1136703220 num_examples: 117346 download_size: 260065204 dataset_size: 1136703220 configs: - config_name: articles_mix_not_have_clause data_files: - split: train path: articles_mix_not_have_clause/train-* - config_name: articles_not_have_clause data_files: - split: train path: articles_not_have_clause/train-* - config_name: clause_mix_not_have_point data_files: - split: train path: clause_mix_not_have_point/train-* - config_name: clause_not_have_point data_files: - split: train path: clause_not_have_point/train-* - config_name: point data_files: - split: train path: point/train-* - config_name: point_mix data_files: - split: train path: point_mix/train-* ---

aelbereth/srm-ft-class-1

aelbereth

--- license: apache-2.0 ---

shruthigudimalla/pricer-data

shruthigudimalla

--- dataset_info: features: - name: text dtype: string - name: price dtype: float64 splits: - name: train num_bytes: 313746593 num_examples: 400000 - name: test num_bytes: 1558981 num_examples: 2000 download_size: 188212928 dataset_size: 315305574 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

gametwix/rummlu

gametwix

--- language: - ru license: mit configs: - config_name: abstract_algebra data_files: - split: test path: data/abstract_algebra/test.jsonl - split: dev path: data/abstract_algebra/dev.jsonl - config_name: anatomy data_files: - split: test path: data/anatomy/test.jsonl - split: dev path: data/anatomy/dev.jsonl - config_name: astronomy data_files: - split: test path: data/astronomy/test.jsonl - split: dev path: data/astronomy/dev.jsonl - config_name: business_ethics data_files: - split: test path: data/business_ethics/test.jsonl - split: dev path: data/business_ethics/dev.jsonl - config_name: clinical_knowledge data_files: - split: test path: data/clinical_knowledge/test.jsonl - split: dev path: data/clinical_knowledge/dev.jsonl - config_name: college_biology data_files: - split: test path: data/college_biology/test.jsonl - split: dev path: data/college_biology/dev.jsonl - config_name: college_chemistry data_files: - split: test path: data/college_chemistry/test.jsonl - split: dev path: data/college_chemistry/dev.jsonl - config_name: college_computer_science data_files: - split: test path: data/college_computer_science/test.jsonl - split: dev path: data/college_computer_science/dev.jsonl - config_name: college_mathematics data_files: - split: test path: data/college_mathematics/test.jsonl - split: dev path: data/college_mathematics/dev.jsonl - config_name: college_medicine data_files: - split: test path: data/college_medicine/test.jsonl - split: dev path: data/college_medicine/dev.jsonl - config_name: college_physics data_files: - split: test path: data/college_physics/test.jsonl - split: dev path: data/college_physics/dev.jsonl - config_name: computer_security data_files: - split: test path: data/computer_security/test.jsonl - split: dev path: data/computer_security/dev.jsonl - config_name: conceptual_physics data_files: - split: test path: data/conceptual_physics/test.jsonl - split: dev path: data/conceptual_physics/dev.jsonl - config_name: econometrics data_files: - split: test path: data/econometrics/test.jsonl - split: dev path: data/econometrics/dev.jsonl - config_name: electrical_engineering data_files: - split: test path: data/electrical_engineering/test.jsonl - split: dev path: data/electrical_engineering/dev.jsonl - config_name: elementary_mathematics data_files: - split: test path: data/elementary_mathematics/test.jsonl - split: dev path: data/elementary_mathematics/dev.jsonl - config_name: formal_logic data_files: - split: test path: data/formal_logic/test.jsonl - split: dev path: data/formal_logic/dev.jsonl - config_name: global_facts data_files: - split: test path: data/global_facts/test.jsonl - split: dev path: data/global_facts/dev.jsonl - config_name: high_school_biology data_files: - split: test path: data/high_school_biology/test.jsonl - split: dev path: data/high_school_biology/dev.jsonl - config_name: high_school_chemistry data_files: - split: test path: data/high_school_chemistry/test.jsonl - split: dev path: data/high_school_chemistry/dev.jsonl - config_name: high_school_computer_science data_files: - split: test path: data/high_school_computer_science/test.jsonl - split: dev path: data/high_school_computer_science/dev.jsonl - config_name: high_school_european_history data_files: - split: test path: data/high_school_european_history/test.jsonl - split: dev path: data/high_school_european_history/dev.jsonl - config_name: high_school_geography data_files: - split: test path: data/high_school_geography/test.jsonl - split: dev path: data/high_school_geography/dev.jsonl - config_name: high_school_government_and_politics data_files: - split: test path: data/high_school_government_and_politics/test.jsonl - split: dev path: data/high_school_government_and_politics/dev.jsonl - config_name: high_school_macroeconomics data_files: - split: test path: data/high_school_macroeconomics/test.jsonl - split: dev path: data/high_school_macroeconomics/dev.jsonl - config_name: high_school_mathematics data_files: - split: test path: data/high_school_mathematics/test.jsonl - split: dev path: data/high_school_mathematics/dev.jsonl - config_name: high_school_microeconomics data_files: - split: test path: data/high_school_microeconomics/test.jsonl - split: dev path: data/high_school_microeconomics/dev.jsonl - config_name: high_school_physics data_files: - split: test path: data/high_school_physics/test.jsonl - split: dev path: data/high_school_physics/dev.jsonl - config_name: high_school_psychology data_files: - split: test path: data/high_school_psychology/test.jsonl - split: dev path: data/high_school_psychology/dev.jsonl - config_name: high_school_statistics data_files: - split: test path: data/high_school_statistics/test.jsonl - split: dev path: data/high_school_statistics/dev.jsonl - config_name: high_school_us_history data_files: - split: test path: data/high_school_us_history/test.jsonl - split: dev path: data/high_school_us_history/dev.jsonl - config_name: high_school_world_history data_files: - split: test path: data/high_school_world_history/test.jsonl - split: dev path: data/high_school_world_history/dev.jsonl - config_name: human_aging data_files: - split: test path: data/human_aging/test.jsonl - split: dev path: data/human_aging/dev.jsonl - config_name: human_sexuality data_files: - split: test path: data/human_sexuality/test.jsonl - split: dev path: data/human_sexuality/dev.jsonl - config_name: international_law data_files: - split: test path: data/international_law/test.jsonl - split: dev path: data/international_law/dev.jsonl - config_name: jurisprudence data_files: - split: test path: data/jurisprudence/test.jsonl - split: dev path: data/jurisprudence/dev.jsonl - config_name: logical_fallacies data_files: - split: test path: data/logical_fallacies/test.jsonl - split: dev path: data/logical_fallacies/dev.jsonl - config_name: machine_learning data_files: - split: test path: data/machine_learning/test.jsonl - split: dev path: data/machine_learning/dev.jsonl - config_name: management data_files: - split: test path: data/management/test.jsonl - split: dev path: data/management/dev.jsonl - config_name: marketing data_files: - split: test path: data/marketing/test.jsonl - split: dev path: data/marketing/dev.jsonl - config_name: medical_genetics data_files: - split: test path: data/medical_genetics/test.jsonl - split: dev path: data/medical_genetics/dev.jsonl - config_name: miscellaneous data_files: - split: test path: data/miscellaneous/test.jsonl - split: dev path: data/miscellaneous/dev.jsonl - config_name: moral_disputes data_files: - split: test path: data/moral_disputes/test.jsonl - split: dev path: data/moral_disputes/dev.jsonl - config_name: moral_scenarios data_files: - split: test path: data/moral_scenarios/test.jsonl - split: dev path: data/moral_scenarios/dev.jsonl - config_name: nutrition data_files: - split: test path: data/nutrition/test.jsonl - split: dev path: data/nutrition/dev.jsonl - config_name: philosophy data_files: - split: test path: data/philosophy/test.jsonl - split: dev path: data/philosophy/dev.jsonl - config_name: prehistory data_files: - split: test path: data/prehistory/test.jsonl - split: dev path: data/prehistory/dev.jsonl - config_name: professional_accounting data_files: - split: test path: data/professional_accounting/test.jsonl - split: dev path: data/professional_accounting/dev.jsonl - config_name: professional_law data_files: - split: test path: data/professional_law/test.jsonl - split: dev path: data/professional_law/dev.jsonl - config_name: professional_medicine data_files: - split: test path: data/professional_medicine/test.jsonl - split: dev path: data/professional_medicine/dev.jsonl - config_name: professional_psychology data_files: - split: test path: data/professional_psychology/test.jsonl - split: dev path: data/professional_psychology/dev.jsonl - config_name: public_relations data_files: - split: test path: data/public_relations/test.jsonl - split: dev path: data/public_relations/dev.jsonl - config_name: security_studies data_files: - split: test path: data/security_studies/test.jsonl - split: dev path: data/security_studies/dev.jsonl - config_name: sociology data_files: - split: test path: data/sociology/test.jsonl - split: dev path: data/sociology/dev.jsonl - config_name: us_foreign_policy data_files: - split: test path: data/us_foreign_policy/test.jsonl - split: dev path: data/us_foreign_policy/dev.jsonl - config_name: virology data_files: - split: test path: data/virology/test.jsonl - split: dev path: data/virology/dev.jsonl - config_name: world_religions data_files: - split: test path: data/world_religions/test.jsonl - split: dev path: data/world_religions/dev.jsonl dataset_info: - config_name: abstract_algebra features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: anatomy features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: astronomy features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: business_ethics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: clinical_knowledge features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_biology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_chemistry features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_computer_science features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_mathematics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_medicine features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: college_physics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: computer_security features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: conceptual_physics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: econometrics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: electrical_engineering features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: elementary_mathematics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: formal_logic features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: global_facts features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_biology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_chemistry features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_computer_science features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_european_history features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_geography features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_government_and_politics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_macroeconomics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_mathematics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_microeconomics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_physics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_psychology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_statistics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_us_history features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: high_school_world_history features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: human_aging features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: human_sexuality features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: international_law features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: jurisprudence features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: logical_fallacies features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: machine_learning features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: management features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: marketing features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: medical_genetics features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: miscellaneous features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: moral_disputes features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: moral_scenarios features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: nutrition features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: philosophy features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: prehistory features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: professional_accounting features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: professional_law features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: professional_medicine features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: professional_psychology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: public_relations features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: security_studies features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: sociology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: us_foreign_policy features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: virology features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string - config_name: world_religions features: - name: instruction dtype: string - name: inputs struct: - name: text dtype: string - name: option_a dtype: string - name: option_b dtype: string - name: option_c dtype: string - name: option_d dtype: string - name: subject dtype: string - name: outputs dtype: string - name: domain dtype: string --- ## **ruMMLU** ### Task Description **Russian Massive Multitask Language Understanding (ruMMLU)** is a dataset designed to measure model professional knowledge acquired during pretraining in various fields . The task covers 57 subjects (subdomains) across different topics (domains): HUMANITIES; SOCIAL SCIENCE; SCIENCE, TECHNOLOGY, ENGINEERING, AND MATHEMATICS (STEM); OTHER. The dataset was created based on the English MMLU dataset proposed in the original paper and follows its methodology in the instruction formal. Each example contains a question from one of the categories with four possible answers, only one of which is correct. **Warning:** to avoid data leakage for ruMMLU, we created the NEW closed test set that follows the original MMLU design. Thus, **results on the MMLU and ruMMLU datasets cannot be directly compared with each other.** **Warning:** additional open data is the public test set of the original MMLU dataset. Do not use it in train purposes! **Keywords**: logic, world knowledge, factual, expert knowledge ### Dataset Description #### Data Fields - `instruction` is a string containing instructions for the task and information about the requirements for the model output format; - `inputs` is a dictionary that contains the following information: - `text` is the test question; - `option_a` is the option A; - `option_b` is the option B; - `option_c` is the option C; - `option_d` is the option D; - `subject` is the topic of the question (generalization of a group of subdomains by meaning); - `outputs` is the result: can be one of the following string variables: "A", "B", "C", "D"; - `domain` is question subdomain. #### Prompts For this task 10 prompts of varying difficulty were created. Example: ```json "Дан вопрос по теме {subject}: {text}. Варианты ответа:\nA {option_a}\nB {option_b}\nC {option_c}\nD {option_d}\nОпредели, какой вариант ответа правильный. Напиши только букву этого ответа: A, B, C, D. Ответ:" ``` #### Dataset Creation The open set is based on the [the original MMLU dataset](https://github.com/hendrycks/test) and translated to the Russian language using the following pipeline: 1) the public test was translated into Russian using automatic translation; 2) the translations were verified on the Yandex.Toloka platform; 3) the data that did not pass verification was manually validated and Russified. The current version of the open public set is not final, and the dataset set will be updated in the future. For the closed test set, the set was assembled manually according to the original format with domains as close as possible to the original set. The set is adapted for the Russian language and culture. The distribution of tasks across individual specific domains corresponds to the original set and is equal to an average of 150 examples. ### Evaluation #### Metrics The dataset is evaluated using Accuracy and, following the original methodology, is evaluated in the few-shot format with five shots. #### Human benchmark According to the original article, for English test human-level accuracy varies: "Unspecialized humans from Amazon Mechanical Turk obtain 34.5% accuracy on English test. Meanwhile, expert-level performance can be far higher. For example, real-world test-taker human accuracy at the 95th percentile is around 87% for US Medical Licensing Examinations, and these questions make up our “Professional Medicine” task. If we take the 95th percentile human test-taker accuracy for exams that build up our test, and if we make an educated guess when such information is unavailable, we then estimate that expert-level accuracy is approximately 89.8%.". Accuracy of the annotation on the test set is `84.4%`. ### Limitations The questions relate to human knowledge relevant on January 1, 2020, for the train part and on October 31, 2023, for the test part.

