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Real data tests are failing as this dataset needs to be manually downloaded
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Add Species-800
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[ "thanks @lhoestq ! I probably need to do the same change in the `SplitGenerator`s (lines 107, 110 and 113). I'll open a new PR for that", "Yes indeed ! Good catch 👍 \r\nFeel free to open a PR and ping me", "Hi , theres a issue pulling species_800 dataset , throws google drive error \r\n\r\nerror: \r\n\r\n```\r\nraise ConnectionError(f\"Couldn't reach {url} ({repr(head_error)})\")\r\nConnectionError: Couldn't reach https://drive.google.com/u/0/uc?id=1OletxmPYNkz2ltOr9pyT0b0iBtUWxslh&export=download/ (ReadTimeout(ReadTimeoutError(\"HTTPSConnectionPool(host='drive.google.com', port=443): Read timed out. (read timeout=10)\")))\r\n```\r\ncode: \r\n```\r\nfrom datasets import load_dataset\r\n\r\ndataset = load_dataset(\"species_800\")\r\n```", "Hi @obonyojimmy! I am running the same commands and they work for me. Did you check your internet connection?" ]
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Add JFLEG
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[ "Hi @j-chim ! You're right it does feel redundant: your option works better, but I'd even suggest having the references in a Sequence feature, which you can declare as:\r\n```\r\n\t features=datasets.Features(\r\n {\r\n \"sentence\": datasets.Value(\"string\"),\r\n \"corrections\": datasets.Sequence(datasets.Value(\"string\")),\r\n }\r\n ),\r\n```\r\n\r\nTo create the dummy data, you just need to tell the generator which files it should use, which you can do with:\r\n`python datasets-cli dummy_data datasets/<your-dataset-folder> --auto_generate --match_text_files \"train*,dev*,test*\"`\r\n", "Many thanks for this @yjernite! I've incorporated your feedback and sorted out the dummy data." ]
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This PR adds [JFLEG ](https://www.aclweb.org/anthology/E17-2037/), an English grammatical error correction benchmark. The tests were successful on real data, although it would be great if I can get some guidance on the **dummy data**. Basically, **for each source sentence there are 4 possible gold standard target sentences**. The original dataset comprise files in a flat structure, labelled by split then by source/target (e.g., dev.src, dev.ref0, ..., dev.ref3). Not sure what is the best way of adding this. I imagine I can treat each distinct source-target pair as its own split? But having so many copies of the source sentence feels redundant, and it would make it less convenient to end-users who might want to access multiple gold standard targets simultaneously.
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Add the Winograd Schema Challenge
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Adds the Winograd Schema Challenge, including configs for the more canonical wsc273 as well as wsc285 with 12 new examples. - https://cs.nyu.edu/faculty/davise/papers/WinogradSchemas/WS.html The data format was a bit of a nightmare but I think I got it to a workable format.
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Fix PerSenT
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New PR for dataset PerSenT
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Add GitHub version of ETH Py150 Corpus
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[ "The `RemoteDatasetTest` is fixed on master so it's fine", "thanks for rebasing :)\r\n\r\nCI is green now, merging" ]
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Add the redistributable version of **ETH Py150 Corpus**
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Add Urdu Sentiment Corpus (USC).
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[ "@lhoestq have made the suggested changes in the README file.", "@lhoestq Created a new PR #1231 with only the relevant files.\r\nclosing this one :)" ]
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Added Urdu Sentiment Corpus. More details about the dataset over <a href="https://github.com/MuhammadYaseenKhan/Urdu-Sentiment-Corpus">here</a>.
