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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 hrenwac_para
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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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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 πŸ€— ", "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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[ "merging since the CI is fixed on master" ]
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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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Hebrew project BenYehuda
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[ "merging since the CI is fixed on master" ]
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Added Hebrew corpus from https://github.com/projectbenyehuda/public_domain_dump
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init commit for MultiReQA for third PR with all issues fixed
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[ "good dataset card as well :) ", "@lhoestq Thank you :) " ]
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3rd PR w.r.t. PR #1349 with all the issues fixed. As #1349 had uploaded other files along with the multi_re_qa dataset
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Add german common crawl dataset
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[ "Hi @Phil1108 !\r\nHave you had a chance to take a look at my suggestions ?\r\nFeel free to ping me if you have questions or if you're ready for a review\r\n\r\nThanks again for adding this dataset, this one is very useful !", "> \r\n> \r\n> Hi @Phil1108 !\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 if you're ready for a review\r\n> \r\n> Thanks again for adding this dataset, this one is very useful !\r\n\r\nHello @lhoestq , \r\n\r\nokay so should we go on with only the 2 parts or wait until the hosting of all 200 GB is cleared at HF? \r\nIf you want to merge it with the 2 parts only at first und upgrade later to all, sure I'll include the minor changes in the next few days and update it here", "I think we can wait a bit to find a solution for the hosting and update the PR to include all the files when it's done.\r\nIn the meantime you can update the PR to take into account the suggestions regarding the dataset card, the parallel downloads and the use of eval.\r\n\r\nA safer alternative to eval is `ast.literal_eval`, it should do the job" ]
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Adding a subpart of the Common Crawl which was extracted with this repo https://github.com/facebookresearch/cc_net and additionally filtered for duplicates
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Add yoruba wordsim353
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Added WordSim-353 evaluation dataset for Yoruba
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Imppres
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[ "Feel free to ping me once you're ready for another review :) ", "For sure! Gonna work on this now!", "I incorporated all the changes but when I go to rebase I get the following error:\r\n```python\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git rebase upstream/master\r\nerror: cannot rebase: You have unstaged changes.\r\nerror: Please commit or stash them.\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git stash\r\nSaved working directory and index state WIP on imppres: 51736236 Incorporated secondary sets as configurations instead of splits.\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git rebase upstream/master\r\nCONFLICT (add/add): Merge conflict in datasets/wiki_movies/wiki_movies.py\r\nAuto-merging datasets/wiki_movies/wiki_movies.py\r\nCONFLICT (add/add): Merge conflict in datasets/wiki_movies/dataset_infos.json\r\nAuto-merging datasets/wiki_movies/dataset_infos.json\r\nCONFLICT (add/add): Merge conflict in datasets/wiki_movies/README.md\r\nAuto-merging datasets/wiki_movies/README.md\r\nerror: could not apply 04d08587... Created wiki_movies dataset.\r\nResolve all conflicts manually, mark them as resolved with\r\n\"git add/rm <conflicted_files>\", then run \"git rebase --continue\".\r\nYou can instead skip this commit: run \"git rebase --skip\".\r\nTo abort and get back to the state before \"git rebase\", run \"git rebase --abort\".\r\nCould not apply 04d08587... Created wiki_movies dataset.\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git branch\r\n* (no branch, rebasing imppres)\r\n imppres\r\n logiqa_en\r\n master\r\n wiki_movies\r\n wiki_movies_htl\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git checkout imppres \r\ndatasets/wiki_movies/README.md: needs merge\r\ndatasets/wiki_movies/dataset_infos.json: needs merge\r\ndatasets/wiki_movies/wiki_movies.py: needs merge\r\nerror: you need to resolve your current index first\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ \r\n```", "I think it's because the current branch includes changes about wiki_movies.\r\n\r\nCan you create a new branch from `master` and create another PR please ?", "I get this response when I try to switch to master:\r\n```\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git checkout master\r\ndatasets/wiki_movies/README.md: needs merge\r\ndatasets/wiki_movies/dataset_infos.json: needs merge\r\ndatasets/wiki_movies/wiki_movies.py: needs merge\r\nerror: you need to resolve your current index first\r\n```", "Maybe you have to remove the changes in wiki_movies before checkout to master\r\n```\r\ngit stash\r\n```\r\n\r\nshould do the job", "Here is what I get:\r\n```\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git stash\r\ndatasets/wiki_movies/README.md: needs merge\r\ndatasets/wiki_movies/dataset_infos.json: needs merge\r\ndatasets/wiki_movies/wiki_movies.py: needs merge\r\n```", "Ok I see\r\nLooks like you're in a `merge` process.