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Add : Conv AI 2 (Messed up original PR)
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@lhoestq Sorry I messed up the previous 2 PR's -> https://github.com/huggingface/datasets/pull/1462 -> https://github.com/huggingface/datasets/pull/1383. So created a new one. Also, everything is fixed in this PR. Can you please review it ? Thanks in advance.
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added Hebrew thisworld corpus
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added corpus from https://thisworld.online/ , https://github.com/thisworld1/thisworld.online
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Adding a second branch for Atomic to fix git errors
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Adding the Atomic common sense dataset. See https://homes.cs.washington.edu/~msap/atomic/
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ADD: swahili dataset for language modeling
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Add a corpus for Swahili language modelling. All tests passed locally. README updated with all information available.
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Add eHealth Knowledge Discovery dataset
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[ "Thank you very much for your review @lewtun ! \r\n\r\nI've updated the script metadata, created the README and fixed the two details you commented.\r\n\r\nReady for another review! 🤗 ", "I've updated the task tag as we discussed and also added a couple of lines of code to make sure I include all the available examples.\r\n\r\nThank you again!" ]
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This Spanish dataset can be used to mine knowledge from unstructured health texts. In particular, for: - Entity recognition - Relation extraction
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Add semeval 2020 task 11
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[ "@SBrandeis : Thanks for the feedback! Just updated to use context manager for the `open`s and removed the placeholder text from the `README`!", "Great, thanks @ZacharySBrown !\r\nFailing tests seem to be unrelated to your changes, merging the current master branch into yours should fix them.\r\n" ]
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Adding in propaganda detection task (task 11) from Sem Eval 2020
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Atomic
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[ "I had to create a new PR to fix git errors. See: https://github.com/huggingface/datasets/pull/1525\r\n\r\nI'm closing this PR. " ]
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This is the ATOMIC common sense dataset. More info can be found here: * README.md still to be created.
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ru_reviews dataset adding
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[ "Hi @lhoestq \r\n\r\nI have added the readme as well \r\n\r\nPlease do have a look at it when suitable ", "Chatted with @darshan-gandhi on Slack about parsing examples into a separate text and sentiment field" ]
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RuReviews: An Automatically Annotated Sentiment Analysis Dataset for Product Reviews in Russian
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Initial commit for AQuaMuSe
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[ "@yjernite Thank you for your help, generating the dummy data 🤗 Having that all the tests have passed 👍🏻", "merging since the CI is fixed on master", "Thank you :)" ]
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There is an issue in generation of dummy data. Tests on real data have passed locally.
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[ "@lhoestq thanks for the comments! Should be fixed in the latest commit, I assume the CI errors are unrelated. ", "merging since the CI is fixed on master" ]
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how to get all the options of a property in datasets
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[ "In a dataset, labels correspond to the `ClassLabel` feature that has the `names` property that returns string represenation of the integer classes (or `num_classes` to get the number of different classes).", "I think the `features` attribute of the dataset object is what you are looking for:\r\n```\r\n>>> dataset.features\r\n{'sentence1': Value(dtype='string', id=None),\r\n 'sentence2': Value(dtype='string', id=None),\r\n 'label': ClassLabel(num_classes=2, names=['not_equivalent', 'equivalent'], names_file=None, id=None),\r\n 'idx': Value(dtype='int32', id=None)\r\n}\r\n>>> dataset.features[\"label\"].names\r\n['not_equivalent', 'equivalent']\r\n```\r\n\r\nFor reference: https://huggingface.co/docs/datasets/exploring.html" ]
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Hi could you tell me how I can get all unique options of a property of dataset? for instance in case of boolq, if the user wants to know which unique labels it has, is there a way to access unique labels without getting all training data lables and then forming a set i mean? thanks
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[ "Hi @lhoestq \r\n\r\nI have added the readme file as well, please if you could check it once \r\n\r\nThank you " ]
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- Added tags, Readme file - Added code changes
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[ "The only CI error comes from \r\n```\r\nFAILED tests/test_file_utils.py::TempSeedTest::test_tensorflow\r\n```\r\n\r\nwhich is not related to your PR and is fixed on master.\r\n\r\nYou can ignore it", "@lhoestq I've made the changes. Please review and merge. \r\n\r\nI have a similar PR https://github.com/huggingface/datasets/pull/1562 for another dataset. I'll incorporate your comment about sorting and reducing dummy dataset size there.", "The CI raises an error `FAILED tests/test_file_utils.py::TempSeedTest::test_tensorflow` but it's not related to this dataset.\r\nThis issue is fixed on master", "You did all the work ;) thanks\r\n\r\nmerging since the CI is fixed on master" ]
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Need help with the dummy data.
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Fix namedsplit docs
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[ "Hii please follow me", "Thanks @mariosasko!" ]
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Fixes a broken link and `DatasetInfoMixin.split`'s docstring.
