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added craigslist_bargians
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`craigslist_bargains` data set from [here](https://worksheets.codalab.org/worksheets/0x453913e76b65495d8b9730d41c7e0a0c/)
(Cleaned up version of #1278)
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add LeNER-Br dataset
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"I don't know what happened, my first commit passed on all checks, but after just a README.md update one of the scripts failed, is it normal? 😕 ",
"Looks like a flaky connection error, I've launched a re-run, it should be fine :)",
"The RemoteDatasetTest error in the CI is just a connection error, we can ignore it",
"merging since the CI is fixed on master"
] | 2020-12-09T00:06:38Z | 2020-12-10T14:11:33Z | 2020-12-10T14:11:33Z |
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Adding the LeNER-Br dataset, a Portuguese language dataset for named entity recognition
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initial commit for MultiReQA
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"looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n\r\nCan you create another branch and another PR please ?",
"> looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\nSure I will do that. Thank you."
] | 2020-12-08T23:44:34Z | 2020-12-09T16:46:37Z | 2020-12-09T16:46:37Z |
CONTRIBUTOR
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Added MultiReQA, which is a dataset containing the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA.
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add Yoruba NER dataset
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"Thank you. Okay, other pull requests only have one dataset",
"The `RemoteDatasetTest` error in the CI is just a connection error, we can ignore it",
"merging since the CI is fixed on master",
"Thank you very much"
] | 2020-12-08T23:42:35Z | 2020-12-10T14:30:25Z | 2020-12-10T14:09:43Z |
CONTRIBUTOR
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Added Yoruba GV dataset based on this paper
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Add spanish billion words corpus
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"Thank you for your feedback! I've reduced the dummy data size to 2KB.\r\n\r\nI had to rebase to fix `RemoteDatasetTest` fails, sorry about the 80 commits. \r\nI could create a new clean PR if you prefer.",
"I have seen that in similar cases you have suggested to other contributors to create another branch and another PR, so I will do that.",
"Yes thank you !",
"The new PR is #1476 :)"
] | 2020-12-08T22:51:38Z | 2020-12-11T11:26:39Z | 2020-12-11T11:15:28Z |
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Add an unannotated Spanish corpus of nearly 1.5 billion words, compiled from different resources from the web.
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Add MultiBooked dataset
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"There' still an issue with the dummy data, let me take a look"
] | 2020-12-08T22:49:36Z | 2020-12-15T17:02:09Z | 2020-12-15T17:02:09Z |
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Add dataset.
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First commit of NarrativeQA Dataset
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[] | 2020-12-08T22:31:59Z | 2021-01-25T15:31:52Z | 2020-12-09T09:29:52Z |
CONTRIBUTOR
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Added NarrativeQA dataset and included a manual downloading option to download scripts from the original scripts provided by the authors.
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Add hausa ner corpus
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[] | 2020-12-08T22:25:04Z | 2020-12-08T23:11:55Z | 2020-12-08T23:11:55Z |
CONTRIBUTOR
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Added Hausa VOA NER data
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Add LiveQA
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[] | 2020-12-08T21:52:36Z | 2020-12-14T09:40:28Z | 2020-12-14T09:40:28Z |
CONTRIBUTOR
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This PR adds LiveQA, the Chinese real-time/timeline-based QA task by [Liu et al., 2020](https://arxiv.org/pdf/2010.00526.pdf).
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[yaml] Fix metadata according to pre-specified scheme
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@lhoestq @yjernite
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We can now use the wonderful online form for dataset cards created by @evrardts
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:fist: ¡Viva la Independencia!
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"I've added the changes / fixes - ready for a second pass :)"
] | 2020-12-08T20:43:43Z | 2020-12-14T10:36:01Z | 2020-12-14T10:36:01Z |
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Adds the Catalonia Independence Corpus for stance-detection of Tweets.
Ready for review!
