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Adding the HAREM dataset, a Portuguese language dataset for NER tasks
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Add wiki lingua dataset
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Hello @lhoestq ,
I am opening a fresh pull request as advised in my original PR https://github.com/huggingface/datasets/pull/1308
Thanks
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ADD: Wino_bias dataset
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Updated PR to counter messed up history of previous one (https://github.com/huggingface/datasets/pull/1235) due to rebase.
Removed manual downloading of dataset.
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add Indonesian newspapers (id_newspapers_2018)
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The dataset contains around 500K articles (136M of words) from 7 Indonesian newspapers. The size of uncompressed 500K json files (newspapers-json.tgz) is around 2.2GB.
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adding snow_simplified_japanese_corpus
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Adding simplified Japanese corpus "SNOW T15" and "SNOW T23".
They contain original Japanese, simplified Japanese, and original English (the original text is gotten from en-ja translation corpus). Hence, it can be used not only for Japanese simplification but also for en-ja translation.
- http://www.jnlp.org/SNOW/T15
- http://www.jnlp.org/SNOW/T23
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Add Turkish News Category Dataset (270K).Updates were made for review…
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This PR adds the **Turkish News Categories Dataset (270K)** dataset which is a text classification dataset by me and @yavuzKomecoglu. Turkish news dataset consisting of **273601 news in 17 categories**, compiled from printed media and news websites between 2010 and 2017 by the [Interpress](https://www.interpress.com/) media monitoring company.
**Note**: Resubmitted as a clean version of the previous Pull Request(#1419). @SBrandeis @lhoestq
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Add clean menyo20k data
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New Clean PR for menyo20k_mt
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196k Reddit Jokes dataset
Dataset link- https://raw.githubusercontent.com/taivop/joke-dataset/master/reddit_jokes.json
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Adding enriched_web_nlg features + handling xml bugs
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This PR adds features of the enriched_web_nlg dataset that were not present yet (most notably sorted rdf triplet sets), and deals with some xml issues that led to returning no data in cases where surgery could be performed to salvage it.
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Added conv ai 2 (Again)
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The original PR -> https://github.com/huggingface/datasets/pull/1383
Reason for creating again -
The reason I had to create the PR again was due to the master rebasing issue. After rebasing the changes, all the previous commits got added to the branch.
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Adding NewsQA dataset
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Since the dataset has legal restrictions to circulate the original data. It has to be manually downloaded by the user and loaded to the library.
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add Bengali Hate Speech dataset
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Add Google Conceptual Captions Dataset
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Add id_nergrit_corpus
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Nergrit Corpus is a dataset collection of Indonesian Named Entity Recognition, Statement Extraction, and Sentiment Analysis.
Recently my PR for id_nergrit_ner has been accepted and merged to the main branch. The id_nergrit_ner has only one dataset (NER), and this new PR renamed the dataset from id_nergrit_ner to id_nergrit_corpus and added 2 other remaining datasets (Statement Extraction, and Sentiment Analysis.)
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add hrenwac_para
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Add CC100 Dataset
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Closes #773
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MDExOlB1bGxSZXF1ZXN0NTM1OTA1OTQy
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Add HEAD-QA: A Healthcare Dataset for Complex Reasoning
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HEAD-QA is a multi-choice HEAlthcare Dataset, the questions come from exams to access a specialized position in the
Spanish healthcare system.
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Add kinnews_kirnews
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Add kinnews and kirnews
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MDExOlB1bGxSZXF1ZXN0NTM1ODkyNTM5
| 1,453 |
Adding ethos dataset clean
|
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I addressed the comments on the PR1318
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| 761,104,924 |
MDU6SXNzdWU3NjExMDQ5MjQ=
| 1,452 |
SNLI dataset contains labels with value -1
|
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NONE
| null | null | null |
```
import datasets
nli_data = datasets.load_dataset("snli")
train_data = nli_data['train']
train_labels = train_data['label']
label_set = set(train_labels)
print(label_set)
```
**Output:**
`{0, 1, 2, -1}`
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Add European Center for Disease Control and Preventions's (ECDC) Translation Memory dataset
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ECDC-TM homepage: https://ec.europa.eu/jrc/en/language-technologies/ecdc-translation-memory
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| 1,450 |
Fix version in bible_para
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add W&I + LOCNESS dataset (BEA-2019 workshop shared task on GEC) [PROPER]
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- **Name:** W&I + LOCNESS dataset (from the BEA-2019 workshop shared task on GEC)
- **Description:** https://www.cl.cam.ac.uk/research/nl/bea2019st/#data
- **Paper:** https://www.aclweb.org/anthology/W19-4406/
- **Motivation:** This is a recent dataset (actually two in one) for grammatical error correction and is used for benchmarking in this field of NLP.