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Add SelQA Dataset
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[ "Hii please follow me", "The CI error `FAILED tests/test_file_utils.py::TempSeedTest::test_tensorflow` is not related with this dataset and is fixed on master. You can ignore it", "merging since the Ci is fixed on master" ]
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Add the SelQA Dataset, a new benchmark for selection-based question answering tasks Repo: https://github.com/emorynlp/selqa/ Paper: https://arxiv.org/pdf/1606.08513.pdf
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Add nq_open question answering dataset
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[ "@SBrandeis thanks for the review, I applied your suggested changes, but CI is failing now not sure about the error.", "Many thanks @Nilanshrajput !\r\nThe failing tests on CI are not related to your changes, merging master on your branch should fix them :)\r\nIf you're interested in what causes the CI to fail, checkout [this commit](https://github.com/huggingface/datasets/commit/9a0f1e20ca1e783cb14c1ab1cc2f54b0b5b201e8)", "@SBrandeis done!\r\n", "Hello @Nilanshrajput, your PR includes changes from other branches too now (485 files changed)\r\nWould you mind creating another branch from master with your changes and opening a new PR?", "@SBrandeis sorry i messed up the git history, #1587 I opened this new pr! ", "closing in favor of #1587 " ]
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Added nq_open Open-domain question answering dataset. The NQ-Open task is currently being used to evaluate submissions to the EfficientQA competition, which is part of the NeurIPS 2020 competition track.
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add ilist dataset
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This PR will add Indo-Aryan Language Identification Shared Task Dataset.
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Add SentiWS dataset for pos-tagging and sentiment-scoring (German)
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[ "Hi @lhoestq @yjernite, requesting you to review this for any changes needed. Thanks! :)", "Hi @lhoestq , I have updated the PR" ]
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Adding COVID QA dataset in Chinese and English from UC SanDiego
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[ "Changed the pre-processing based on the comments raised in [PR-1482](https://github.com/huggingface/datasets/pull/1482).The below command is passing in my local environment:\r\n\r\n`python datasets-cli test datasets/covid_qa_ucsd/ --save_infos --all_configs --data_dir ~/Downloads/Medical-Dialogue-Dataset/CovidDailogue/`\r\n\r\n" ]
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Add Senti_Lex Dataset
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[ "Better will be if you close this PR and make a fresh PR", "Feel free to ping me if you also have questions about the dummy data", "also it looks like this PR includes changes about dummy_data.zip files in the ./datasets//un_pc folder. Can you remove them ?", "Thanks for all the advice @lhoestq. I've implemented the changes you kindly highlighted and have made sure the scripts pass all the test. I've also marked this as ready for review as I believe it's in a good place to be merged now.", "Great suggestion I fixed the dummy data and the file paths." ]
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TODO: Fix feature format issue Create dataset_info.json file Run pytests Make Style
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Adds XED dataset
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[ "Hi @lhoestq @yjernite, requesting you to review this for any changes needed. Thanks! :)" ]
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adding polsum
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[ "@lhoestq thanks for the comments! Should be fixed in the latest commit, I assume the CI errors are unrelated." ]
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update the dataset id_newspapers_2018
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Hi, I need to update the link to the dataset. The link in the previous PR was to a small test dataset. Thanks
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add stereoset
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StereoSet is a dataset that measures stereotype bias in language models. StereoSet consists of 17,000 sentences that measures model preferences across gender, race, religion, and profession.
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adding fake-news-english-5
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Add Multi-Dimensional Gender Bias classification data
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https://parl.ai/projects/md_gender/ Mostly has the ABOUT dimension since the others are inferred from other datasets in most cases. I tried to keep the dummy data small but one of the configs has 140 splits ( > 56KB data)
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Opus DGT added
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Dataset : http://opus.nlpl.eu/DGT.php
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Added Opus Wikipedia
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Dataset : http://opus.nlpl.eu/Wikipedia.php
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Added RONEC dataset.
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[ "Thanks for the PR @iliemihai . \r\n\r\nFew comments - \r\n\r\nCan you run - \r\n`python datasets-cli dummy_data ./datasets/ronec --auto_generate` to generate dummy data.\r\n\r\nAlso, before committing files run : \r\n`make style`\r\n`flake8 datasets`\r\nthen you can add and commit files.", "> Thanks for the PR @iliemihai .\r\n> \r\n> Few comments -\r\n> \r\n> Can you run -\r\n> `python datasets-cli dummy_data ./datasets/ronec --auto_generate` to generate dummy data.\r\n> \r\n> Also, before committing files run :\r\n> `make style`\r\n> `flake8 datasets`\r\n> then you can add and commit files.\r\n\r\nSorry, forgot to generate dummy data. I will do it now :D", "Awesome, good job @iliemihai !\r\nI think the PR is ready to merge.\r\n@lhoestq would you mind double-checking this ?", "Had to regenerate the dummy data since I just found out they were empty files" ]
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OPUS UBUNTU dataset
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Dataset : http://opus.nlpl.eu/Ubuntu.php
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added opus GNOME data
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Dataset : http://opus.nlpl.eu/GNOME.php
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ADD: opus_rf dataset for translation
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Passed all local tests. Hopefully passes all Circle CI tests too. Tried to keep the commit history clean.