khmarastudio01041987/Govorek_LORA

khmarastudio01041987

--- license: apache-2.0 ---

javifer/raw-autoreg-fact-extraction

javifer

--- dataset_info: - config_name: longfact_Meta-Llama-3.1-8B-Instruct features: - name: dataset dtype: string - name: subset dtype: string - name: orig_dataset_idx dtype: int64 - name: orig_dataset_split dtype: string - name: query_id dtype: string - name: completion_idx dtype: int64 - name: conversation list: - name: content dtype: string - name: role dtype: string - name: completion dtype: string - name: reconstructed_completion dtype: string - name: facts list: - name: fact dtype: 'null' - name: id dtype: string - name: idx_in_text dtype: int64 - name: label dtype: 'null' - name: labeling_metadata dtype: 'null' - name: sentence dtype: string - name: span dtype: string splits: - name: test num_bytes: 598122 num_examples: 6 download_size: 123463 dataset_size: 598122 - config_name: longfact_gemma-2-9b-it features: - name: dataset dtype: string - name: subset dtype: string - name: orig_dataset_idx dtype: int64 - name: orig_dataset_split dtype: string - name: query_id dtype: string - name: completion_idx dtype: int64 - name: conversation list: - name: content dtype: string - name: role dtype: string - name: completion dtype: string - name: reconstructed_completion dtype: string - name: facts list: - name: fact dtype: 'null' - name: id dtype: string - name: idx_in_text dtype: int64 - name: label dtype: 'null' - name: labeling_metadata dtype: 'null' - name: sentence dtype: string - name: span dtype: string splits: - name: test num_bytes: 160861 num_examples: 6 download_size: 96089 dataset_size: 160861 configs: - config_name: longfact_Meta-Llama-3.1-8B-Instruct data_files: - split: test path: longfact_Meta-Llama-3.1-8B-Instruct/test-* - config_name: longfact_gemma-2-9b-it data_files: - split: test path: longfact_gemma-2-9b-it/test-* ---

fr3on/company

fr3on

--- dataset_info: features: - name: name dtype: string - name: website dtype: string - name: founded dtype: string - name: size dtype: string - name: locality dtype: string - name: region dtype: string - name: country dtype: string - name: industry dtype: string - name: linkedin_url dtype: string - name: description dtype: string - name: location dtype: string - name: has_linkedin dtype: bool - name: size_category dtype: int64 splits: - name: train num_bytes: 11886369371 num_examples: 24045262 download_size: 3978768319 dataset_size: 11886369371 configs: - config_name: default data_files: - split: train path: data/train-* license: apache-2.0 language: - en tags: - companies - business - logistics - supply-chain - dataset - tabular - data-analysis task_categories: - text-generation - text-classification - question-answering pretty_name: Company Dataset size_categories: - 10M<n<100M --- # Company Dataset ## Overview The **Company Dataset** is a large-scale collection containing detailed information on companies from around the globe. With approximately **24 million rows** of data, this dataset offers a rich resource for market research, business intelligence, and machine learning applications focused on company profiling and analysis. > **Note:** This is a public dataset, freely available for research and analysis purposes. ## Dataset Details - **Total Rows:** 24M - **Split:** Train (24M rows) - **Format:** Parquet - **Language:** Primarily English ### Data Fields The dataset includes the following attributes for each company: - **name:** The official name of the company. - **website:** The URL of the company’s website. - **founded:** The year (or date) the company was founded. - **size:** Information on the company size (e.g., employee count or range). - **locality:** The city or locality where the company is located. - **region:** The region or state of operation. - **country:** The country in which the company is based. - **industry:** The sector or industry in which the company operates. - **linkedin_url:** The URL to the company’s LinkedIn profile. - **description:** A brief description of the company. - **location:** Additional location details (if available). - **has_linkedin:** Boolean flag indicating whether the company has a LinkedIn profile. - **size_category:** A categorical representation of the company’s size (e.g., small, medium, large). ## Potential Use Cases - **Market Research:** Analyze trends and distributions of companies by region, size, and industry. - **Business Intelligence:** Enhance business databases with detailed company profiles. - **Machine Learning:** Train models for company classification, recommendation systems, or entity resolution tasks. - **Data Enrichment:** Integrate with other datasets to improve the quality of business or financial analyses. ## Data Source and Creation This dataset was curated and published by [fr3on](https://huggingface.co/fr3on). The data has been auto-converted to Parquet format to enable efficient storage and fast query performance. It aggregates company information from various public sources, making it a valuable resource for both academic research and industry applications. > **Note:** As with any large-scale aggregated dataset, please verify the data quality and completeness for your specific use case. ## Limitations and Considerations - **Data Quality:** Due to the massive scale, there may be inconsistencies or outdated information in some records. - **Coverage:** While extensive, the dataset might not include every company worldwide. - **Usage:** Intended primarily for research and analytical purposes. Ensure you comply with any relevant privacy or licensing requirements when using this data. ## License This dataset is released under the Apache-2.0 License. ## Citation If you use this dataset in your research, please consider citing it as follows: ```bibtex @dataset{fr3on_company, author = {fr3on}, title = {Company Dataset}, year = {2025}, url = {https://huggingface.co/datasets/fr3on/company} }

Troy-Codes/python

Troy-Codes

--- license: artistic-2.0 ---

aadityap/8k_forcing_buffer

aadityap

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 12749234.649681529 num_examples: 400 - name: test num_bytes: 37072 num_examples: 1 download_size: 3693870 dataset_size: 12786306.649681529 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

appvoid/no-prompt-oasst-mini

appvoid

--- license: apache-2.0 ---

aadityap/3k_forcing_022225_buffer

aadityap

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 8639371.681415929 num_examples: 400 - name: test num_bytes: 20663 num_examples: 1 download_size: 2388382 dataset_size: 8660034.681415929 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

akore/1xwm-orig-v1.1

akore

--- dataset_info: features: - name: input_ids sequence: sequence: sequence: uint32 - name: actions sequence: sequence: sequence: float32 splits: - name: train num_bytes: 2464511832 num_examples: 56619 - name: val num_bytes: 10533776 num_examples: 242 download_size: 1728000194 dataset_size: 2475045608 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---

aadityap/8k_forcing_022225_buffer

aadityap

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 12749234.649681529 num_examples: 400 - name: test num_bytes: 37072 num_examples: 1 download_size: 3694982 dataset_size: 12786306.649681529 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