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Add ReFreSD dataset
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[ "Cool dataset! Replying in-line:\r\n\r\n> This PR adds the **ReFreSD dataset**.\r\n> The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data.\r\n> \r\n> Need feedback on:\r\n> \r\n> * I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work.\r\n\r\nyou can use `--match_text_files` in the dummy data generation:\r\n`python datasets-cli dummy_data datasets/refresd --auto_generate --match_text_files \"REFreSD_rationale\"`\r\n\r\n> * The feature names.\r\n> \r\n> * I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit.\r\n\r\nIt would actually be even better to use the `Translation` feature here to replace best:\r\n`\"sentence_pair\": datasets.Translation(languages=['en', 'fr']),`\r\n\r\nThen during `_generate_examples` this filed should look like\"\r\n`{\"sentence_pair\": {\"fr\": french, \"en\": english}}`\r\n\r\n> * There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better.\r\nLooks good!\r\n\r\n> * The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple.\r\n\r\nHaving the feature declared as `\"rationale_en\": datasets.Sequence(datasets.Value(\"int32\"))` should work\r\n\r\n> \r\n> Thanks in advance\r\n\r\nHope that helps you out! Don't forget to `make style`, rebase from master, and run all the tests before pushing again! You will also need to add a `README.md` as described in the guide:\r\nhttps://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card", "Thanks a lot for the answer, that does help a lot !\r\nI opened a PR for a License in the original repo so I was waiting for that for the model card. If there is no news on Monday, I'll add it without License. ", "Looks good! It looks like it might need a rebase to pass the tests. Once you do that, should be good to go!" ]
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This PR adds the **ReFreSD dataset**. The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data. Need feedback on: - I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work. - The feature names. - I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit. - There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better. - The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple. Thanks in advance
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updated after the class name update
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@lhoestq <---
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add wmt mlqe 2020 shared task
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[ "re-created in #1218 because this was too messy" ]
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First commit for Shared task 1 (wmt_mlqw_task1) of WMT20 MLQE (quality estimation of machine translation) Note that I copied the tags in the README for only one (of the 7 configurations): `en-de`. There is one configuration for each pair of languages.
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minor change in description in paws-x.py and updated dataset_infos
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added paws
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Updating README and tags for dataset card in a while
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adding xquad-r dataset
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Adding XQUAD-R Dataset
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Add Urdu Sentiment Corpus (USC).
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Added Urdu Sentiment Corpus. More details about the dataset over <a href="https://github.com/MuhammadYaseenKhan/Urdu-Sentiment-Corpus">here</a>.
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adding discovery
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[ "merging since the CI is fixed on master" ]
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Adding initial version of cord-19 dataset
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[ "Hi @ggdupont !\r\nHave you had a chance to take a look at my suggestions ?\r\nFeel free to ping me if you have questions or when you're ready for a review", "> Hi @ggdupont !\r\n> Have you had a chance to take a look at my suggestions ?\r\n> Feel free to ping me if you have questions or when you're ready for a review\r\n\r\nYes I did, just busy period (and no time on weekend right now ;-) )", "With some delay, reduced the dummy data and had t rebase", "Thanks !\r\n\r\nIt looks like the rebase messed up the github diff for this PR (2.000+ files changed)\r\nCould you create another branch and another PR please ?", "Cleaned PR: https://github.com/huggingface/datasets/pull/1850" ]
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Initial version only reading the metadata in CSV. ### Checklist: - [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 and at least fill the tags - [x] Both tests for the real data and the dummy data pass. ### TODO: - [x] add more metadata - [x] add full text - [x] add pre-computed document embedding
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Add xquad-r dataset
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Add wikiqaar dataset
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Arabic Wiki Question Answering Corpus.
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Adding babi dataset
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[ "This is ok now @lhoestq\r\n\r\nI've included the tweak to `dummy_data` to only use the data transmitted to `_generate_examples` by default (it only do that if it can find at least one path to an existing file in the `gen_kwargs` and this can be unactivated with a flag).\r\n\r\nShould I extract it in another PR or is it ok like this?", "Nice !\r\nCould you add the dummy data generation trick in another PR ?\r\nI think we can also extend it to make it work not only with data files paths but also with data directories (sometimes it's one of the parent directory that is passed to gen_kwargs, not the actual path to the file).\r\nThis will help a lot to make the dummy data lighter !", "This PR can be closed due to #2053 @lhoestq\r\n\r\n" ]
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Adding the English version of bAbI. Samples are taken from ParlAI for consistency with the main users at the moment. Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed).