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Fake news english 4
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[ "Thanks for the PR @MisbahKhan789 !\r\n\r\nFew comments to help you along (I'm NOT a maintainer, just offering help to unblock the process) :-\r\n - Could you re-run `make style` and fix the errors related to code quality specific to your dataset in the `datasets/fake_news_english` folder?\r\n(These seem to show errors that need manual fixes on running `flake8 datasets/fake_news_english`)\r\n- Please run the local tests and check if they pass\r\n`RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_<your-dataset-name>`\r\n `RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your-dataset-name>`\r\n(If not, you may have to regenerate the dummy data and the `dataset_infos.json` files)\r\n\r\n", "Hii please follow me", "> Thanks for the PR @MisbahKhan789 !\r\n> \r\n> Few comments to help you along (I'm NOT a maintainer, just offering help to unblock the process) :-\r\n> \r\n> * Could you re-run `make style` and fix the errors related to code quality specific to your dataset in the `datasets/fake_news_english` folder?\r\n> (These seem to show errors that need manual fixes on running `flake8 datasets/fake_news_english`)\r\n> * Please run the local tests and check if they pass\r\n> `RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_<your-dataset-name>`\r\n> `RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your-dataset-name>`\r\n> (If not, you may have to regenerate the dummy data and the `dataset_infos.json` files)\r\n\r\nHey Bharat, thanks for the reply. I actually submitted a new PR with the changes that are required :)\r\n" ]
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Adding NELL
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[ "hi @lhoestq, I wanted to push another change to this branch b/c I found a bug in the parsing. I need to swap arg1 and arg2. I tried to git push -u origin nell but it didn't work. So I tried to do git push --force -u origin nell which seems to work, but nothing is happening to this branch. I think this is because it's closed. Do I need to open another PR?\r\n\r\nThe change should be below in _generate_examples:\r\n best_arg1 = row[9]\r\n best_arg2 = row[8]\r\n", "Hi @ontocord !\r\n\r\nYup the easiest thing to do is to open a new PR with a title like \"Fix NELL dataset argument order\". If it's a simple fix we can look at it pretty fast :) " ]
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NELL is a knowledge base and knowledge graph along with sentences used to create the KB. See http://rtw.ml.cmu.edu/rtw/ for more details.
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added conv_ai_3 dataset
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[ "@lhoestq Thank you for suggesting changes. I fixed all the changes you suggested. Can you please review it again? ", "@lhoestq Thank you for reviewing and suggesting changes. I made the requested changes. Can you please review it again?", "Thanks @lhoestq for reviewing it again. I made the required changes. Can you please have a look ?", "merging since the CI is fixed on master" ]
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Dataset : https://github.com/aliannejadi/ClariQ/
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hate speech 18 dataset
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[ "The error `tests/test_file_utils.py::TempSeedTest::test_tensorflow` just appeared because of tensorflow's update.\r\nOnce it's fixed on master we'll be free to merge this one", "It's fixed on master now :) \r\n\r\nmerging this once" ]
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This is again a PR instead of #1339, because something went wrong there.
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Re-added wiki_movies dataset due to previous PR having changes from m…
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…any other unassociated files.
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Add peer-read dataset
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[ "> Cool thank you !\r\n> \r\n> I left a few comments\r\n\r\nThank you @lhoestq addressed your comments. Haven't changed the code but I see that tests are failing now. Do I need to rebase or something? ", "The CI error is not related to your dataset and is fixed on master.\r\nYou can ignore it" ]
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Added Times of India News Headlines Dataset
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[ "@lhoestq @abhishekkrthakur what happened here ?\r\n", "@lhoestq everything alright here ?", "@tanmoyio please have patience. @lhoestq has to look at 150+ PRs and it may take time. The PR looks good to me but we wait for his confirmation :) 🤗 " ]
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Dataset name: Times of India News Headlines link: https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/DPQMQH
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Adding medical database chinese and english
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[ "Let me know it that helps !\r\nAlso feel free to ping me if you have other questions or if I can help you.", "Now I am getting an Assertion Error!\r\n![image](https://user-images.githubusercontent.com/16264631/101943915-f5bf5600-3c11-11eb-84e5-045bbc472162.png)\r\n", "All tests have passed. However, PyTest is still failing with the `AssertionError` as before. Also _datasets_info.json_ actually does not seem to provide much info. Please review and let me know what has to be improved.\r\n\r\nThanks!", "[PR-1503](https://github.com/huggingface/datasets/pull/1503) on the COVID dialog dataset from the same University has similar features. I kept it separate because it is only on COVID qa. Also consists of only single files per language. Kindly let me know if it has to be added as two more configurations to this existing dataset itself. If it has to be added, then can I still freeze the file names like in PR-1503?", "It's ok to have them separate" ]
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Error in creating dummy dataset
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Fix ADD_NEW_DATASET to avoid rebasing once pushed
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Adding the Mac-Morpho dataset
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Adding the Mac-Morpho dataset, a Portuguese language dataset for Part-of-speech tagging tasks
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Add narrativeQA
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[ "@lhoestq this is now only failing some random windows test (it appears to be somewhere in wnut_17)", "This is a connection error, you can ignore it :) \r\nThe level of activity on the lib is quite overwhelming, it stresses a bit the CI ^^" ]
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Redo of #1368 #309 #499 In redoing the dummy data a few times, I ended up adding a load of files to git. Hopefully this should work.