\r\nYou can abort it with `git reset --merge`\r\n\r\nThen `git checkout master` should work", "So close! I got the new branch made and went through all the tests. When I went to push, I got the following:\r\n```\r\naclifton@pop-os:~/hf_datasets_sprint/datasets$ git push -u origin imppres\r\nUsername for 'https://github.com': aclifton314\r\nPassword for 'https://aclifton314@github.com': \r\nTo https://github.com/aclifton314/datasets\r\n ! [rejected] imppres -> imppres (non-fast-forward)\r\nerror: failed to push some refs to 'https://github.com/aclifton314/datasets'\r\nhint: Updates were rejected because the tip of your current branch is behind\r\nhint: its remote counterpart. Integrate the remote changes (e.g.\r\nhint: 'git pull ...') before pushing again.\r\nhint: See the 'Note about fast-forwards' in 'git push --help' for details.\r\n```", "after a rebase you need to `git push --force`", "Done!" ]
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2nd PR ever! Hopefully I'm starting to get the hang of this. This is for the IMPPRES dataset. Please let me know of any corrections or changes that need to be made.
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Can't map dataset (loaded from csv)
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[ "Please could you post the whole script? I can't reproduce your issue. After updating the feature names/labels to match with the data, everything works fine for me. Try to update datasets/transformers to the newest version.", "Actually, the problem was how `tokenize` function was defined. This was completely my side mistake, so there are really no needs in this issue anymore" ]
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Hello! I am trying to load single csv file with two columns: ('label': str, 'text' str), where is label is str of two possible classes. Below steps are similar with [this notebook](https://colab.research.google.com/drive/1-JIJlao4dI-Ilww_NnTc0rxtp-ymgDgM?usp=sharing), where bert model and tokenizer are used to classify lmdb loaded dataset. Only one difference it is the dataset loaded from .csv file. Here is how I load it: ```python data_path = 'data.csv' data = pd.read_csv(data_path) # process class name to indices classes = ['neg', 'pos'] class_to_idx = { cl: i for i, cl in enumerate(classes) } # now data is like {'label': int, 'text' str} data['label'] = data['label'].apply(lambda x: class_to_idx[x]) # load dataset and map it with defined `tokenize` function features = Features({ target: ClassLabel(num_classes=2, names=['neg', 'pos'], names_file=None, id=None), feature: Value(dtype='string', id=None), }) dataset = Dataset.from_pandas(data, features=features) dataset.map(tokenize, batched=True, batch_size=len(dataset)) ``` It ruins on the last line with following error: ``` --------------------------------------------------------------------------- AssertionError Traceback (most recent call last) <ipython-input-112-32b6275ce418> in <module>() 9 }) 10 dataset = Dataset.from_pandas(data, features=features) ---> 11 dataset.map(tokenizer, batched=True, batch_size=len(dataset)) 2 frames /usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in map(self, function, with_indices, input_columns, batched, batch_size, drop_last_batch, remove_columns, keep_in_memory, load_from_cache_file, cache_file_name, writer_batch_size, features, disable_nullable, fn_kwargs, num_proc, suffix_template, new_fingerprint) 1237 test_inputs = self[:2] if batched else self[0] 1238 test_indices = [0, 1] if batched else 0 -> 1239 update_data = does_function_return_dict(test_inputs, test_indices) 1240 logger.info("Testing finished, running the mapping function on the dataset") 1241 /usr/local/lib/python3.6/dist-packages/datasets/arrow_dataset.py in does_function_return_dict(inputs, indices) 1208 fn_args = [inputs] if input_columns is None else [inputs[col] for col in input_columns] 1209 processed_inputs = ( -> 1210 function(*fn_args, indices, **fn_kwargs) if with_indices else function(*fn_args, **fn_kwargs) 1211 ) 1212 does_return_dict = isinstance(processed_inputs, Mapping) /usr/local/lib/python3.6/dist-packages/transformers/tokenization_utils_base.py in __call__(self, text, text_pair, add_special_tokens, padding, truncation, max_length, stride, is_split_into_words, pad_to_multiple_of, return_tensors, return_token_type_ids, return_attention_mask, return_overflowing_tokens, return_special_tokens_mask, return_offsets_mapping, return_length, verbose, **kwargs) 2281 ) 2282 ), ( -> 2283 "text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) " 2284 "or `List[List[str]]` (batch of pretokenized examples)." 2285 ) AssertionError: text input must of type `str` (single example), `List[str]` (batch or single pretokenized example) or `List[List[str]]` (batch of pretokenized examples). ``` which I think is not expected. I also tried the same steps using `Dataset.from_csv` which resulted in the same error. For reproducing this, I used [this dataset from kaggle](https://www.kaggle.com/team-ai/spam-text-message-classification)
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adding fake-news-english-2
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Contains loading script as well as dataset card including YAML tags.