1231czx/ppo220_math500

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: question dtype: string - name: gt_cot dtype: string - name: gt dtype: string - name: level dtype: int64 - name: solution dtype: string - name: answer dtype: string - name: code sequence: string - name: pred sequence: string - name: report sequence: 'null' - name: score sequence: bool splits: - name: train num_bytes: 2003384 num_examples: 500 download_size: 827564 dataset_size: 2003384 --- # Dataset Card for "ppo220_math500" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

embodied-ai/piper_shirt_hanging_a1

embodied-ai

--- license: apache-2.0 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:** [More Information Needed] - **Paper:** [More Information Needed] - **License:** apache-2.0 ## Dataset Structure [meta/info.json](meta/info.json): ```json { "codebase_version": "v2.0", "robot_type": "piper_ros", "total_episodes": 228, "total_frames": 147196, "total_tasks": 1, "total_videos": 912, "total_chunks": 1, "chunks_size": 1000, "fps": 30, "splits": { "train": "0:228" }, "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": { "action": { "dtype": "float32", "shape": [ 14 ], "names": [ "left_waist", "left_shoulder", "left_elbow", "left_forearm_roll", "left_wrist_angle", "left_wrist_rotate", "left_gripper", "right_waist", "right_shoulder", "right_elbow", "right_forearm_roll", "right_wrist_angle", "right_wrist_rotate", "right_gripper" ] }, "observation.state": { "dtype": "float32", "shape": [ 14 ], "names": [ "left_waist", "left_shoulder", "left_elbow", "left_forearm_roll", "left_wrist_angle", "left_wrist_rotate", "left_gripper", "right_waist", "right_shoulder", "right_elbow", "right_forearm_roll", "right_wrist_angle", "right_wrist_rotate", "right_gripper" ] }, "observation.images.cam_high": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_low": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_left_wrist": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "observation.images.cam_right_wrist": { "dtype": "video", "shape": [ 480, 640, 3 ], "names": [ "height", "width", "channels" ], "info": { "video.fps": 30.0, "video.height": 480, "video.width": 640, "video.channels": 3, "video.codec": "h264", "video.pix_fmt": "yuv420p", "video.is_depth_map": false, "has_audio": false } }, "timestamp": { "dtype": "float32", "shape": [ 1 ], "names": null }, "frame_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "episode_index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "index": { "dtype": "int64", "shape": [ 1 ], "names": null }, "task_index": { "dtype": "int64", "shape": [ 1 ], "names": null } } } ``` ## Citation **BibTeX:** ```bibtex [More Information Needed] ```

1231czx/sftep1_math500

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: question dtype: string - name: gt_cot dtype: string - name: gt dtype: string - name: level dtype: int64 - name: solution dtype: string - name: answer dtype: string - name: code sequence: string - name: pred sequence: string - name: report sequence: 'null' - name: score sequence: bool splits: - name: train num_bytes: 1953849 num_examples: 500 download_size: 828992 dataset_size: 1953849 --- # Dataset Card for "sftep1_math500" [More Information needed](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

tttx/8k_forcing_022225_buffer

tttx

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 12749234.649681529 num_examples: 400 - name: test num_bytes: 37072 num_examples: 1 download_size: 3698529 dataset_size: 12786306.649681529 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

tttx/3k_forcing_022225_buffer

tttx

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 8639371.681415929 num_examples: 400 - name: test num_bytes: 20663 num_examples: 1 download_size: 2389835 dataset_size: 8660034.681415929 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

lihaoxin2020/SciLitIns-labelled

lihaoxin2020

--- dataset_info: features: - name: conversations list: - name: from dtype: string - name: value dtype: string - name: category dtype: string splits: - name: train num_bytes: 172718663 num_examples: 109952 download_size: 84112723 dataset_size: 172718663 configs: - config_name: default data_files: - split: train path: data/train-* ---

TimeTestUniverse/ag_news_annotated

TimeTestUniverse

--- dataset_info: features: [] splits: - name: train num_bytes: 0 num_examples: 0 download_size: 324 dataset_size: 0 configs: - config_name: default data_files: - split: train path: data/train-* ---

rirv938/best_of_deployed_weight_7_seed_20_samples_instruct

rirv938

--- dataset_info: features: - name: text dtype: string splits: - name: train num_bytes: 5484643 num_examples: 1400 download_size: 3162725 dataset_size: 5484643 configs: - config_name: default data_files: - split: train path: data/train-* ---

bezir/MATH-500-multilingual

bezir

--- configs: - config_name: French data_files: - split: test path: french.jsonl - config_name: Turkish data_files: - split: test path: turkish.jsonl - config_name: Italian data_files: - split: test path: italian.jsonl - config_name: English data_files: - split: test path: english.jsonl - config_name: Spanish data_files: - split: test path: spanish.jsonl language: - tr - en - fr - it - es tags: - math - HuggingfaceH4 - OpenAI - mathematics pretty_name: MATH 500 Multilingual size_categories: - 1K<n<10K --- <div align="center" style="line-height: 1;"> <a href="https://www.huggingface.co/bezir" target="_blank" style="margin: 2px;"> <img alt="Follow" src="https://huggingface.co/datasets/bezir/MATH-500-multilingual/resolve/main/follow.svg" style="display: inline-block; vertical-align: middle;"/> </a> </div> # MATH-500 Multilingual Problem Set 🌍➗ A multilingual subset from OpenAI's MATH benchmark. Perfect for testing math skills across languages, this dataset includes same problems in **English, French, Italian, Turkish and Spanish**. --- ### 🌐 Available Languages - English 🇬🇧 - French 🇫🇷 - Italian 🇮🇹 - Turkish 🇹🇷 - Spanish 🇪🇸 --- ### 📂 Source & Attribution - **Original Dataset**: Sourced from [HuggingFaceH4/MATH-500](https://huggingface.co/datasets/HuggingFaceH4/MATH-500). --- ### 🚀 Quick Start Load the dataset in your favorite language: ```python from datasets import load_dataset dataset = load_dataset("bezir/MATH-500-multilingual", "French")