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Inconsistent argument names.
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[ "Also for the `Accuracy` metric the `accuracy_score` method should have its args in the opposite order so `accuracy_score(predictions, references,,,)`.", "Thanks for pointing this out ! 🕵🏻 \r\nPredictions and references should indeed be swapped in the docstring.\r\nHowever, the call to `accuracy_score` should not be changed, it [signature](https://scikit-learn.org/stable/modules/generated/sklearn.metrics.accuracy_score.html#sklearn.metrics.accuracy_score) being:\r\n```\r\nsklearn.metrics.accuracy_score(y_true, y_pred, *, normalize=True, sample_weight=None)\r\n```\r\n\r\nFeel free to open a PR if you want to fix this :)" ]
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Just find it a wee bit odd that in the transformers library `predictions` are those made by the model: https://github.com/huggingface/transformers/blob/master/src/transformers/trainer_utils.py#L51-L61 While in many datasets metrics they are the ground truth labels: https://github.com/huggingface/datasets/blob/c3f53792a744ede18d748a1133b6597fdd2d8d18/metrics/accuracy/accuracy.py#L31-L40 Do you think predictions & references should be swapped? I'd be willing to do some refactoring here if you agree.
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Jigsaw toxicity pred
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Managed to mess up my original pull request, opening a fresh one incorporating the changes suggested by @lhoestq.
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Add Spanish Billion Words Corpus
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Add an unannotated Spanish corpus of nearly 1.5 billion words, compiled from different resources from the web.
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Fix XML iterparse in opus_dogc dataset
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I forgot to add `elem.clear()` to clear the element from memory.
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Create JSON dummy data without loading all dataset in memory
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See #1442. The statement `json.load()` loads **all the file content in memory**. In order to avoid this, file content should be parsed **iteratively**, by using the library `ijson` e.g. I have refactorized the code into a function `_create_json_dummy_data` and I have added some tests.
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Adding the HAREM dataset
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[ "Thanks for the changes !\r\n\r\nSorry if I wasn't clear about the suggestion of adding the `raw` dataset as well.\r\nBy `raw` I meant the dataset with its original features, i.e. not tokenized to follow the conll format for NER.\r\nThe `raw` dataset has data fields `doc_text`, `doc_id` and `entities`.", "Alright, @lhoestq, now I understand your suggestion, but the JSON files the script downloads aren't actually the \"raw\" HAREM dataset, the [real raw version](https://www.linguateca.pt/primeiroHAREM/harem/ColeccaoDouradaHAREM.zip) of it is on XML format that needs a lot of preprocessing. Those JSON are just pre-processed versions of the dataset.\r\n\r\nI can make the config of the raw version of the pre-processed dataset, but I'll leave a comment on the dataset summary about those details.", "Oh I see ! Sorry I thought there really were the raw (i.e. original/unprocessed) files", "The original xml format doesn't seem very practical to use :/ \r\nWe can ignore that and only keep the default and selective configs then.\r\nCan you revert to the old configs ?\r\n\r\nThanks again for adding this dataset !", "Hi @lhoestq, I've reverted the changes and put more details on README about the dataset." ]
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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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[ "it’s failing because of `RemoteDatasetTest.test_load_dataset_orange_sum`\r\nwhich i think is not the dataset you are doing a PR for. Try rebasing with:\r\n```\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push -u -f origin your_branch\r\n```", "> it’s failing because of `RemoteDatasetTest.test_load_dataset_orange_sum`\r\n> which i think is not the dataset you are doing a PR for. Try rebasing with:\r\n> \r\n> ```\r\n> git fetch upstream\r\n> git rebase upstream/master\r\n> git push -u -f origin your_branch\r\n> ```\r\n\r\nThanks, my branch seems to be up to date. \r\n```Current branch add-wiki-lingua-dataset is up to date.```", "Also where do the google drive urls come from ?", "looks like this PR includes changes about many other files than the ones for wiki_lingua.\r\n\r\nCan you create another branch and another PR ?\r\n(or you can try to fix this branch with rebase and push force if you're familiar with it)", "Thanks for fixing the dummy data and removing the glob call :) ", "> looks like this PR includes changes about many other files than the ones for wiki_lingua.\r\n> \r\n> Can you create another branch and another PR ?\r\n> (or you can try to fix this branch with rebase and push force if you're familiar with it)\r\n\r\nEasier to create a new branch and submit, I have submitted a new PR #1582 ", "Closing this one in favor of #1582 " ]