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Add Turkish News Category Dataset (270K)
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[ "@lhoestq, can you please review this PR?\r\n", "@SBrandeis,\r\nSorry. All of the latest version came to my branch. You can find final version. \r\nResubmitted as a clean final version of #1466\r\nI have completed all the review comments.", "Closing this as PR is now https://github.com/huggingface/datasets/pull/1466" ]
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This PR adds the Turkish News Categories Dataset (270K) dataset which is a text classification dataset by me and @yavuzKomecoglu. Turkish news dataset consisting of **273601 news** in **17 categories**, compiled from printed media and news websites between 2010 and 2017 by the [Interpress](https://www.interpress.com/) media monitoring company.
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Add arabic dialects
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Data loading script and dataset card for Dialectal Arabic Resources dataset. Fixed git issues from PR #976
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WIP: Vinay/add peer read dataset
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Add Shrinked Turkish NER from Kaggle.
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Add Shrinked Turkish NER from [Kaggle](https://www.kaggle.com/behcetsenturk/shrinked-twnertc-turkish-ner-data-by-kuzgunlar).
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Add Hate Speech and Offensive Language Detection dataset
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[ "@lhoestq done! The failing testes don't seem to be related, it seems to be a connection issue, if I understand it correctly.", "@lhoestq done!", "merging since the CI is fixed on master" ]
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Add [Hate Speech and Offensive Language Detection dataset](https://github.com/t-davidson/hate-speech-and-offensive-language) from [this paper](https://arxiv.org/abs/1703.04009).
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Adding BioCreative II Gene Mention corpus
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Adding BioCreative II Gene Mention corpus
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Add OffComBR
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[ "Hello @hugoabonizio, thanks for the contribution.\r\nRegarding the fake data, you can generate it manually.\r\nRunning the `python datasets-cli dummy_data datasets/offcombr` should give you instructions on how to manually create the dummy data.\r\nFor reference, here is a spec for `.arff` files : https://www.cs.waikato.ac.nz/ml/weka/arff.html", "@lhoestq again the failing tests doesn't seem to be related", "merging since the CI is fixed on master" ]
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Add [OffComBR](https://github.com/rogersdepelle/OffComBR) from [Offensive Comments in the Brazilian Web: a dataset and baseline results](https://sol.sbc.org.br/index.php/brasnam/article/view/3260/3222) paper. But I'm having a hard time generating dummy data since the original dataset extion is `.arff` and the [_create_dummy_data function](https://github.com/huggingface/datasets/blob/a4aeaf911240057286a01bff1b1d75a89aedd57b/src/datasets/commands/dummy_data.py#L185) doesn't allow it.