olivernan/mArenaHard-examples

olivernan

--- dataset_info: - config_name: arb_Arab features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 15804705 num_examples: 500 download_size: 5391107 dataset_size: 15804705 - config_name: ces_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 12240063 num_examples: 500 download_size: 5374851 dataset_size: 12240063 - config_name: deu_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13775710 num_examples: 500 download_size: 5820194 dataset_size: 13775710 - config_name: ell_Grek features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 17508379 num_examples: 500 download_size: 6117037 dataset_size: 17508379 - config_name: eng_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 14150199 num_examples: 500 download_size: 6097492 dataset_size: 14150199 - config_name: fra_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 14079510 num_examples: 500 download_size: 5812496 dataset_size: 14079510 - config_name: heb_Hebr features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 15066905 num_examples: 500 download_size: 5279088 dataset_size: 15066905 - config_name: hin_Deva features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 19335156 num_examples: 500 download_size: 5966047 dataset_size: 19335156 - config_name: ind_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13249535 num_examples: 500 download_size: 5144161 dataset_size: 13249535 - config_name: ita_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13367385 num_examples: 500 download_size: 5733572 dataset_size: 13367385 - config_name: jpn_Jpan features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 14536332 num_examples: 500 download_size: 5177221 dataset_size: 14536332 - config_name: kor_Hang features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 14080389 num_examples: 500 download_size: 5114957 dataset_size: 14080389 - config_name: nld_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13198218 num_examples: 500 download_size: 5490209 dataset_size: 13198218 - config_name: pes_Arab features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 16164070 num_examples: 500 download_size: 5453240 dataset_size: 16164070 - config_name: pol_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 12332214 num_examples: 500 download_size: 5427137 dataset_size: 12332214 - config_name: por_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13898766 num_examples: 500 download_size: 5755129 dataset_size: 13898766 - config_name: ron_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13056880 num_examples: 500 download_size: 5528629 dataset_size: 13056880 - config_name: rus_Cyrl features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 18711190 num_examples: 500 download_size: 7016465 dataset_size: 18711190 - config_name: spa_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13667398 num_examples: 500 download_size: 5849128 dataset_size: 13667398 - config_name: tur_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 13688308 num_examples: 500 download_size: 5076397 dataset_size: 13688308 - config_name: ukr_Cyrl features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 17313883 num_examples: 500 download_size: 6419823 dataset_size: 17313883 - config_name: vie_Latn features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 14640774 num_examples: 500 download_size: 5361596 dataset_size: 14640774 - config_name: zho_Hans features: - name: prompt dtype: string - name: c4ai-aya-ex-8b dtype: string - name: Gemini-Flash-1.5-8B dtype: string - name: Llama-3.2-11B-Vision-Instruct dtype: string - name: Qwen2-VL-7B-Instruct dtype: string - name: Pixtral-12B dtype: string - name: Qwen2.5-VL-7B-Instruct dtype: string - name: Pangea-7B dtype: string - name: Molmo-7B-D dtype: string - name: Llama-3.2-90B-Vision-Instruct dtype: string - name: paligemma2-10b-mix-448 dtype: string splits: - name: train num_bytes: 11453505 num_examples: 500 download_size: 5318682 dataset_size: 11453505 configs: - config_name: arb_Arab data_files: - split: train path: arb_Arab/train-* - config_name: ces_Latn data_files: - split: train path: ces_Latn/train-* - config_name: deu_Latn data_files: - split: train path: deu_Latn/train-* - config_name: ell_Grek data_files: - split: train path: ell_Grek/train-* - config_name: eng_Latn data_files: - split: train path: eng_Latn/train-* - config_name: fra_Latn data_files: - split: train path: fra_Latn/train-* - config_name: heb_Hebr data_files: - split: train path: heb_Hebr/train-* - config_name: hin_Deva data_files: - split: train path: hin_Deva/train-* - config_name: ind_Latn data_files: - split: train path: ind_Latn/train-* - config_name: ita_Latn data_files: - split: train path: ita_Latn/train-* - config_name: jpn_Jpan data_files: - split: train path: jpn_Jpan/train-* - config_name: kor_Hang data_files: - split: train path: kor_Hang/train-* - config_name: nld_Latn data_files: - split: train path: nld_Latn/train-* - config_name: pes_Arab data_files: - split: train path: pes_Arab/train-* - config_name: pol_Latn data_files: - split: train path: pol_Latn/train-* - config_name: por_Latn data_files: - split: train path: por_Latn/train-* - config_name: ron_Latn data_files: - split: train path: ron_Latn/train-* - config_name: rus_Cyrl data_files: - split: train path: rus_Cyrl/train-* - config_name: spa_Latn data_files: - split: train path: spa_Latn/train-* - config_name: tur_Latn data_files: - split: train path: tur_Latn/train-* - config_name: ukr_Cyrl data_files: - split: train path: ukr_Cyrl/train-* - config_name: vie_Latn data_files: - split: train path: vie_Latn/train-* - config_name: zho_Hans data_files: - split: train path: zho_Hans/train-* ---

charmaineregina/illustration-dataset

charmaineregina

--- dataset_info: features: - name: image dtype: string - name: text dtype: string splits: - name: train num_bytes: 71450 num_examples: 900 download_size: 8519 dataset_size: 71450 configs: - config_name: default data_files: - split: train path: data/train-* ---

djelia/multilingual-asr

djelia

--- dataset_info: - config_name: covost2-transcription features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: duration dtype: float64 - name: language dtype: string - name: task_type dtype: string - name: source_dataset dtype: string splits: - name: train num_bytes: 3296500489.19 num_examples: 86062 download_size: 3235624110 dataset_size: 3296500489.19 - config_name: hausa features: - name: audio dtype: audio: sampling_rate: 48000 - name: text dtype: string - name: duration dtype: float64 - name: language dtype: string - name: source_dataset dtype: string splits: - name: train num_bytes: 49469774.0 num_examples: 1925 - name: test num_bytes: 18817320.0 num_examples: 661 download_size: 67690779 dataset_size: 68287094.0 - config_name: swahili features: - name: audio dtype: audio: sampling_rate: 48000 - name: text dtype: string - name: duration dtype: float64 - name: language dtype: string - name: source_dataset dtype: string splits: - name: train num_bytes: 1516290519.0 num_examples: 46494 - name: test num_bytes: 413707420.0 num_examples: 12253 download_size: 1900116607 dataset_size: 1929997939.0 - config_name: translation features: - name: audio dtype: audio: sampling_rate: 16000 - name: text dtype: string - name: duration dtype: float64 - name: language dtype: string - name: task_type dtype: string - name: source_dataset dtype: string splits: - name: train num_bytes: 3295510887.19 num_examples: 86062 download_size: 3234263049 dataset_size: 3295510887.19 configs: - config_name: covost2-transcription data_files: - split: train path: covost2-transcription/train-* - config_name: hausa data_files: - split: train path: hausa/train-* - split: test path: hausa/test-* - config_name: swahili data_files: - split: train path: swahili/train-* - split: test path: swahili/test-* - config_name: translation data_files: - split: train path: translation/train-* ---

akore/1xwm-all-v1.1

akore

--- dataset_info: features: - name: input_ids sequence: sequence: sequence: uint32 - name: actions sequence: sequence: sequence: float32 splits: - name: train num_bytes: 4865037504 num_examples: 111768 - name: val num_bytes: 10533776 num_examples: 242 download_size: 2867090538 dataset_size: 4875571280 configs: - config_name: default data_files: - split: train path: data/train-* - split: val path: data/val-* ---

divij30/legal-qa-augmented

divij30

--- dataset_info: features: - name: question dtype: string - name: answer dtype: string - name: source dtype: string splits: - name: train num_bytes: 7876362 num_examples: 6742 download_size: 4156056 dataset_size: 7876362 configs: - config_name: default data_files: - split: train path: data/train-* ---

plesniar/Sand44_300_dataset

plesniar

--- dataset_info: features: - name: audio dtype: audio - name: text dtype: string - name: speaker_id dtype: int64 - name: line_id dtype: int64 splits: - name: train num_bytes: 109522240.0 num_examples: 100 download_size: 109429309 dataset_size: 109522240.0 configs: - config_name: default data_files: - split: train path: data/train-* ---

obiwan96/obiwan96open_web_math_qav3

obiwan96

--- dataset_info: features: - name: query dtype: string - name: completion dtype: string splits: - name: train num_bytes: 586110.9459459459 num_examples: 35 - name: test num_bytes: 33492.05405405405 num_examples: 2 download_size: 126957 dataset_size: 619603.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