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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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[ "Looks like there's a `Path` issue on windows. Could you try switching to\r\n`glob.glob(os.path.join(article_dir, \"*.json\"))`", "> Looks like there's a `Path` issue on windows. Could you try switching to\r\n> `glob.glob(os.path.join(article_dir, \"*.json\"))`\r\n\r\nThanks, I replaced it with glob. Let's see if it solves the issue. Anyway, the main directory has a space, could it make the issue on windows? the test on linux don't have this problem.", "It seems glob doesn't help also. Btw, one of the failing test tried to connect aws which failed:\r\n```\r\nC:\\tools\\miniconda3\\lib\\site-packages\\urllib3\\connection.py:160: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _\r\n\r\naddress = ('s3.amazonaws.com', 443), timeout = 10, source_address = None\r\nsocket_options = [(6, 1, 1)]\r\n\r\n```\r\nWhy did it try to connect to aws? I don't use it.", "It seems that the circleci make a test for whole datasets repository, that means if only one of the dataset in the official repository has a download issue, this will also affect the test of a new dataset like mine, isn't it?\r\nI changed the url to my newspaper dataset which contains only few simple json files and simple directory structure. But it still failed. And it failed not only on windows test. This is one of the error message:\r\n```\r\n-- Docs: https://docs.pytest.org/en/stable/warnings.html\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ajgt_twitter_ar\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_chr_en\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_ajgt_twitter_ar\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_chr_en\r\n===== 4 failed, 2667 passed, 2052 skipped, 4 warnings in 432.05s (0:07:12) =====\r\n\r\nExited with code exit status 1\r\nCircleCI received exit code 1\r\n```\r\nThe test failed on twitter dataset even my dataset has nothing to do with twitter? ", "merging since the CI is fixed on master", "Hi, thanks for merging the dataset. I create a new PR (#1499) since I need to update the link to the dataset. " ]
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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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[ "@SBrandeis, What exactly is it that makes the tests fail? Can you help me please?", "These errors\r\n```\r\n=========================== short test summary info ============================\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ajgt_twitter_ar\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_chr_en\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_ajgt_twitter_ar\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_chr_en\r\n```\r\nappeared on master 3 hours ago and are now fixed.\r\n(it was due to today's update of `xlrd` that broke two datasets)\r\n\r\nYou can ignore them, they're not related to your dataset", "> These errors\r\n> \r\n> ```\r\n> =========================== short test summary info ============================\r\n> FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_ajgt_twitter_ar\r\n> FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_chr_en\r\n> FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_ajgt_twitter_ar\r\n> FAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_chr_en\r\n> ```\r\n> \r\n> appeared on master 3 hours ago and are now fixed.\r\n> (it was due to today's update of `xlrd` that broke two datasets)\r\n> \r\n> You can ignore them, they're not related to your dataset\r\n\r\n**If it is not a problem caused by us, we have already completed the review notes. You can then check it out and confirm?**", "merging since the CI is fixed on master" ]
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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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[ "@lhoestq rerun the tests " ]
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New Clean PR for menyo20k_mt
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Reddit jokes
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[ "@lhoestq would you please rerun the test, ", "I re-started the test.\r\n\r\n@lhoestq let's hold off on merging for now though, having a conversation on Slack about some of the offensive content in the dataset and how/whether we want to present it." ]
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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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[ "Looking perfect to me, need to rerun the tests\r\n", "Thanks, @tanmoyio. \r\nHow do I rerun the tests? Should I change something or push a new commit?", "@rkc007 you don't need to rerun it, @lhoestq @yjernite will rerun it, as there are huge number of PRs in the queue it might take lil bit of time. ", "ive just re-run the tests", "Thank you @abhishekkrthakur. Can you please rerun it again? It seems something was broken in CI during the previous test.", "@lhoestq Sorry for the mess. I don't know why this keeps on happening. I tried step by step process of updating the PR but seems something is wrong. This happened for 2nd time with the same PR. Apologies for that. \r\n\r\nNew PR -> https://github.com/huggingface/datasets/pull/1527\r\nAlso, I fixed everything in the new PR." ]
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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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[ "Generate the dummy dataset then regenerate the dataset_info.json file, ", "> Generate the dummy dataset then regenerate the dataset_info.json file,\r\n\r\nThe pytest scripts do not accept manual directory inputs for the data provided manually. This is why the tests fail. ", "don't use the --auto-generate argument and you will get a brief instructions on how to create dummy data for your dataset,\r\nalso you dont have to run the pytest for main dataset if your data is needed to be downloaded manually, just run the pytest for dummy dataset, and when you will create the json you need to provide the main data directory path by using this argument --data_dir", "Thanks for your help, @tanmoyio \r\nI tried with and without --auto_generate flag. \r\nHere are the issues. \r\n\r\n**With --auto_generate**\r\n`python datasets-cli dummy_data datasets/newsqa/ --auto_generate `\r\n`Traceback (most recent call last):\r\n File \"datasets-cli\", line 36, in <module>\r\n service.run()\r\n File \"/Users/sanjaykamath/Python_Projects/HuggingFace/datasets/src/datasets/commands/dummy_data.py\", line 321, in run\r\n keep_uncompressed=self._keep_uncompressed,\r\n File \"/Users/sanjaykamath/Python_Projects/HuggingFace/datasets/src/datasets/commands/dummy_data.py\", line 340, in _autogenerate_dummy_data\r\n dataset_builder._split_generators(dl_manager)\r\n File \"/Users/sanjaykamath/.cache/huggingface/modules/datasets_modules/datasets/newsqa/7a565b204506c1fd91047290073be54d3ae05fa2b0ab17ae0bc6f709350fcbca/newsqa.py\", line 180, in _split_generators\r\n path_to_manual_folder = os.path.abspath(os.path.expanduser(dl_manager.manual_dir))\r\n File \"/Users/sanjaykamath/anaconda3/envs/huggingface/lib/python3.7/posixpath.py\", line 235, in expanduser\r\n path = os.fspath(path)\r\nTypeError: expected str, bytes or os.PathLike object, not NoneType\r\n`\r\n\r\n\r\n**Without --auto_generate**\r\n`python datasets-cli dummy_data datasets/newsqa/`\r\n`Dataset with config BuilderConfig(name='combined-csv', version=1.0.0, data_dir=None, data_files=None, description='This part of the dataset covers the whole dataset in the combined format of CSV as mentioned here: https://github.com/Maluuba/newsqa#csv') seems to already open files in the method `_split_generators(...)