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hate_speech_18 initial commit
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"> Nice thanks !\r\n> \r\n> Can you rename the dataset folder and the dataset script name `hate_speech18` instead of `hate_speech_18` to follow the snake case convention we're using ?\r\n> \r\n> Also it looks like the dummy_data.zip file is quite big (almost 4MB).\r\n> Can you try to reduce its size ?\r\n> \r\n> To do so feel free to take a look inside it and remove all the unnecessary files or chunks of texts. The idea is to only keep a few examples\r\n\r\nDone, thanks! ",
"Re-opened in https://github.com/huggingface/datasets/pull/1486"
] | 2020-12-08T20:10:08Z | 2020-12-12T16:17:32Z | 2020-12-12T16:17:32Z |
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Add GigaFren Dataset
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"@lhoestq fixed"
] | 2020-12-08T19:42:04Z | 2020-12-14T10:03:47Z | 2020-12-14T10:03:46Z |
CONTRIBUTOR
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Add spanish billion words
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"The tests failed because of ```RemoteDatasetTest``` so I tried ```git rebase``` and messed everything up. I've made a new clean PR (#1347)."
] | 2020-12-08T19:18:02Z | 2020-12-08T22:59:38Z | 2020-12-08T21:15:27Z |
CONTRIBUTOR
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Add an unannotated corpus of the Spanish language of nearly 1.5 billion words, compiled from different resources from the web.
The dataset needs 10 GB (download: 1.89 GiB, generated: 8.34 GiB, post-processed: Unknown size, total: 10.22 GiB), the test using dummy data pass but my laptop isn't able to run it on the real data (I left it running for over 8 hours and it didn't finish).
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Add dataset Yoruba BBC Topic Classification
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[] | 2020-12-08T19:12:18Z | 2020-12-10T11:27:41Z | 2020-12-10T11:27:41Z |
CONTRIBUTOR
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Added new dataset Yoruba BBC Topic Classification
Contains loading script as well as dataset card including YAML tags.
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Added Bianet dataset
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"merging since the Ci is fixed on master"
] | 2020-12-08T19:10:32Z | 2020-12-14T10:00:56Z | 2020-12-14T10:00:56Z |
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Hi :hugs:, This is a PR for [Bianet: A parallel news corpus in Turkish, Kurdish and English; Source](http://opus.nlpl.eu/Bianet.php) dataset
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Add QED Amara Dataset
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Add Tanzil Dataset
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Add Open Subtitles Dataset
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First version of the new dataset hausa_voa_topics
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Contains loading script as well as dataset card including YAML tags.
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"Looks like this PR includes changes about many other files than the ones for un_ga\r\n\r\nCan you create another branch an another PR please ?",
"@lhoestq, Thank you for suggestions. I have made the changes and raised the new PR https://github.com/huggingface/datasets/pull/1569. "
] | 2020-12-08T17:58:38Z | 2020-12-14T17:52:34Z | 2020-12-14T17:52:34Z |
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Hi :hugs:, This is a PR for [United nations general assembly resolutions: A six-language parallel corpus](http://opus.nlpl.eu/UN.php) dataset
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Add yoruba ner corpus
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Added the NewsPH Raw dataset and corresponding dataset card
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This PR adds the original NewsPH dataset which is used to autogenerate the NewsPH-NLI dataset. Reopened a new PR as the previous one had problems.