### Checkbox
- [x] Create the dataset script `/datasets/my_dataset/my_dataset.py` using the template
- [x] Fill the `_DESCRIPTION` and `_CITATION` variables
- [x] Implement `_infos()`, `_split_generators()` and `_generate_examples()`
- [x] Make sure that the `BUILDER_CONFIGS` class attribute is filled with the different configurations of the dataset and that the `BUILDER_CONFIG_CLASS` is specified if there is a custom config class.
- [x] Generate the metadata file `dataset_infos.json` for all configurations
- [x] Generate the dummy data `dummy_data.zip` files to have the dataset script tested and that they don't weigh too much (<50KB)
- [x] Add the dataset card `README.md` using the template : fill the tags and the various paragraphs
- [x] Both tests for the real data and the dummy data pass.
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add thai_toxicity_tweet
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Thai Toxicity Tweet Corpus contains 3,300 tweets (506 tweets with texts missing) annotated by humans with guidelines including a 44-word dictionary. The author obtained 2,027 and 1,273 toxic and non-toxic tweets, respectively; these were labeled by three annotators. The result of corpus analysis indicates that tweets that include toxic words are not always toxic. Further, it is more likely that a tweet is toxic, if it contains toxic words indicating their original meaning. Moreover, disagreements in annotation are primarily because of sarcasm, unclear existing target, and word sense ambiguity.
Notes from data cleaner: The data is included into [huggingface/datasets](https://www.github.com/huggingface/datasets) in Dec 2020. By this time, 506 of the tweets are not available publicly anymore. We denote these by `TWEET_NOT_FOUND` in `tweet_text`.
Processing can be found at [this PR](https://github.com/tmu-nlp/ThaiToxicityTweetCorpus/pull/1).
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Update step-by-step guide for windows
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Update step-by-step guide for windows to give an alternative to `make style`.
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Add Bing Coronavirus Query Set
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Added dataset clickbait_news_bg
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MDU6SXNzdWU3NjEwNTU2NTE=
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FileNotFound remotly, can't load a dataset
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NONE
| null | null | null |
```py
!pip install datasets
import datasets as ds
corpus = ds.load_dataset('large_spanish_corpus')
```
gives the error
> FileNotFoundError: Couldn't find file locally at large_spanish_corpus/large_spanish_corpus.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/large_spanish_corpus/large_spanish_corpus.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/large_spanish_corpus/large_spanish_corpus.py
not just `large_spanish_corpus`, `zest` too, but `squad` is available.
this was using colab and localy
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MDExOlB1bGxSZXF1ZXN0NTM1NzYyNTQ1
| 1,443 |
Add OPUS Wikimedia Translations Dataset
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Create XML dummy data without loading all dataset in memory
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While I was adding one XML dataset, I noticed that all the dataset was loaded in memory during the dummy data generation process (using nearly all my laptop RAM).
Looking at the code, I have found that the origin is the use of `ET.parse()`. This method loads **all the file content in memory**.
In order to fix this, I have refactorized the code and use `ET.iterparse()` instead, which **parses the file content incrementally**.
I have also implemented a test.
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Add Igbo-English Machine Translation Dataset
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Adding english plaintext jokes dataset
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This PR adds a dataset of 200k English plaintext Jokes from three sources: Reddit, Stupidstuff, and Wocka.
Link: https://github.com/taivop/joke-dataset
This is my second PR.
First was: [#1269 ](https://github.com/huggingface/datasets/pull/1269)
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Update README.md
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1k-10k -> 1k-1M
3 separate configs are available with min. 1K and max. 211.3k examples
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A descriptive name for my changes
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hind encorp resubmited
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Add Indosum dataset
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add ALT
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ALT dataset -- https://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/
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Add FreebaseQA dataset
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This PR adds the FreebaseQA dataset: A Trivia-type QA Data Set over the Freebase Knowledge Graph
Repo: https://github.com/kelvin-jiang/FreebaseQA
Paper: https://www.aclweb.org/anthology/N19-1028.pdf
## TODO: create dummy data
Error encountered when running `python datasets-cli dummy_data datasets/freebase_qa --auto_generate`
```
f"Couldn't parse columns {list(json_data.keys())}. "
ValueError: Couldn't parse columns ['Dataset', 'Version', 'Questions']. Maybe specify which json field must be used to read the data with --json_field <my_field>.