`. You might consider to instead only open files in the method `_generate_examples(...)` instead. If this is not possible the dummy data has to be created with less guidance. Make sure you create the file None.\r\nTraceback (most recent call last):\r\n File \"datasets-cli\", line 36, in <module>\r\n service.run()\r\n File \"/Users/sanjaykamath/Python_Projects/HuggingFace/datasets/src/datasets/commands/dummy_data.py\", line 326, in run\r\n dataset_builder=dataset_builder, mock_dl_manager=mock_dl_manager\r\n File \"/Users/sanjaykamath/Python_Projects/HuggingFace/datasets/src/datasets/commands/dummy_data.py\", line 406, in _print_dummy_data_instructions\r\n for split in generator_splits:\r\nUnboundLocalError: local variable 'generator_splits' referenced before assignment\r\n`\r\n", "Excellent comments. Thanks @lhoestq for your valuable comments. \r\nI've changed everything you had mentioned and the tests pass now. \r\nLet me know if something still needs to be changed. ", "Thank you very much @lhoestq @tanmoyio @yjernite @thomwolf for all your support :) " ]
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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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[ "@lhoestq I think you might want to look at the dataset, and the first data instances mentioned in the README.md is very much offensive. Though this dataset is based on hate speech but I found the dataset heavily disturbing as Bengali is my native language.", "Hi @tanmoyio indeed you're right.\r\nWe should *at least* add very explicit mentions in the dataset card that the content of this dataset contains very offensive language. We should also put it in perspective with the tasks it tries to solve, the annotation process and the limitations.\r\n\r\nWe have to make sure that nothing is unclear/misleading nor could lead to bad usage of the dataset.\r\n\r\nWhat do you think @tanmoyio ?\r\nAlso feel free to suggest modifications in the dataset cards if you feel like some sections require corrections or more details", "> Hi @tanmoyio indeed you're right.\r\n> We should _at least_ add very explicit mentions in the dataset card that the content of this dataset contains very offensive language. We should also put it in perspective with the tasks it tries to solve, the annotation process and the limitations.\r\n> \r\n> We have to make sure that nothing is unclear/misleading nor could lead to bad usage of the dataset.\r\n> \r\n> What do you think @tanmoyio ?\r\n> Also feel free to suggest modifications in the dataset cards if you feel like some sections require corrections or more details\r\n\r\nyeah I agree with you. It would be good if \"Personal and Sensitive Information\" and \"Considerations for Using the Data\" is being explained properly in the README.md. @stevhliu ", "please let me know if there is anything else you'd like to see!", "This looks ok to merge for me. Let me know @stevhliu and @tanmoyio if you want to add something or if it looks good to you", "looks good to me @lhoestq 👍 ", "merging since the CI is fixed on master" ]
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Add Google Conceptual Captions Dataset (manual download)
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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 CC100 Dataset
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Closes #773
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Add HEAD-QA: A Healthcare Dataset for Complex Reasoning
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[ "Thank you for your review @lhoestq, I've changed the types of `qid` and `ra` and now they are integers as `aid`.\r\n\r\nReady for another review!" ]
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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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[ "merging since the CI is fixed on master" ]
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Add kinnews and kirnews
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Adding ethos dataset clean
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[ "> Thanks !\r\n\r\nThanks as well for your hard work 😊!!", "merging since the CI is fixed on master" ]
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I addressed the comments on the PR1318
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SNLI dataset contains labels with value -1
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[ "I believe the `-1` label is used for missing/NULL data as per HuggingFace Dataset conventions. If I recall correctly SNLI has some entries with no (gold) labels in the dataset.", "Ah, you're right. The dataset has some pairs with missing labels. Thanks for reminding me." ]
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``` 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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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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[ "linter your code with flake8 and also run the commands present in Makefile for proper formatting \r\n", "merging since the CI is fixed on master" ]