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Adding the ASSIN dataset
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Adding the ASSIN dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring
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2 typos
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Corrected 2 typos
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Add penn treebank dataset
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[ "@yjernite I have updated the PR to be language modeling task specific. Please review!\r\n", "Yes a line corresponds to a sentence in this data." ]
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Adding the ASSIN dataset
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[ "I wrongly commited data from another branch in this PR, I'll close this a reopen another PR with the fixed branch" ]
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Adding the ASSIN dataset, a Portuguese language dataset for Natural Language Inference and Semantic Similarity Scoring
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adding fake-news-english
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[ "also don't forget to format your code using `make style` to fix the CI" ]
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Add Tweet Eval Dataset
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[ "Hi @lhoestq,\r\n\r\nSeeing that it has been almost two months to this draft, I'm willing to take this forward if you and @abhishekkrthakur don't mind. :)", "Hi @gchhablani !\r\nSure if @abhishekkrthakur doesn't mind\r\nThanks for your help :)", "Please feel free :) ", "Hi @lhoestq, @abhishekkrthakur \r\n\r\nI believe this can be closed. Merged in #1829." ]
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Add Portuguese Hate Speech dataset
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[ "@lhoestq done! (The failing tests don't seem to be related)", "merging since the CI is fixed on master" ]
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Binary Portuguese Hate Speech dataset from [this paper](https://www.aclweb.org/anthology/W19-3510/).
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Adding TaPaCo Dataset with README.md
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[ "We want to keep the repo as light as possible so that it doesn't take ages to clone, that's why we ask for small dummy data files (especially when there are many of them). Let me know if you have questions or if we can help you on this", "Hello @lhoestq , made the changes as you suggested and pushed, please review. By default, the dummy data was generated the way it was by the dummy data auto generate command. Thank you." ]
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Add Acronym Identification Dataset
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[ "fixed @lhoestq " ]
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Add dataset clickbait_news_bg
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[ "Closing this pull request, will submit a new one for this dataset." ]
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Adding a new dataset - clickbait_news_bg
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adding covid-tweets-japanese (again)
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[ "README.md is not created yet. I'll add it soon.", "Thank you for your detailed code review! It's so helpful.\r\nI'll reflect them to the code in 24 hours.\r\n\r\nYou may have told me in Slack (I cannot find the conversation log though I've looked through threads), but I'm sorry it seems I'm still misunderstanding how to get YAML from the tagger.\r\nI'm now asking on Slack if I am looking at the tagger the wrong way.", "One more thing I'd like to ask.\r\nShould I make changes by myself, or can I use the \"Commit suggestion\" feature?\r\nI'm new to this feature and I don't know how the rules work in this repository, so I'd like to ask just in case.", "Thank you very much for merging!" ]
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I had mistaken use git rebase, I was so hurried to fix it. However, I didn't fully consider the use of git reset , so I unintendedly stopped PR (#1367) altogether. Sorry about that. I'll make a new PR.
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Add reasoning_bg
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[ "Hi @saradhix have you had the chance to reduce the size of the dummy data ?\r\n\r\nFeel free to ping me when it's done so we can merge :) ", "@lhoestq I have reduced the size of the dummy data manually and pushed the changes.", "The CI errors are not related to your dataset.\r\nThey're fixed on master, you can ignore them", "merging since the CI is fixed on master" ]
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Adding reading comprehension dataset for Bulgarian language
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Add European Union Education and Culture Translation Memory (EAC-TM) dataset
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Adding the EAC Translation Memory dataset : https://ec.europa.eu/jrc/en/language-technologies/eac-translation-memory
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Add HoVer Dataset
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[ "@lhoestq all comments addressed :) ", "merging since the CI is fixed on master" ]
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HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification https://arxiv.org/abs/2011.03088
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Add Neural Code Search Dataset
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[ "@lhoestq Refactored into new branch, please review :) ", "The `RemoteDatasetTest ` errors in the CI are fixed on master so it's fine", "merging since the CI is fixed on master" ]
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datasets card-creator link added
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dataset card creator link has been added link: https://huggingface.co/datasets/card-creator/
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initial commit for MultiReQA for second PR
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[ "Subsequent [PR #1426 ](https://github.com/huggingface/datasets/pull/1426) since this PR has uploaded other files along with the MultiReQA dataset.", "closing this one since a new PR has been created" ]
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Since last PR #1349 had some issues passing the tests. So, a new PR is generated.