Ualajac/chemistry-qa-bot

Ualajac

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

leandroconsolaro/minhavoz99

leandroconsolaro

--- license: openrail ---

md-nishat-008/Bangla-TextBook

md-nishat-008

--- license: mit --- <!-- # Bangla-TextBook Corpus --> <h1 style="color:#2A7AE2; font-family: 'Helvetica Neue', Helvetica, Arial, sans-serif;"> Bangla-TextBook Corpus </h1> <p align="center"> <img src="wc.png" alt="Bangla Word Cloud" style="width:60%; border: 2px solid #2A7AE2; border-radius: 8px;"> </p> ## Overview The **Bangla-TextBook** corpus is a high-quality, **open-source** educational dataset curated from textbooks published by the [National Curriculum and Textbook Board](https://nctb.gov.bd/) of Bangladesh. This corpus fills a critical gap in Bangla educational content, offering a curated alternative to corpora primarily sourced from OSCAR and [Common Crawl](https://commoncrawl.org/). > "Recent findings by <strong>Gunasekar et al.</strong> demonstrate that LLMs achieve superior performance through high-quality training data, even with reduced volume." ## Dataset Statistics | **Metric** | **Value** | | ---------------------- | -------------:| | **Total Characters** | 63,560,507 | | **Total Words** | 10,307,926 | | **Total Sentences** | 920,722 | | **Total Paragraphs** | 466,800 | ## Corpus Details Previous Bangla LLMs rely predominantly on corpora sourced from OSCAR [^1] and Common Crawl [^2], despite quality control challenges. While alternative Bangla corpora have emerged [^3][^4], the absence of curated educational content remains a critical gap. To bridge this gap, we present the **Bangla-TextBook** corpus—constructed exclusively from high-quality open-source educational materials published by the [National Curriculum and Textbook Board](https://nctb.gov.bd/). The corpus aggregates texts from **163 textbooks for Grades 6–12**, totaling **9,897,623 tokens** and **697,903 sentences**. ## References 1. Ortiz Suárez, et al. (2020). *Monolingual corpora for low-resource languages: The OSCAR corpus*. [Link](https://aclanthology.org/2020.acl-srw.40/) 2. Bhattacharjee, et al. (2022). *BanglaBERT and BongLlama: Large Language Models for Bangla*. [Link](https://commoncrawl.org/) 3. Bhattacharya, et al. (2023). *Vacaspati: [Details Pending]*. 4. Zehady, et al. (2024). *BongLLama: [Details Pending]*. 5. Gunasekar, et al. (2023). *Textbooks: [Details Pending]*. ## Acknowledgments We deeply appreciate the contributions of the researchers and institutions that have paved the way for high-quality language modeling. The **Bangla-TextBook** corpus is a testament to the impact of curated, domain-specific datasets on advancing language technologies. --- *For more details, please refer to the associated research publications and the official dataset repository.*

juliadollis/FINET_10mil_qwen25_7bI_promptoriginal

juliadollis

--- dataset_info: features: - name: Description dtype: string - name: Patient dtype: string - name: Doctor dtype: string - name: Translated_Description dtype: string - name: Translated_Patient dtype: string - name: Translated_Doctor dtype: string - name: Inferencia dtype: string splits: - name: train num_bytes: 261521 num_examples: 100 download_size: 133133 dataset_size: 261521 configs: - config_name: default data_files: - split: train path: data/train-* ---

juliadollis/FINET_30mil_qwen25_7bI_promptoriginal

juliadollis

--- dataset_info: features: - name: Description dtype: string - name: Patient dtype: string - name: Doctor dtype: string - name: Translated_Description dtype: string - name: Translated_Patient dtype: string - name: Translated_Doctor dtype: string - name: Inferencia dtype: string splits: - name: train num_bytes: 261326 num_examples: 100 download_size: 132918 dataset_size: 261326 configs: - config_name: default data_files: - split: train path: data/train-* ---

juliadollis/FINET_30mil_llama32_3bI_promptoriginal

juliadollis

--- dataset_info: features: - name: Description dtype: string - name: Patient dtype: string - name: Doctor dtype: string - name: Translated_Description dtype: string - name: Translated_Patient dtype: string - name: Translated_Doctor dtype: string - name: Inferencia dtype: string splits: - name: train num_bytes: 282651 num_examples: 100 download_size: 140824 dataset_size: 282651 configs: - config_name: default data_files: - split: train path: data/train-* ---

quickmt/quickmt-train.ko-en

quickmt

--- dataset_info: features: - name: ko dtype: string - name: en dtype: string - name: sco dtype: float64 splits: - name: train num_bytes: 5419243382 num_examples: 26294677 download_size: 3717844777 dataset_size: 5419243382 configs: - config_name: default data_files: - split: train path: data/train-* --- # `quickmt` ko-en Training Corpus Contains the following datasets downloaded with `mtdata` after deduplication and [basic filtering](https://github.com/quickmt/quickmt/blob/main/quickmt/scripts/clean.py) with `quickmt`: * OPUS-ccaligned-v1-eng-kor * OPUS-ccmatrix-v1-eng-kor * OPUS-elrc_3070_wikipedia_health-v1-eng-kor * OPUS-elrc_wikipedia_health-v1-eng-kor * OPUS-elrc_2922-v1-eng-kor * OPUS-gnome-v1-eng-kor * OPUS-globalvoices-v2017q3-eng-kor * OPUS-globalvoices-v2018q4-eng-kor * OPUS-kde4-v2-eng-kor * OPUS-linguatools_wikititles-v2014-eng-kor * OPUS-mdn_web_docs-v20230925-eng-kor * OPUS-multiccaligned-v1-eng-kor * OPUS-nllb-v1-eng-kor * OPUS-neulab_tedtalks-v1-eng-kor * OPUS-opensubtitles-v2016-eng-kor * OPUS-opensubtitles-v2018-eng-kor * OPUS-php-v1-eng-kor * OPUS-paracrawl-v8-eng-kor * OPUS-paracrawl-v9-eng-kor * OPUS-qed-v2.0a-eng-kor * OPUS-ted2020-v1-eng-kor * OPUS-tanzil-v1-eng-kor * OPUS-tatoeba-v2-eng-kor * OPUS-tatoeba-v20190709-eng-kor * OPUS-tatoeba-v20200531-eng-kor * OPUS-tatoeba-v20201109-eng-kor * OPUS-tatoeba-v20210310-eng-kor * OPUS-tatoeba-v20210722-eng-kor * OPUS-tatoeba-v20220303-eng-kor * OPUS-tatoeba-v20230412-eng-kor * OPUS-ubuntu-v14.10-eng-kor * OPUS-wikimatrix-v1-eng-kor * OPUS-xlent-v1.2-eng-kor * OPUS-bible_uedin-v1-eng-kor * OPUS-tldr_pages-v20230829-eng-kor * OPUS-wikimedia-v20210402-eng-kor * OPUS-wikimedia-v20230407-eng-kor * Statmt-ccaligned-1-eng-kor_KR * ParaCrawl-paracrawl-1_bonus-eng-kor * Facebook-wikimatrix-1-eng-kor * Neulab-tedtalks_train-1-eng-kor * Neulab-tedtalks_dev-1-eng-kor * ELRC-wikipedia_health-1-eng-kor * ELRC-hrw_dataset_v1-1-eng-kor * LinguaTools-wikititles-2014-eng-kor