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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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[ "Hi @thomwolf, for simplification purposes, I think you could remove the \"`pip install ...`\" steps from this commit, 'cause these deps (black, isort, flake8) are already installed on `pip install -e \".[dev]\"` on the [Start by preparing your environment](https://github.com/huggingface/datasets/blob/704107f924e74445f6f0fbde69a218b72178b588/ADD_NEW_DATASET.md#start-by-preparing-your-environment)\r\n" ]
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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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[ "Looks like this PR includes changes about many other files than the ones for clickbait_news_bg\r\n\r\nCan you create another branch and another PR please ?", "I created a new branch with the dataset code and submitted a new PR for it: https://github.com/huggingface/datasets/pull/1568" ]
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FileNotFound remotly, can't load a dataset
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[ "This dataset will be available in version-2 of the library. If you want to use this dataset now, install datasets from `master` branch rather.\r\n\r\nCommand to install datasets from `master` branch:\r\n`!pip install git+https://github.com/huggingface/datasets.git@master`", "Closing this, thanks @VasudevGupta7 " ]
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```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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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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[ "Hi @purvimisal, thanks for your contributions!\r\n\r\nThis jokes dataset has come up before, and after a conversation with the initial submitter, we decided not to add it then. Humor is important, but looking at the actual data points in this set raises several concerns :) \r\n\r\nThe main issue is the Reddit part of the dataset which has most of the examples. A cursory look at the data shows a large number of highly offensive jokes that reproduce some pretty harmful biases (the second one from the top is a Holocaust joke). \r\n\r\nThe other two sources have similar issues (especially the \"Blond Jokes\") to a slightly lesser extent.\r\n\r\nWhile such datasets can be useful in the right context, there is a real concern that people using the library might miss some of this context (however much we outline it), and end up unwittingly training models that rely on some pretty racist and sexist associations.\r\n\r\nWe would recommend skipping this dataset altogether.\r\n\r\nIf you feel really strongly about having a joke dataset, then we would ask that you:\r\n- remove the Reddit part of the dataset altogether\r\n- write an in-depth description of the social biases present in the remaining data\r\n\r\nLet us know which of the two you decide! And if you want recommendations on other datasets to add, hit us up on Slack 🤗 ", "Hi @yjernite, thanks so much. I should've totally thought about this earlier. The harmful biases make so much sense. I should've consulted before making a PR. \r\nI will be closing this one and skipping this dataset altogether. \r\nThanks again \r\n" ]
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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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[ "I have noticed that the master branch of your fork has diverged from the one of the repo. This is probably what causes the mess in the github diff \"Files changed\".\r\n\r\nI would suggest to re-fork the `datasets` repo and recreate a new branch and a new PR. ", "You're pretty close to having all things ready to merge !\r\nFeel free to ping me when you have a new PR", "Closing this one in favor of #1575 " ]
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hind encorp resubmited
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Add Indosum dataset
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[ "Hi @prasastoadi have you had a chance to take a look at my suggestions ?\r\n\r\nFeel free to ping ;e if you have questions or when you're ready for a review" ]
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add ALT
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[ "The errors in de CI are fixed on master so it's fine" ]
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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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[ "@yjernite @lhoestq Any suggestions on how to get the dummy data generator to recognize the columns? The structure of the json is:\r\n```\r\n{\r\n \"Dataset\": \"FreebaseQA-eval\", \r\n \"Version\": \"1.0\", \r\n \"Questions\": [\r\n {\r\n \"Question-ID\": \"FreebaseQA-eval-0\", \r\n \"RawQuestion\": \"Who is the female presenter of the Channel 4 quiz show '1001 things you should know'?\", \r\n \"ProcessedQuestion\": \"who is the female presenter of the channel 4 quiz show '1001 things you should know'\", \r\n \"Parses\": [\r\n {\r\n \"Parse-Id\": \"FreebaseQA-eval-0.P0\", \r\n \"PotentialTopicEntityMention\": \"1001 things you should know\", \r\n \"TopicEntityName\": \"1001 things you should know\", \r\n \"TopicEntityMid\": \"m.0nd3t34\", \r\n \"InferentialChain\": \"tv.tv_program.regular_personal_appearances..tv.tv_regular_personal_appearance.person\", \r\n \"Answers\": [\r\n {\r\n \"AnswersMid\": \"m.0216y_\", \r\n \"AnswersName\": [\r\n \"sandi toksvig\"\r\n ]\r\n }\r\n ]\r\n }\r\n ]\r\n }, \r\n ...\r\n ]\r\n}\r\n```\r\n\r\nThanks!", "Unfortunately this json structure is not recognized by the auto-generation yet, so you'd have to create the dummy data manually. \r\nYou can get some instructions on how to do that with: `python datasets-cli dummy_data datasets/freebase_qa`\r\nWe can definitely help you with that if there are too many files! ", "@yjernite Thanks for the instructions. I manually added dummy data and created the zip file but one of the splits seem to return an empty list.