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Add Urdu fake news dataset.
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[ "@lhoestq looks like a lot of files were updated... shall I create a new PR?", "Hi @chaitnayabasava ! you can try rebasing and see if that fixes the number of files changed, otherwise please do open a new PR with only the relevant files and close this one :) ", "Created a new PR #1230.\r\nclosing this one :)" ]
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Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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Add Xitsonga Ner
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[ "looks like this PR includes changes about many files other than the ones related to xitsonga NER\r\n\r\ncould you create another branch and another PR please ?" ]
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Clean Xitsonga Ner PR
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adding cdt dataset
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[ "the `ms_terms` formatting CI fails is fixed on master", "merging since the CI is fixed on master" ]
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Add Urdu fake news.
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Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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adding cdt dataset
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Add conda environment activation
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Added activation of Conda environment before installing.
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Add Google Great Code Dataset
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Add Tashkeela dataset
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[ "Sorry @lhoestq for the trouble, sometime I forget to change the names :/", "> Sorry @lhoestq for the trouble, sometime I forget to change the names :/\r\n\r\nhaha it's ok ;)" ]
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Arabic Vocalized Words Dataset.
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Fix incorrect MRQA train+SQuAD URL
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[ "Thanks ! could you regenerate the dataset_infos.json file ?\r\n\r\n```\r\ndatasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\nalso cc @VictorSanh ", "Oooops, good catch @jimmycode ", "> Thanks ! could you regenerate the dataset_infos.json file ?\r\n> \r\n> ```\r\n> datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications\r\n> ```\r\n> \r\n> also cc @VictorSanh\r\n\r\nUpdated the `dataset_infos.json` file." ]
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Fix issue #1115
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add dbpedia_14 dataset
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[ "Thanks for the review. \r\nCheers!", "Hi @hfawaz, this week we are doing the 🤗 `datasets` sprint (see some details [here](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)).\r\n\r\nNothing more to do on your side but it means that if you register on the thread I linked above, you can have some goodies for the present dataset that you have already added (and a special goodie if you want to spend more time and add 2 other datasets as well).\r\n\r\nIf you want to join, just tell me (or post on the thread on the HuggingFace forum: https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)", "Hello @thomwolf \r\nThanks for the feedback and for this invitation, indeed I would be glad to join you guys (you can add me). \r\nI will see if I have the time to implement a couple of datasets. \r\nCheers! ", "@hfawaz invited you to the slack with your uha email.\r\n\r\nCheck your spam folder if you can't find the invitation :)", "Oh thanks, but can you invite me on my gmail: [email protected] \r\nUHA is my old organization, I haven't had the time to update my online profiles yet.\r\nThank you " ]
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This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
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Incorrect URL for MRQA SQuAD train subset
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[ "good catch !" ]
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https://github.com/huggingface/datasets/blob/4ef4c8f8b7a60e35c6fa21115fca9faae91c9f74/datasets/mrqa/mrqa.py#L53 The URL for `train+SQuAD` subset of MRQA points to the dev set instead of train set. It should be `https://s3.us-east-2.amazonaws.com/mrqa/release/v2/train/SQuAD.jsonl.gz`.