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Add WikiSource Dataset
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[ "@lhoestq fixed :) " ]
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Add OfisPublik Dataset
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Add script_version suggestion when dataset/metric not found
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Adds a helpful prompt to the error message when a dataset/metric is not found, suggesting the user might need to pass `script_version="master"` if the dataset was added recently. The whole error looks like: > Couldn't find file locally at blah/blah.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1/metrics/blah/blah.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/met rics/blah/blah.py. If the dataset was added recently, you may need to to pass script_version="master" to find the loading script on the master branch.
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Add KDE4 Dataset
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Add MultiParaCrawl Dataset
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Add SPC Dataset
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add amazon polarity dataset
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[ "`amazon_polarity` is probably a subset of `amazon_us_reviews` but I am not entirely sure about that.\r\nI guess `amazon_polarity` will help in reproducing results of papers using this dataset since even if it is a subset from `amazon_us_reviews`, it is not trivial how to extract `amazon_polarity` from `amazon_us_reviews`, especially since `amazon_us_reviews` was released after `amazon_polarity`. ", "do you know what the problem would be ? should I pull the master before ? @lhoestq ", "The error just appeared on master. I will try to fix it today.\r\nYou can ignore them since it's not related to the dataset you added", "merging since the CI is fixed on master", "Great thanks for the help. " ]
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This corresponds to the amazon (binary dataset) requested in https://github.com/huggingface/datasets/issues/353
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hind_encorp
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resubmit of hind_encorp file changes
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Add LIAR dataset
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[ "@lhoestq done! The failing testes don't seem to be related, it seems to be a connection issue, if I understand it correctly.", "merging since the CI is fixed on master" ]
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Add LIAR dataset from [β€œLiar, Liar Pants on Fire”: A New Benchmark Dataset for Fake News Detection](https://www.aclweb.org/anthology/P17-2067/).
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Add RecipeNLG Dataset (manual download)
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[ "@lhoestq yes. I asked the authors for direct link but unfortunately we need to fill a form (captcha)" ]
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add best2009
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`best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by [NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for [BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10). The test set answers are not provided publicly.
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Add News Commentary Dataset
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added conv ai 2
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[ "@lhoestq Thank you for the suggestions. I added the changes to the branch and seems after rebasing it to master, all the commits previous commits got added. Should I create a new PR or should I keep this one only ? ", "closing this one in favor of #1527 " ]
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Dataset : https://github.com/DeepPavlov/convai/tree/master/2018
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adding UNPC
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[ "merging since the CI just had a connection error" ]
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Adding United Nations Parallel Corpus http://opus.nlpl.eu/UNPC.php
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Add twi text c3
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[ "looks like this PR includes changes about other datasets\r\n\r\nCan you only include the changes related to twi text c3 please ?", "Hi @lhoestq , I have removed the unnecessary files. Can you please confirm?", "You might need to either find a way to go back to the commit before it changes 389 files or create a new branch.", "okay, I have created another branch, see the latest pull https://github.com/huggingface/datasets/pull/1518 @cstorm125 ", "Hii please follow me", "Closing this one in favor of #1518" ]
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Added Twi texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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[ "looks like this PR includes changes about other datasets\r\n", "Thanks for the review. I'm a bit confused how to remove the files. Every time I add a new branch name using the following commands:\r\n\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit checkout -b a-descriptive-name-for-my-changes\r\n\r\nand push to the origin, this issue occurs", "Can you try to create the branch from the master branch of your fork ?\r\n\r\nfirst update your master branch:\r\n```\r\ngit checkout master\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push\r\n```\r\n\r\nthen create a new one:\r\n```\r\ngit checkout -b my-new-branch\r\n```", "I think you were still having the files because you were creating the new branch from a branch in which you've committed the files, instead of creating the new branch from the master branch", "Got it, will correct that. Thanks", "@lhoestq , I have removed the unnecessary files. Looks like I still have one error. How do I resolve this?", "> @lhoestq , I have removed the unnecessary files. Looks like I still have one error. How do I resolve this?\r\n\r\nI think it's connection error on piqa dataset. Can you try triggering the test again? I usually resolve similar issues with:\r\n```\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push -u -f origin your_branch_name\r\n```", "thank you @cstorm125 ", "I have created another pull request for this https://github.com/huggingface/datasets/pull/1515 @cstorm125 @lhoestq ", "Hii please follow me", "merging since the CI is fixed on master", "Great, thanks a lot" ]
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Added Yoruba texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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Add FACTCK.BR dataset
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This PR adds [FACTCK.BR](https://github.com/jghm-f/FACTCK.BR) dataset from [FACTCK.BR: a new dataset to study fake news](https://dl.acm.org/doi/10.1145/3323503.3361698).