Asap7772/obiwan96open_web_math_qav3_none

Asap7772

--- dataset_info: features: - name: query dtype: string - name: completion dtype: string splits: - name: train num_bytes: 544717155 num_examples: 143360 - name: test num_bytes: 28735779 num_examples: 7546 download_size: 227099099 dataset_size: 573452934 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

JoyeeChen/20k_real_animals_convos_2_feb22

JoyeeChen

--- dataset_info: features: - name: conversation dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 21984974.4 num_examples: 16000 - name: test num_bytes: 5496243.6 num_examples: 4000 download_size: 15730233 dataset_size: 27481218.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

CompassioninMachineLearning/20k_real_animals_convos_1_feb22

CompassioninMachineLearning

--- dataset_info: features: - name: conversation dtype: string - name: instruction dtype: string - name: output dtype: string splits: - name: train num_bytes: 21984974.4 num_examples: 16000 - name: test num_bytes: 5496243.6 num_examples: 4000 download_size: 15730233 dataset_size: 27481218.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

1231czx/qwen25_star_baseline_gen1

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: prompt dtype: string - name: answers sequence: string - name: gt dtype: string - name: true_reward dtype: bool splits: - name: train num_bytes: 930568522 num_examples: 48640 download_size: 344944611 dataset_size: 930568522 configs: - config_name: default data_files: - split: train path: data/train-* ---

juliadollis/FINET_10mil_llama32_3bI_promptoriginal

juliadollis

--- dataset_info: features: - name: Description dtype: string - name: Patient dtype: string - name: Doctor dtype: string - name: Translated_Description dtype: string - name: Translated_Patient dtype: string - name: Translated_Doctor dtype: string - name: Inferencia dtype: string splits: - name: train num_bytes: 267233 num_examples: 100 download_size: 134984 dataset_size: 267233 configs: - config_name: default data_files: - split: train path: data/train-* ---

1231czx/qwen25_star_baseline_gen2

1231czx

--- dataset_info: features: - name: idx dtype: int64 - name: prompt dtype: string - name: answers sequence: string - name: gt dtype: string - name: true_reward dtype: bool splits: - name: train num_bytes: 751911255 num_examples: 39375 download_size: 278381903 dataset_size: 751911255 configs: - config_name: default data_files: - split: train path: data/train-* ---

tttx/3k_force_step1_mask15_022225

tttx

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: difficulty dtype: int64 - name: problem_uid dtype: string - name: step dtype: int64 splits: - name: train num_bytes: 8625360.11994003 num_examples: 400 - name: test num_bytes: 21771 num_examples: 1 download_size: 2396183 dataset_size: 8647131.11994003 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

laolaorkk/filtered-proof-Omni-Numina-v3

laolaorkk

--- dataset_info: features: - name: solution dtype: string - name: answer dtype: string - name: question dtype: string - name: math_type dtype: string - name: source_type dtype: string - name: metadata dtype: string splits: - name: train num_bytes: 60702447 num_examples: 47984 download_size: 28652268 dataset_size: 60702447 configs: - config_name: default data_files: - split: train path: data/train-* ---

Rokii3/ud-annotated-questions

Rokii3

--- tags: - rlfh - argilla - human-feedback --- # Dataset Card for ud-annotated-questions This dataset has been created with [Argilla](https://github.com/argilla-io/argilla). As shown in the sections below, this dataset can be loaded into your Argilla server as explained in [Load with Argilla](#load-with-argilla), or used directly with the `datasets` library in [Load with `datasets`](#load-with-datasets). ## Using this dataset with Argilla To load with Argilla, you'll just need to install Argilla as `pip install argilla --upgrade` and then use the following code: ```python import argilla as rg ds = rg.Dataset.from_hub("Rokii3/ud-annotated-questions", settings="auto") ``` This will load the settings and records from the dataset repository and push them to you Argilla server for exploration and annotation. ## Using this dataset with `datasets` To load the records of this dataset with `datasets`, you'll just need to install `datasets` as `pip install datasets --upgrade` and then use the following code: ```python from datasets import load_dataset ds = load_dataset("Rokii3/ud-annotated-questions") ``` This will only load the records of the dataset, but not the Argilla settings. ## Dataset Structure This dataset repo contains: * Dataset records in a format compatible with HuggingFace `datasets`. These records will be loaded automatically when using `rg.Dataset.from_hub` and can be loaded independently using the `datasets` library via `load_dataset`. * The [annotation guidelines](#annotation-guidelines) that have been used for building and curating the dataset, if they've been defined in Argilla. * A dataset configuration folder conforming to the Argilla dataset format in `.argilla`. The dataset is created in Argilla with: **fields**, **questions**, **suggestions**, **metadata**, **vectors**, and **guidelines**. ### Fields The **fields** are the features or text of a dataset's records. For example, the 'text' column of a text classification dataset of the 'prompt' column of an instruction following dataset. | Field Name | Title | Type | Required | | ---------- | ----- | ---- | -------- | | text | text | text | True | ### Questions The **questions** are the questions that will be asked to the annotators. They can be of different types, such as rating, text, label_selection, multi_label_selection, or ranking. | Question Name | Title | Type | Required | Description | Values/Labels | | ------------- | ----- | ---- | -------- | ----------- | ------------- | | verified | Verification Status | label_selection | True | Has this record been verified? | ['yes', 'no'] | <!-- check length of metadata properties --> ### Data Splits The dataset contains a single split, which is `train`. ## 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 guidelines Universal Dependencies question sentence #### 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 [More Information Needed]