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Add sesotho ner corpus
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Clean Sesotho PR
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add qed
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adding QED: Dataset for Explanations in Question Answering https://github.com/google-research-datasets/QED https://arxiv.org/abs/2009.06354
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Initial version of cord-19 dataset from AllenAI with only the abstract
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[ "too ugly, I'll make a clean one" ]
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Initial version only reading the metadata in CSV. ### Checklist: - [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 and at least fill the tags - [ ] Both tests for the real data and the dummy data pass. ### TODO: - [ ] add more metadata - [ ] add full text - [ ] add pre-computed document embedding
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Add Siswati Ner corpus
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Clean Siswati PR
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Using a feature named "_type" fails with certain operations
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[ "Thanks for reporting !\r\n\r\nIndeed this is a keyword in the library that is used to encode/decode features to a python dictionary that we can save/load to json.\r\nWe can probably change `_type` to something that is less likely to collide with user feature names.\r\nIn this case we would want something backward compatible though.\r\n\r\nFeel free to try a fix and open a PR, and to ping me if I can help :) " ]
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A column named `_type` leads to a `TypeError: unhashable type: 'dict'` for certain operations: ```python from datasets import Dataset, concatenate_datasets ds = Dataset.from_dict({"_type": ["whatever"]}).map() concatenate_datasets([ds]) # or simply Dataset(ds._data) ``` Context: We are using datasets to persist data coming from elasticsearch to feed to our pipeline, and elasticsearch has a `_type` field, hence the strange name of the column. Not sure if you wish to support this specific column name, but if you do i would be happy to try a fix and provide a PR. I already had a look into it and i think the culprit is the `datasets.features.generate_from_dict` function. It uses the hard coded `_type` string to figure out if it reached the end of the nested feature object from a serialized dict. Best wishes and keep up the awesome work!
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add woz_dialogue
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Adding Wizard-of-Oz task oriented dialogue dataset https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz https://arxiv.org/abs/1604.04562
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Add Sepedi NER corpus
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Finally a clean PR for Sepedi
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Add arsentd_lev dataset
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[ "thanks ! can you also regenerate the dataset_infos.json file please ?" ]
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Add The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV) Paper: [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://arxiv.org/abs/1906.01830) Homepage: http://oma-project.com/
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Add Urdu fake news
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Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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add xquad_r dataset
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[ "looks like this PR includes changes in many files than the ones for xquad_r, could you create a new branch and a new PR ?", "Sure, I will close this then.\r\n" ]
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add TLC
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Added TLC dataset
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Add support to download kaggle datasets
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[ "Hey, I think this is great idea. Any plan to integrate kaggle private datasets loading to `datasets`?" ]
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We can use API key
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Add retries to download manager
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Add Wikicorpus dataset
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[ "@lhoestq done! ;)" ]
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Add dataset.
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Urdu fake news
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Added Bend the Truth urdu fake news dataset. More inforation <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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Adds a brand new table to text dataset: https://github.com/google-research-datasets/ToTTo
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Add MSRA NER labels
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Fixes #940
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FIX matinf link in ADD_NEW_DATASET.md
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Add TupleInf Open IE Dataset
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[ "Errors are in the CI are not related to this PR (RemoteDatasetError)\r\nthe CI is fixed on master so it's fine ", "@lhoestq Added the dataset card. Please let me know if more information needs to be added." ]
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For more information: https://allenai.org/data/tuple-ie
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add urdu fake news dataset
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Added Urdu fake news dataset. The dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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Add NCBI Disease Corpus dataset
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Add Coached Conversation Preference Dataset
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Adding [Coached Conversation Preference Dataset](https://research.google/tools/datasets/coached-conversational-preference-elicitation/)
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Add Google wellformed query dataset
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This pull request will add Google wellformed_query dataset. Link of dataset is https://github.com/google-research-datasets/query-wellformedness
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add thaisum
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ThaiSum, a large-scale corpus for Thai text summarization obtained from several online news websites namely Thairath, ThaiPBS, Prachathai, and The Standard. This dataset consists of over 350,000 article and summary pairs written by journalists. We evaluate the performance of various existing summarization models on ThaiSum dataset and analyse the characteristic of the dataset to present its difficulties.