```
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adding [SOFC-Exp Corpus](https://arxiv.org/abs/2006.03039)
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Adding the ASSIN 2 dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring
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Adding journalists questions dataset
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This is my first dataset to be added to HF.
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Ar cov19
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Adding ArCOV-19 dataset. ArCOV-19 is an Arabic COVID-19 Twitter dataset that covers the period from 27th of January till 30th of April 2020. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering COVID-19 pandemic that includes over 1M tweets alongside the propagation networks of the most-popular subset of them (i.e., most-retweeted and-liked). The propagation networks include both retweets and conversational threads (i.e., threads of replies). ArCOV-19 is designed to enable research under several domains including natural language processing, information retrieval, and social computing, among others.
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Add 1.5 billion words Arabic corpus
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Needs https://github.com/huggingface/datasets/pull/1429 to work.
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extract rar files
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Unfortunately, I didn't find any native python libraries for extracting rar files. The user has to manually install `sudo apt-get install unrar`. Discussion with @yjernite is in the slack channel.
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Add twi WordSim 353
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Hebrew project BenYehuda
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Added Hebrew corpus from https://github.com/projectbenyehuda/public_domain_dump
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init commit for MultiReQA for third PR with all issues fixed
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3rd PR w.r.t. PR #1349 with all the issues fixed. As #1349 had uploaded other files along with the multi_re_qa dataset
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Add german common crawl dataset
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Adding a subpart of the Common Crawl which was extracted with this repo https://github.com/facebookresearch/cc_net and additionally filtered for duplicates
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Add yoruba wordsim353
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Added WordSim-353 evaluation dataset for Yoruba
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Imppres
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2nd PR ever! Hopefully I'm starting to get the hang of this. This is for the IMPPRES dataset. Please let me know of any corrections or changes that need to be made.
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Can't map dataset (loaded from csv)
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Hello! I am trying to load single csv file with two columns: ('label': str, 'text' str), where is label is str of two possible classes.
Below steps are similar with [this notebook](https://colab.research.google.com/drive/1-JIJlao4dI-Ilww_NnTc0rxtp-ymgDgM?usp=sharing), where bert model and tokenizer are used to classify lmdb loaded dataset. Only one difference it is the dataset loaded from .csv file.
Here is how I load it:
```python
data_path = 'data.csv'
data = pd.read_csv(data_path)
# process class name to indices
classes = ['neg', 'pos']
class_to_idx = { cl: i for i, cl in enumerate(classes) }
# now data is like {'label': int, 'text' str}
data['label'] = data['label'].apply(lambda x: class_to_idx[x])
# load dataset and map it with defined `tokenize` function
features = Features({
target: ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None),
feature: Value(dtype='string', id=None),
})
dataset = Dataset.from_pandas(data, features=features)
dataset.map(tokenize, batched=True, batch_size=len(dataset))
```
It ruins on the last line with following error:
```
---------------------------------------------------------------------------
AssertionError Traceback (most recent call last)
<ipython-input-112-32b6275ce418> in <module>()
9 })
10 dataset = Dataset.from_pandas(data, features=features)
---> 11 dataset.map(tokenizer, batched=True, batch_size=len(dataset))
2 frames
/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint)
1237 test_inputs = self[:2] if batched else self[0]
1238 test_indices = [0, 1] if batched else 0
-> 1239 update_data = does_function_return_dict(test_inputs, test_indices)
1240 logger.info("Testing finished, running the mapping function on the dataset")
1241
/usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in does_function_return_dict(inputs, indices)
1208 fn_args = [inputs] if input_columns is None else [inputs[col] for col in input_columns]
1209 processed_inputs = (
-> 1210 function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs)
1211 )
1212 does_return_dict = isinstance(processed_inputs, Mapping)
/usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py in __call__(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs)
2281 )
2282 ), (
-> 2283 "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) "
2284 "or `List[List[str]]` (batch of pretokenized examples)."
2285 )
AssertionError: text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples).