sakshee05/CCP-censorship-dataset

sakshee05

--- license: mit --- # **Dataset for Fine-Tuning DeepSeek** ## **Overview** This dataset was created as part of an effort to fine-tune DeepSeek to analyze and mitigate censorship biases in AI models. The dataset consists of questions generated using Perplexity AI and responses generated using ChatGPT. The focus is on historical, political, and cultural topics where AI-generated content may exhibit bias or inconsistencies due to censorship filters. ## **Purpose** The goal of this dataset is to improve transparency in AI-generated responses by fine-tuning DeepSeek to provide more balanced and comprehensive answers. By curating this dataset, I aim to evaluate how censorship impacts AI outputs and explore ways to enhance model robustness against selective filtering. ## **Data Generation Process** - **Question Generation:** Perplexity AI was used to generate a diverse set of questions across various sensitive and non-sensitive topics. - **Answer Generation:** ChatGPT was used to generate responses to these questions. No manual edits were made to the responses to ensure consistency with the AI’s output. ## **Disclaimer** This dataset was generated using Perplexity AI for question generation and ChatGPT for responses. The content is AI-generated and may contain inaccuracies, biases, or outdated information. It should not be considered an authoritative source, and users are encouraged to independently verify any information before relying on it. The curator of this dataset is not a subject matter expert and does not assume responsibility for the accuracy or implications of the content.

zhenghaoxu/helpsteer2-preference_preference

zhenghaoxu

--- dataset_info: features: - name: chosen list: - name: content dtype: string - name: role dtype: string - name: rejected list: - name: content dtype: string - name: role dtype: string - name: strength dtype: int64 splits: - name: train num_bytes: 30477934 num_examples: 6766 - name: validation num_bytes: 1569485 num_examples: 352 download_size: 15617820 dataset_size: 32047419 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

zhenghaoxu/helpsteer2-preference_comparison

zhenghaoxu

--- dataset_info: features: - name: prompt dtype: string - name: response_1 dtype: string - name: response_2 dtype: string - name: strength dtype: int64 - name: label dtype: float64 splits: - name: train num_bytes: 64409732 num_examples: 17354 - name: validation num_bytes: 3297172 num_examples: 896 download_size: 29515858 dataset_size: 67706904 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

zhenghaoxu/helpsteer2-preference_generative

zhenghaoxu

--- dataset_info: features: - name: context dtype: string - name: context_messages list: - name: content dtype: string - name: role dtype: string - name: label dtype: string splits: - name: train num_bytes: 87707002 num_examples: 17354 - name: validation num_bytes: 4482434 num_examples: 896 download_size: 23791960 dataset_size: 92189436 configs: - config_name: default data_files: - split: train path: data/train-* - split: validation path: data/validation-* ---

alidi/bearing-run2failure-unsw

alidi

--- dataset_info: features: - name: signal sequence: float64 - name: signal_length dtype: int64 - name: sampling_frequency dtype: float64 - name: speed dtype: float64 - name: radial_load dtype: float64 - name: defect_size dtype: float64 - name: defect_type dtype: string - name: test_number dtype: int64 splits: - name: test1 num_bytes: 393220800 num_examples: 80 - name: test3 num_bytes: 388305540 num_examples: 79 download_size: 548959288 dataset_size: 781526340 configs: - config_name: default data_files: - split: test1 path: data/test1-* - split: test3 path: data/test3-* language: - en tags: - bearing - vibration - remaining-useful-life pretty_name: Bearing run-to-failure dataset of UNSW - test 1 & 3 - horizontal acceleration --- This dataset is a subset of the bearing run-to-failure dataset of UNSW : - Horizontal acceleration (accH) measurements - Test 1 and Test 3 from the original dataset - Sampling frequency: 51200 Hz - Each sample contains signal data, signal length, sampling frequency, speed (6.0 Hz), radial load (10.5 kN), defect size (1.0 and 0.5 mm), and defect type (BPFO) ## Implementation This dataset is used as the validation dataset in this RUL prediction project: https://github.com/alidi24/bearing-rul-prediction.git ## Original Dataset - **Source**: 10.17632/h4df4mgrfb.3 ## License This dataset is shared under the CC BY 4.0 license, the same as the original dataset.

BCCard/BCAI-Finance-Kor

BCCard

--- license: apache-2.0 ---

introvoyz041/inbix

introvoyz041

--- license: mit ---

JEFFERSONMUSIC/MJAllEra1979-2009

JEFFERSONMUSIC

--- license: apache-2.0 ---

Sulav/dt-finetune-convos-cust-dthru-combined

Sulav

--- dataset_info: features: - name: messages list: - name: content dtype: string - name: role dtype: string - name: token_count dtype: int64 splits: - name: train num_bytes: 117563503.51065588 num_examples: 5750 - name: test num_bytes: 6195085.489344127 num_examples: 303 download_size: 25819998 dataset_size: 123758589.0 configs: - config_name: default data_files: - split: train path: data/train-* - split: test path: data/test-* ---

quickmt/quickmt-train.ar-en

quickmt

--- dataset_info: features: - name: ar dtype: string - name: en dtype: string - name: sco dtype: float64 splits: - name: train num_bytes: 37475572129 num_examples: 115355613 download_size: 22348241927 dataset_size: 37475572129 configs: - config_name: default data_files: - split: train path: data/train-* ---

kaamd/vvj

kaamd

--- dataset_info: features: - name: english dtype: string - name: fula dtype: string - name: dialect dtype: string - name: source dtype: string - name: explanation dtype: string - name: synth_direction dtype: string - name: french dtype: string splits: - name: train num_bytes: 49275110 num_examples: 56194 download_size: 29385752 dataset_size: 49275110 configs: - config_name: default data_files: - split: train path: data/train-* ---

Abdelilahe112/Hhh

Abdelilahe112

--- license: openrail --- async function askQuestion() { const question = document.getElementById("user-question").value; const answerElement = document.getElementById("ai-answer"); if (question.trim() === "") { answerElement.innerText = "الرجاء إدخال سؤال."; return; } try { const response = await axios.post( "https://api-inference.huggingface.co/models/facebook/blenderbot-3B", { inputs: question }, { headers: { "Authorization": `Bearer YOUR_HUGGING_FACE_API_KEY`, }, } ); const answer = response.data.generated_text; answerElement.innerText = answer; } catch (error) { console.error(error); answerElement.innerText = "حدث خطأ في الاتصال بالخادم."; } }

zarahall/prm_gender_data

zarahall

--- dataset_info: features: - name: example_id dtype: int64 - name: completion_idx dtype: int64 - name: problem dtype: string - name: step_number dtype: int64 - name: step_content dtype: string - name: biased dtype: int64 - name: leads_to_correct dtype: int64 - name: explanation dtype: string splits: - name: train num_bytes: 5256697 num_examples: 7387 download_size: 758774 dataset_size: 5256697 configs: - config_name: default data_files: - split: train path: data/train-* ---