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add sharc_modified
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Adding modified ShARC dataset https://github.com/nikhilweee/neural-conv-qa
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add xquad_r dataset
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Add Big Patent dataset
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[ "@lhoestq reduced the dummy data size to around 19MB in total and added the dataset card.", "@lhoestq so I ended up removing all the nested JSON objects in the gz datafile and keep only one object with minimal content: `{\"publication_number\": \"US-8230922-B2\", \"abstract\": \"dummy abstract\", \"application_number\": \"US-201113163519-A\", \"description\": \"dummy description\"}`. \r\n\r\nThey're reduced to 35KB in total (2.5KB per domain and 17.5KB for all domains), hopefully, they're small enough." ]
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* More info on the dataset: https://evasharma.github.io/bigpatent/ * There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
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adding cdt dataset
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[ "> Thanks for adding this one !\r\n> \r\n> I left a few comments\r\n> \r\n> after the change you'll need to regenerate the dataset_infos.json file as well\r\n\r\ndataset_infos.json regenerated", "looks like this PR includes changes to many files other that the ones for CDT\r\ncould you create another branch and another PR please ?" ]
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- **Name:** *Cyberbullying Detection Task* - **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.* - **Data:** *https://github.com/ptaszynski/cyberbullying-Polish* - **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
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add mutual friends conversational dataset
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Mutual friends dataset WIP TODO: - scenario_kbs (bug with pyarrow conversion) - download from codalab checksums bug
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adding cdsc dataset
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- **Name**: *cdsc (domains: cdsc-e & cdsc-r)* - **Description**: *Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish. The dataset was presented at ACL 2017. Please refer to the Wróblewska and Krasnowska-Kieraś (2017) for a detailed description of the resource.* - **Data**: *http://2019.poleval.pl/index.php/tasks/* - **Motivation**: *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
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Add the multilingual Exams dataset
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[ "Will slim down the dummy files in the morning" ]
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https://github.com/mhardalov/exams-qa `multilingual` configs have all languages mixed together `crosslingual` mixes the languages for test but separates them for train and dec, so I've made one config per language for train/dev data and one config with the joint test set
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Add news topic classification dataset in Myanmar / Burmese languagess This data was collected in 2017 by Aye Hninn Khine , and published on GitHub with a GPL license https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem
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Add Knowledge-Enhanced Language Model Pre-training (KELM)
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Adds the KELM dataset. - Webpage/repo: https://github.com/google-research-datasets/KELM-corpus - Paper: https://arxiv.org/pdf/2010.12688.pdf
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Add WikiANN NER dataset
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This PR adds the full set of 176 languages from the balanced train/dev/test splits of WikiANN / PAN-X from: https://github.com/afshinrahimi/mmner Until now, only 40 of these languages were available in `datasets` as part of the XTREME benchmark Courtesy of the dataset author, we can now download this dataset from a Dropbox URL without needing a manual download anymore 🥳, so at some point it would be worth updating the PAN-X subset of XTREME as well 😄 Link to gist with some snippets for producing dummy data: https://gist.github.com/lewtun/5b93294ab6dbcf59d1493dbe2cfd6bb9 P.S. @yjernite I think I was confused about needing to generate a set of YAML tags per config, so ended up just adding a single one in the README.
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- **Name:** *nkjp-ner* - **Description:** *The NKJP-NER is based on a human-annotated part of NKJP. We extracted sentences with named entities of exactly one type. The task is to predict the type of the named entity.* - **Data:** *https://klejbenchmark.com/tasks/* - **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
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add AJGT dataset
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Arabic Jordanian General Tweets.
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Added glucose dataset
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This PR adds the [Glucose](https://github.com/ElementalCognition/glucose) dataset.
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quac quac / coin coin
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Add QUAC (Question Answering in Context) I linearized most of the dictionnaries to lists. Referenced to the authors' datasheet for the dataset card. 🦆🦆🦆 Coin coin
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adding cleaned verion of E2E NLG
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Found at: https://github.com/tuetschek/e2e-cleaning
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Swedish MT STS-B
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Added a Swedish machine translated version of the well known STS-B Corpus
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Add DialogRE dataset
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Adding the [DialogRE](https://github.com/nlpdata/dialogre) dataset Version 2. - All tests passed successfully.