Paper: https://arxiv.org/abs/2010.11574
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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Add msr_genomics_kbcomp dataset
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TEP: Tehran English-Persian parallel corpus
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TEP: Tehran English-Persian parallel corpus
more info : http://opus.nlpl.eu/TEP.php
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Add humicroedit dataset
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[
"Updated the commit with the generated yaml tags",
"merging since the CI is fixed on master"
] | 2020-12-08T16:35:46Z | 2020-12-17T17:59:09Z | 2020-12-17T17:59:09Z |
CONTRIBUTOR
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Pull request for adding humicroedit dataset
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❓ Sharing ElasticSearch indexed dataset
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"Hello @pietrolesci , I am not sure to understand what you are trying to do here.\r\n\r\nIf you're looking for ways to save a dataset on disk, you can you the `save_to_disk` method:\r\n```python\r\n>>> import datasets\r\n>>> loaded_dataset = datasets.load(\"dataset_name\")\r\n>>> loaded_dataset.save_to_disk(\"/path/on/your/disk\")\r\n```\r\n\r\nThe saved dataset can later be retrieved using:\r\n```python\r\n>>> loaded_dataset = datasets.Dataset.load_from_disk(\"/path/on/your/disk\")\r\n```\r\n\r\nAlso, I'd recommend posting your question directly in the issue section of the [elasticsearch repo](https://github.com/elastic/elasticsearch)",
"Hi @SBrandeis,\n\nThanks a lot for picking up my request. \n\nMaybe I can clarify my use-case with a bit of context. Say I have the IMDb dataset. I create an ES index on it. Now I can save and reload the dataset from disk normally. Once I reload the dataset, it is easy to retrieve the ES index on my machine. I was wondering: is there a way I can share the (now) indexed version of the IMDb dataset with my colleagues without requiring them to re-index it?\n\nThanks a lot in advance for your consideration.\n\nBest,\n\nPietro",
"Thanks for the clarification.\r\n\r\nI am not familiar with ElasticSearch, but if I understand well you're trying to migrate your data along with the ES index.\r\nMy advice would be to check out ES documentation, for instance, this might help you: https://www.elastic.co/guide/en/cloud/current/ec-migrate-data.html\r\n\r\nLet me know if it helps"
] | 2020-12-08T16:25:58Z | 2020-12-22T07:50:56Z | null |
NONE
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Hi there,
First of all, thank you very much for this amazing library. Datasets have become my preferred data structure for basically everything I am currently doing.
**Question:** I'm working with a dataset and I have an elasticsearch container running at localhost:9200. I added an elasticsearch index and I was wondering
- how can I know where it has been saved?
- how can I share the indexed dataset with others?
I tried to dig into the docs, but could not find anything about that.
Thank you very much for your help.
Best,
Pietro
Edit: apologies for the wrong label
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Add CC-News dataset of English language articles
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"@vblagoje nice work, please add the README.md file and it would be ready",
"@lhoestq @tanmoyio @yjernite please have a look at the dataset card. Don't forget that the dataset is still hosted on my private gs bucket and should eventually be moved to the HF bucket",
"I will move the files soon and ping you when it's done and with the new URLs :) ",
"Hi !\r\n\r\nI just moved the file to a HF bucket. It's available at https://storage.googleapis.com/huggingface-nlp/datasets/cc_news/cc_news.tar.gz\r\n\r\nSorry for the delay ^^'",
"@lhoestq no worries, updated PR with the new URL and rebased to master\r\n"
] | 2020-12-08T16:18:15Z | 2021-02-01T16:55:49Z | 2021-02-01T16:55:49Z |
CONTRIBUTOR
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Adds [CC-News](https://commoncrawl.org/2016/10/news-dataset-available/) dataset. It contains 708241 English language news articles. Although each article has a language field these tags are not reliable. I've used Spacy language detection [pipeline](https://spacy.io/universe/project/spacy-langdetect) to confirm that the article language is indeed English.
The prepared dataset is temporarily hosted on my private Google Storage [bucket](https://storage.googleapis.com/hf_datasets/cc_news.tar.gz). We can move it to HF storage and update this PR before merging.
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add indonlu benchmark datasets
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The IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for the Indonesian language. There are 12 datasets in IndoNLU.
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"@lhoestq \r\nUpdated the `dummy_data.zip `(<10kb)I had to reduce it to just a few samples. \r\nTrain-Test-Dev (20-5-5 samples) \r\n\r\nBut the push also added changes from other PRs (probably because of a rebase!) So the files changed tab shows 466 files were changed! \r\n",
"Thanks ! The dummy data are all good now :) \r\n\r\nLooks like this PR includes changes to many other files than the ones for dutch_social now.\r\n\r\nCan you create another branch and another PR please ?",
"> \r\n> Can you create another branch and another PR please ?\r\n@lhoestq \r\n\r\nI did a rebase. Now it doesn't include the other files. Does that help? \r\n\r\n",
"Yes thanks !"