\r\n\r\n```\r\ntests/test_dataset_common.py F [100%]\r\n\r\n========================= FAILURES ==========================\r\n_ LocalDatasetTest.test_load_dataset_all_configs_freebase_qa _\r\n\r\nself = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_freebase_qa>\r\ndataset_name = 'freebase_qa'\r\n\r\n @slow\r\n def test_load_dataset_all_configs(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)\r\n\r\ntests/test_dataset_common.py:237:\r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _\r\ntests/test_dataset_common.py:198: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n```\r\n\r\nNote that the dataset has `train`, `eval`, and `dev` (no test split). I am not sure if I am mapping them correctly when I called the Split Generator.\r\n", "The dummy json files must follow the exact same structure as the original json files.\r\n\r\nHowever it looks like the dummy json files you have in your dummy_data.zip file are not structured the same way.\r\nFor example the original json is a dict with a field \"Questions\" that is a list of items.\r\nHowever your dummy json is simply a list of items.\r\n\r\nCan you update your dummy json files to follow the same structure ?", "And I'm pretty sure that this structure is supported by the dummy data auto-generation tool\r\n```\r\npython datasets-cli dummy_data ./datasets/freebase_qa --json_field \"Questions\"\r\n```", "Hi @anaerobeth did you manage to get the dummy data right ?\r\n\r\nFeel free to ping me if you have questions or when you're ready for a review", "Thanks for your help! I am able to create the dummy data with the dict structure as suggested. I'll add the tags and update this PR shortly.", "Also don't forget to run `make style` to fix the code formatting check in the CI :)", "Hi @anaerobeth ! Have you had a chance to consider updating the dataset script to yield one example per question ?\r\n\r\nFeel free to ping me if you have questions or if I can help :) ", "Hi @lhoestq,\r\n\r\nI am willing to take this forward if you and @anaerobeth don't mind.\r\n", "Hi @gchhablani thanks for proposing your help :) \r\nSure if you want to take this forward feel free to do so.\r\nAlso pinging @anaerobeth to make sure that you both don't work on the same thing at the same time", "Hi ! Closing this one since the dataset was added in #1814 \r\n\r\nThanks you two @anaerobeth and @gchhablani for adding this 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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[ "Hey @lhoestq , thanks for the feedback on this! I updated the `_generate_examples` with some comments on the process, and reduced the `dummy_data.zip` down quite a bit as well. \r\n\r\nFor the dummy data, I reduced the text to only three sentences, and aligned the corresponding entity/token/sentence annotations to that (reduced accordingly). The frames file is a strange combined format for the annotations and I found if I reduced that that would break the parser no matter what I did, so I left that as is. The difference between a reduced frames and non-reduced frames file in the compressed dummy data was only about ~4kb, so hopefully leaving this as is will be ok!" ]
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adding [SOFC-Exp Corpus](https://arxiv.org/abs/2006.03039)
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Adding the ASSIN 2 dataset
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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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[ "@lhoestq Thanks a lot for checking! I hope I addressed all your comments. ", "merging since the CI is fixed on master" ]
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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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[ "Can't pass dummy data tests. For the instructions, it asks me to generate the following file `dummy_data/Youm7_XML_utf_8.rar/Youm7_utf_8.xml` which is strange, any ideas @lhoestq ?\r\n\r\ncc: I tested the data locally and it works, maybe the dummy tests doesn't support `rar` ? ", "In the dummy_data.zip files you must include the rar file as if is was already extracted.\r\nIn particular here `Youm7_XML_utf_8.rar` is a directory (not an archive).", "Also I'm getting `BadRarFile: Failed the read enough data: req=16384 got=51` while trying to download and extract the `Alittihad_XML_utf_8.rar` file. Do you have this issue as well ?\r\n\r\nI have rarfile 4.0", "Sorry it was my mistake, I missed up the directories, it works now. Not sure why you got that error. I have the same version of `rarfile`. Between, there were some suggestions to change the dataset from `1bn_words_arabic` to `arabic_billion_words` like https://github.com/huggingface/datasets/tree/master/datasets/spanish_billion_words. \r\n", "I'm ok with renaming the dataset `arabic_billion_words` if you want.\r\nNote that you will need to rename class name `ArabicBillionWords` instead of `BillionWords`\r\n(though `BillionWords` was not matching `1bn_words_arabic` anyway)\r\n\r\nYou will need to regenerate the dataset_infos.json file after this change.\r\nOR alternatively just replace all mentions of `billion_words` with `arabic_billion_words` in dataset_infos.json <- this trick should save you some time :)", "Hmmm I'm still not able to run it on my side because of the rar error (I'm running macos)\r\nI just tried with rarfile 3.1 and it didn't work either.\r\nI would like to be able to run it end-to-end on my side before merging if you don't mind. Let me investigate this issue a little bit", "No worries, I will investigate it as well. ", "I created a minimal example in [colab ](https://colab.research.google.com/drive/11ijesuGbrQylANka0VdsZ5vXwIuxkheY?usp=sharing).", "Nice thanks, maybe it's just an issue on my side then", "Ok I managed to solve the BadRarFile issue on my side :) \r\nTo fix it I had to install the `unrar` tool for macos (though it seems it's not available with `brew install` anymore, I had to install it from elsewhere)." ]
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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 wordsim353
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Add twi WordSim 353
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