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actually uses the previously declared VERSION on the configs in the template
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add xlrd to test package requirements
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Adds `xlrd` package to the test requirements to handle scripts that use `pandas` to load excel files
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add conv_ai
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[ "This one will make @thomwolf reminisce ;)", "Merging." ]
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Adding ConvAI dataset https://github.com/DeepPavlov/convai/tree/master/2017
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Test
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Add Pubmed (citation + abstract) dataset (2020).
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[ "LGTM! ftp addition looks fine but maybe have a look @thomwolf ?", "It's not finished yet, I need to run the tests on the full dataset (it was running this weekend, there is an error somewhere deep)\r\n", "@yjernite Ready for review !\r\n@thomwolf \r\n\r\nSo I tried to follow closely the original format that means I still had to drop information (namely tags on elements are simply discarded for now but they don't seem to carry critical information).\r\nSome elements are also discarded they tend to not come up often:\r\n - The most notable is Author affiliation, which seems to be all over the place in terms of what it look meaning it's hard to actually get a consistent format.\r\n - Journal is the same, all the elements in there can be wildly different so I decided to drop it for now instead of trying to figure out a way to have a common presentation. (the DOI and medline ID are present so it can be recovered).\r\n\r\nI think this PR could go as it but we probably should add a way to get easier information to use with a config.\r\nFor instance `{\"title\": \"string\", \"abstract\": \"string\", \"authors\": List[str], \"substances\": List[str]}` maybe ? (substances for instance is a tricky one, some substances only have an international identifier, some have simply a common name, some both)\r\n\r\nIt's relatively easy to do I think it's mostly discarding other fields and renaming some deep structure into a flat one.", "Look ok to me but @lhoestq is the master on the Download Manager side" ]
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add xquad-r dataset
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Add ChrEn
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[ "I just saw your PR actually ^^", "> I just saw your PR actually ^^\r\n\r\nSomehow that still doesn't work, lmk if you have any ideas.", "Did you rebase from master ?" ]
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Adding the Cherokee English machine translation dataset of https://github.com/ZhangShiyue/ChrEn
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add xquad-r dataset
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Not support links with 302 redirect
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[ "Hi !\r\nThis kind of links is now supported by the library since #1316", "> Hi !\r\n> This kind of links is now supported by the library since #1316\r\n\r\nI updated links in TLC datasets to be the github links in this pull request \r\n https://github.com/huggingface/datasets/pull/1737\r\n\r\nEverything works now. Thank you." ]
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I have an issue adding this download link https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz it might be because it is not a direct link (it returns 302 and redirects to aws that returns 403 for head requests). ``` r.head("https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz", allow_redirects=True) # <Response [403]> ```
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Add the Ud treebank
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[ "merging since the CI is fixed on master" ]
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This PR adds the 183 datasets in 104 languages of the UD Treebank.
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Add KorNLU dataset
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[ "Nice thank you !\r\nCan you regenerate the dataset_infos.json file ? Since we changed the features we must update it\r\n\r\nThen I think we'll be good to merge :)" ]
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Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289) **Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq - [x] Followed the instructions in CONTRIBUTING.md - [x] Ran the tests successfully - [x] Created the dummy data
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add labr dataset
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Arabic Book Reviews dataset.