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adding marathi-wiki dataset
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[ "Can you make it a draft PR until you've added the dataset please ? @ekdnam ", "Done" ]
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Adding marathi-wiki-articles dataset.
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Add OPUS EMEA Dataset
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Add OPUS Books Dataset
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Adding Scielo
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Adding Scielo: Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB
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Add OPUS PHP Dataset
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Use passed --cache_dir for modules cache
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[ "I have a question: why not using a tmp dir instead, like the DummyDataGeneratorDownloadManager does?", "Hi @lhoestq, I am trying to understand better the logic...\r\n\r\nWhy do we have a `dynamic_module_path` besides the modules cache path?\r\n```python\r\nDYNAMIC_MODULES_PATH = os.path.join(HF_MODULES_CACHE, \"datasets_modules\")\r\n```\r\nMoreover, 2 subdirectories (for datasets and for metrics) were created inside it:\r\n```python\r\nDATASETS_PATH = os.path.join(DYNAMIC_MODULES_PATH, \"datasets\")\r\nMETRICS_PATH = os.path.join(DYNAMIC_MODULES_PATH, \"metrics\")\r\n```", "Hi :) \r\nThe modules cache path is the path added to `sys.path`.\r\nTherefore inside we need to have a folder that is going to be a package: `datasets_modules`.\r\nThis package will contain dynamic modules, i.e. datasets and metrics modules added on-the-fly.\r\nThen we have two sub-modules `datasets_modules.datasets` and `datasets_modules.metrics`.\r\n\r\nMaybe we can make things more explicit in the code with some comments explaining the structure, and maybe better variable naming as well..\r\n\r\nAlso I wanted to say that I started to work on offline loading of modules in #1726 and actually it lead to do similar changes to what you did to control the path where modules are stored.", "Hi @lhoestq, I see...\r\n\r\nIndeed I was also creating a draft for test_load, to clarify the expected behavior... ;)\r\n\r\nSo, for the command line:\r\n```sh\r\npython datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>\r\n```\r\nthe `cache_dir` argument refers to dataset cache dir. We do not have control over the modules cache dir, but we would like to have. And if I understand well, you suggest adding another argument `dynamic_module_path`. Am I right?", "> So, for the command line:\r\n> \r\n> ```shell\r\n> python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>\r\n> ```\r\n> \r\n> the `cache_dir` argument refers to dataset cache dir. We do not have control over the modules cache dir, but we would like to have. And if I understand well, you suggest adding another argument `dynamic_module_path`. Am I right?\r\n\r\nYes the cache_dir is used to download files and also so save the dataset arrow files.\r\nThis is indeed different from the path for dynamic modules.\r\n\r\nI suggested to have `dynamic_module_path` as a parameter but actually this is the parent directory `hf_modules_cache` that we would need (it's the one that is passed to `init_dynamic_modules ` that we need to add to `sys.path`).\r\n\r\nCurrently it's already possible to override it using the env variable `HF_MODULES_CACHE` but we can imagine having it as a parameter as well.\r\n\r\nThis way the user controls both the `cache_dir` and the `hf_modules_cache` which are the two places used by the library to read/write stuff.\r\n\r\n", "I think #1726 is going to be merged pretty soon. Maybe can work on this as soon as it's merged to avoid doing the same things twice and to avoid conflicts ?", "I agree. Indeed I took some of your code in one of my last commit, to try to implement the logic you described." ]
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When passed `--cache_dir` arg: ```shell python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir> ``` it is not used for caching the modules, which are cached in the default location at `.cache/huggingface/modules`. With this fix, the modules will be cached at `<my-cache-dir>/modules`.