```
which I think is not expected. I also tried the same steps using `Dataset.from_csv` which resulted in the same error.
For reproducing this, I used [this dataset from kaggle](https://www.kaggle.com/team-ai/spam-text-message-classification)
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adding fake-news-english-2
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Add Turkish News Category Dataset (270K)
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This PR adds the Turkish News Categories Dataset (270K) dataset which is a text classification dataset by me and @yavuzKomecoglu. Turkish news dataset consisting of **273601 news** in **17 categories**, compiled from printed media and news websites between 2010 and 2017 by the [Interpress](https://www.interpress.com/) media monitoring company.
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Data loading script and dataset card for Dialectal Arabic Resources dataset.
Fixed git issues from PR #976
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Add Shrinked Turkish NER from [Kaggle](https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar).
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Add [Hate Speech and Offensive Language Detection dataset](https://github.com/t-davidson/hate-speech-and-offensive-language) from [this paper](https://arxiv.org/abs/1703.04009).
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Adding BioCreative II Gene Mention corpus
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Adding BioCreative II Gene Mention corpus
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Add [OffComBR](https://github.com/rogersdepelle/OffComBR) from [Offensive Comments in the Brazilian Web: a dataset and baseline results](https://sol.sbc.org.br/index.php/brasnam/article/view/3260/3222) paper.
But I'm having a hard time generating dummy data since the original dataset extion is `.arff` and the [_create_dummy_data function](https://github.com/huggingface/datasets/blob/a4aeaf911240057286a01bff1b1d75a89aedd57b/src/datasets/commands/dummy_data.py#L185) doesn't allow it.
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Adding the ASSIN dataset
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Adding the ASSIN dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring
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Add penn treebank dataset
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Adding the ASSIN dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring
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Binary Portuguese Hate Speech dataset from [this paper](https://www.aclweb.org/anthology/W19-3510/).
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Adding a new dataset - clickbait_news_bg
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I had mistaken use git rebase, I was so hurried to fix it. However, I didn't fully consider the use of git reset , so I unintendedly stopped PR (#1367) altogether. Sorry about that.
I'll make a new PR.
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Adding reading comprehension dataset for Bulgarian language
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Adding the EAC Translation Memory dataset : https://ec.europa.eu/jrc/en/language-technologies/eac-translation-memory
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Add HoVer Dataset
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HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification
https://arxiv.org/abs/2011.03088
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dataset card creator link has been added
link: https://huggingface.co/datasets/card-creator/
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initial commit for MultiReQA for second PR
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Since last PR #1349 had some issues passing the tests. So, a new PR is generated.
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Add WikiSource Dataset
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Add OfisPublik Dataset
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Add script_version suggestion when dataset/metric not found
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Adds a helpful prompt to the error message when a dataset/metric is not found, suggesting the user might need to pass `script_version="master"` if the dataset was added recently. The whole error looks like:
> Couldn't find file locally at blah/blah.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1/metrics/blah/blah.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/met
rics/blah/blah.py.
If the dataset was added recently, you may need to to pass script_version="master" to find the loading script on the master branch.
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Add KDE4 Dataset
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Add MultiParaCrawl Dataset
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Add SPC Dataset
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add amazon polarity dataset
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This corresponds to the amazon (binary dataset) requested in https://github.com/huggingface/datasets/issues/353
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hind_encorp
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resubmit of hind_encorp file changes
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Add LIAR dataset
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Add LIAR dataset from [“Liar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection](https://www.aclweb.org/anthology/P17-2067/).
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Add RecipeNLG Dataset (manual download)
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add best2009
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`best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by [NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10). The test set answers are not provided publicly.
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Add News Commentary Dataset
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added conv ai 2
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Dataset : https://github.com/DeepPavlov/convai/tree/master/2018
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adding UNPC
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Adding United Nations Parallel Corpus
http://opus.nlpl.eu/UNPC.php
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Add twi text c3
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Added Twi texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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Add Tatoeba Dataset
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Add yoruba text c3
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Added Yoruba texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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This PR adds [FACTCK.BR](https://github.com/jghm-f/FACTCK.BR) dataset from [FACTCK.BR: a new dataset to study fake news](https://dl.acm.org/doi/10.1145/3323503.3361698).
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Adding marathi-wiki-articles dataset.
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Add OPUS EMEA Dataset
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Add OPUS Tilde Model Dataset
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