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Fix squad V2 metric script
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[ "The script with changes is used and tested in [#8924](https://github.com/huggingface/transformers/pull/8924). It gives the same results as the old `evaluate_squad` function when used on the same predictions.", "merging since the CI is fixed on master" ]
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The current squad v2 metric doesn't work with the squad (v1 or v2) datasets. The script is copied from `squad_evaluate` in transformers that requires the labels (with multiple answers) to be like this: ``` references = [{'id': 'a', 'answers': [ {'text': 'Denver Broncos', 'answer_start': 177}, {'text': 'Denver Broncos', 'answer_start': 177} ]}] ``` while the dataset had references like this: ``` references = [{'id': 'a', 'answers': {'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]} }] ``` Using one or the other format fails with the current squad v2 metric: ``` from datasets import load_metric metric = load_metric("squad_v2") predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}] references = [{'id': 'a', 'answers': [ {'text': 'Denver Broncos', 'answer_start': 177}, {'text': 'Denver Broncos', 'answer_start': 177} ]}] metric.compute(predictions=predictions, references=references) ``` fails as well as ``` from datasets import load_metric metric = load_metric("squad_v2") predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}] references = [{'id': 'a', 'answers': {'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]} }] metric.compute(predictions=predictions, references=references) ``` This is because arrow reformats the references behind the scene. With this PR (tested locally), both the snippets up there work and return proper results.
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Add TLC
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[ "I have reduced the size of the dummy file and added README sections as you suggested. ", "I have a little issue to run the test. It seems there is no failed case in my machine. ", "Thanks !\r\nIt looks like the PR includes changes to many other files than the ones of `tlc`, can you create another branch and another PR ?" ]
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Added TLC dataset
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Added paws-x dataset. Updating README and tags in the dataset card in a while
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Adding TamilMixSentiment
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[ "looks like this pr incldues changes about many other files than the ones for tamilMixSentiment, could you create another branch and another PR ?" ]
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Add deal_or_no_dialog
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Add deal_or_no_dialog Dataset github: https://github.com/facebookresearch/end-to-end-negotiator Paper: [Deal or No Deal? End-to-End Learning for Negotiation Dialogues](https://arxiv.org/abs/1706.05125)
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Add hebrew-sentiment
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[ "@elronbandel it looks like something went wrong with the renaming, as the old files are still in the PR. Can you `git rm datasets/hebrew-sentiment` ?", "merging since the CI is fixed on master", "This is the old version of the data.\r\nHere is the fixed version.\r\nhttps://github.com/OnlpLab/Hebrew-Sentiment-Data\r\n\r\nI hope I would find time to open a PR. I think it supposed to be only to change the data path ", "Cool ! Sure feel free to open a PR if you have some time :) and feel free to ping me for review or if you have questions" ]
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hebrew-sentiment dataset is ready! (including tests, tags etc)
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Add dataset - SemEval 2014 - Task 1
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[ "Added the dataset card.\r\nRequesting another review." ]
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Adding the dataset of SemEval 2014 Task 1 Found the dataset under the shared Google Sheet > Recurring Task Datasets Task Homepage - https://alt.qcri.org/semeval2014/task1 Thank you!
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Fix dataset URL and file names, and add column name in "Social Bias Frames" dataset
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[ "Thanks a lot, looks good!" ]
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# Why I did When I use "social_bias_frames" datasets in this library, I got 404 Errors. So, I fixed this error and another some problems that I faced to use the dataset. # What I did * Modify this dataset URL * Modify this dataset file names * Add a "dataSource" column Thank you!
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add sharc dataset
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This PR adds the ShARC dataset. More info: https://sharc-data.github.io/index.html
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Add Facebook SimpleQuestionV2
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[ "I think @thomwolf may also be working on this one as part of the Babi benchmark in #945 " ]
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Add simple questions v2: https://research.fb.com/downloads/babi/
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Add GoEmotions
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[ "Whoops, didn't mean for that to be merged yet (my bad). I'm reaching out to the authors since we'd like their feedback on the best way to have the `author` field anonymized or removed. Will send a patch once they get back to me." ]
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Adds the GoEmotions dataset, a nice emotion classification dataset with 27 (multi-)label annotations on reddit comments. Includes both a large raw version and a narrowed version with predefined train/test/val splits, which I've included as separate configs with the latter as a default. - Webpage/repo: https://github.com/google-research/google-research/tree/master/goemotions - Paper: https://arxiv.org/abs/2005.00547
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