] | 2020-12-08T16:07:54Z | 2020-12-16T10:14:17Z | 2020-12-16T10:14:17Z |
CONTRIBUTOR
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The Dutch social media tweets dataset. Which has a total of more than 210k tweets in dutch language. These tweets have been machine annotated with sentiment scores (`label` feature) and `industry` and `hisco_codes`
It can be used for sentiment analysis, multi-label classification and entity tagging
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NONE
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This PR adds the WikiText-TL-39 Filipino Language Modeling dataset. Restarted a new pull request since there were problems with the earlier one.
Paper: https://arxiv.org/abs/1907.00409
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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adding wili-2018 language identification dataset
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"@lhoestq Not sure what happened, I just changed the py file but it is showing some TensorFlow error now.",
"You can ignore it.\r\nIt's caused by the Tensorflow update that happened 30min ago. They added breaking changes.\r\nI'm working on a fix on the master branch right now\r\n",
"oh okay, btw I have made the required change for reading the CSV, I think it should be fine now, please take a look at it when you have some time.",
"merging since the CI is fixed on master"
] | 2020-12-08T16:00:09Z | 2020-12-14T21:20:32Z | 2020-12-14T21:20:32Z |
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ethos first commit
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"> Nice thanks !\r\n> \r\n> I left a few comments\r\n> \r\n> Also it looks like this PR includes changes about other files than the ones for ethos\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\n@lhoestq Should I close this PR? The new one is the: #1453",
"You can create another PR and close this one if you don't mind",
"> You can create another PR and close this one if you don't mind\r\n\r\nPerfect! You should see the #1453 PR for the fixed version! Thanks"
] | 2020-12-08T15:59:47Z | 2020-12-10T14:45:57Z | 2020-12-10T14:45:57Z |
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Ethos passed all the tests except from this one:
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your-dataset-name>
with this error:
E OSError: Cannot find data file.
E Original error:
E [Errno 2] No such file or directory:
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add 10k German News Article Dataset
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"You can just create another branch from master on your fork and create another PR:\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 branch\r\n```\r\ngit checkout -b my-new-branch-name\r\n```\r\n\r\nThen you can add, commit and push the gnad10 files and open a new PR",
"closing in favor of #1572 "
] | 2020-12-08T15:44:25Z | 2021-09-17T16:55:51Z | 2020-12-16T16:50:43Z |
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Allow GitHub releases as dataset source
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[] | 2020-12-08T15:39:35Z | 2020-12-10T10:12:00Z | 2020-12-10T10:12:00Z |
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# Summary
Providing a GitHub release URL to `DownloadManager.download()` currently throws a `ConnectionError: Couldn't reach [DOWNLOAD_URL]`. This PR fixes this problem by adding an exception for GitHub releases in `datasets.utils.file_utils.get_from_cache()`.
# Reproduce
```
import datasets
url = 'http://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz'
result = datasets.utils.file_utils.get_from_cache(url)
# Returns: ConnectionError: Couldn't reach http://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz
```
# Cause
GitHub releases returns a HTTP status 403 (FOUND), indicating that the request is being redirected (to AWS S3, in this case). `get_from_cache()` checks whether the status is 200 (OK) or if it is part of two exceptions (Google Drive or Firebase), otherwise the mentioned error is thrown.
# Solution
Just like the exceptions for Google Drive and Firebase, add a condition for GitHub releases URLs that return the HTTP status 403. If this is the case, continue normally.
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add yelp_review_full
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This corresponds to the Yelp-5 requested in https://github.com/huggingface/datasets/issues/353
I included the dataset card.
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Add snips built in intents 2016 12
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"It is not clear how to automatically add the dummy data if the source data is a more complex json format. Should I manually take a fraction of the source data and include it as dummy data?\r\n",
"Added a fraction of the real data as dummy data.",
"merging since the CI is fixed on master"
] | 2020-12-08T15:30:19Z | 2020-12-14T09:59:07Z | 2020-12-14T09:59:07Z |
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This PR proposes to add the Snips.ai built in intents dataset. The first configuration added is for the intent labels only, but the dataset includes entity slots that may in future be added as alternate configurations.