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Re-adding narrativeqa dataset
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[ "@lhoestq I think I've fixed the dummy data - it finally passes! I'll add the model card now.", "@lhoestq - pretty happy with it now", "> Awesome thank you !\r\n> \r\n> Could you try to reduce the size of the dummy_data.zip file before we merge ? (it's 300KB right now)\r\n> \r\n> To do so feel free to take a look inside it and remove all the unnecessary files and chunks of text, to only keep a few examples. The idea is to have a zip file that is only a few KB\r\n\r\nAh, it only contains 1 example for each split. I think the problem is that I include an entire story (like in the full dataset). We can probably get away with a summarised version.", "> Nice thank you, can you make it even lighter if possible ? Something round 10KB would be awesone\r\n> We try to keep the repo light so that it doesn't take ages to clone. So we have to make sure the dummy data are as small as possible for every single dataset.\r\n\r\nHave trimmed a little more out of each example now." ]
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An update of #309.
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adding covid-tweets-japanese
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[ "I think it's because the file you download uncompresses into a file and not a folder so `--autogenerate` couldn't create dummy data for you. See in your dummy_data.zip if there is a file there. If not, manually create your dummy data and compress them to dummy_data.zip.", "@cstorm125 Thank you for the comment! \r\nAs you point out, it seems my code has something wrong about downloading and uncompressing the file.\r\nHowever, my manually created dummy data seems to contain a file of the required format.\r\n\r\nOn Colaboratory,\r\n`!unzip /content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data.zip`\r\nreturns:\r\n\r\n```\r\nArchive: /content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data.zip\r\n creating: content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data/\r\n extracting: content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data/data.csv.bz2 \r\n```\r\n\r\nThe original data is `data.csv.bz2`, and I had a very hard time dealing with uncompressing bzip2.\r\nI think I could handle it, but there may be problems remain." ]
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Adding COVID-19 Japanese Tweets Dataset as part of the sprint. Testing with dummy data is not working (the file is said to not exist). Sorry for the incomplete PR.
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Adding Hope EDI dataset
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[ "@lhoestq Have addressed your comments. Please review. Thanks." ]
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Add Mkqa dataset
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[ "the `RemoteDatasetTest ` error pf the CI is fixed on master so it's fine", "merging since the CI is fixed on master" ]
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# MKQA: Multilingual Knowledge Questions & Answers Dataset Adding the [MKQA](https://github.com/apple/ml-mkqa) dataset as part of the sprint πŸŽ‰ There is no official data splits so I added just a `train` split. differently from the original: - answer:type field is a ClassLabel (I thought it might be possible to train on this as a label for categorizing questions) - answer:entity field has a default value of empty string '' (since this key is not available for all in original) - answer:alias has default value of [] - [x] All tests passed - [x] Added dummy data - [x] Added data card (as much as I could)
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Narrative QA (Manual Download Stories) Dataset
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[ "Hi ! Maybe we can rename it `narrativeqa_manual` to make it explicit that this one requires manual download contrary to `narrativeqa` ?\r\nIt's important to have this one as well, in case the `narrativeqa` one suffers from download issues (checksums or dead links for example).\r\n\r\nYou can also copy the dataset card from `narrativeqa` and add the dummy data as well", "Thanks @lhoestq will do all this and submit a request in the coming days. 😊 ", "Closing this as another pull request is already done. " ]
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Narrative QA with manual download for stories.
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Adding OPUS MultiUN
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Adding UnMulti http://www.euromatrixplus.net/multi-un/
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adding opus_infopankki
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[ "Thanks Quentin !" ]
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Adding opus_infopankki http://opus.nlpl.eu/infopankki-v1.php
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adding bprec
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[ "@lhoestq I think this is ready for review, I assume the errors (connection) are unrelated to the PR :) ", "merging since the CI is fixed on master" ]
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Brand-Product Relation Extraction Corpora in Polish
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add wisesight1000
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`wisesight1000` contains Thai social media texts randomly drawn from the full `wisesight-sentiment`, tokenized by human annotators. Out of the labels `neg` (negative), `neu` (neutral), `pos` (positive), `q` (question), 250 samples each. Some texts are removed because they look like spam.Because these samples are representative of real world content, we believe having these annotaed samples will allow the community to robustly evaluate tokenization algorithms.
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