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Add HateSpeech Corpus for Polish
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"@lhoestq Do you think using the ClassLabel is correct if we don't know the meaning of them?",
"Once we find out the meanings we can still add them to the dataset card",
"Feel free to ping me when the PR is ready for the final review"
] | 2020-12-08T15:23:53Z | 2020-12-16T16:48:45Z | 2020-12-16T16:48:45Z |
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This PR adds a HateSpeech Corpus for Polish, containing offensive language examples.
- **Homepage:** http://zil.ipipan.waw.pl/HateSpeech
- **Paper:** http://www.qualitativesociologyreview.org/PL/Volume38/PSJ_13_2_Troszynski_Wawer.pdf
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Jigsaw toxicity pred
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Requires manually downloading data from Kaggle.
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"@lhoestq done"
] | 2020-12-08T14:57:08Z | 2020-12-09T15:30:57Z | 2020-12-09T15:30:56Z |
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Add OffensEval-TR 2020 Dataset
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[
"@lhoestq, can you please review this PR? ",
"> Awesome thank you !\r\n\r\nThanks for the small fixes @lhoestq ",
"@coltekin, we have added the data set that you created an article that says \"Turkish Attack Language Community in Social Media\", HuggingFace dataset update sprint for you. We added Sprint quickly for a short time. I hope you welcome it too. The dataset is accessible at https://huggingface.co/datasets/offenseval2020_tr. ",
"Thank you for the heads up. I am not familiar with the terminology above (no idea what a sprint is), but I am happy that you found the data useful. Please feel free to distribute/use it as you see fit.\r\n\r\nThe OffensEval version you included in your data set has only binary labels. There is also a version [here](https://coltekin.github.io/offensive-turkish/troff-v1.0.tsv.gz) which also includes fine-grained labels similar to the OffensEval English data set - Just in case it would be of interest.\r\n\r\nIf you have questions about the data set, or need more information please let me know."
] | 2020-12-08T14:49:51Z | 2020-12-12T14:15:42Z | 2020-12-09T16:02:06Z |
CONTRIBUTOR
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This PR adds the OffensEval-TR 2020 dataset which is a Turkish offensive language corpus by me and @basakbuluz. The corpus consist of randomly sampled tweets and annotated in a similar way to [OffensEval](https://sites.google.com/site/offensevalsharedtask/) and [GermEval](https://projects.fzai.h-da.de/iggsa/).
- **Homepage:** [offensive-turkish](https://coltekin.github.io/offensive-turkish/)
- **Paper:** [A Corpus of Turkish Offensive Language on Social Media](https://coltekin.github.io/offensive-turkish/troff.pdf)
- **Point of Contact:** [Çağrı Çöltekin]([email protected])
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Add SAMSum Corpus dataset
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"also to fix the check_code_quality CI you have to remove the imports of the unused `csv` and `os`",
"@lhoestq Thanks for the review! I have done what you asked, README is also updated. 🤗 \r\nThe CI fails because of the added dependency. I have never used circleCI before, so I am curious how will you solve that?",
"I just added `py7zr` to our test dependencies",
"merging since the CI is fixed on master",
"Thanks! 🤗 "
] | 2020-12-08T14:40:56Z | 2020-12-14T12:32:33Z | 2020-12-14T10:20:55Z |
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Did not spent much time writing README, might update later.
Copied description and some stuff from tensorflow_datasets
https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/summarization/samsum.py
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Add Wiki Lingua Dataset
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"I am done adding the dataset. Requesting to review and advise.",
"looks like this PR has changes about many other files than the ones for WIki Lingua \r\n\r\nCan you create another branch and another PR please ?",
"Any reason to have english as the default config over the other languages ?",
"> looks like this PR has changes about many other files than the ones for WIki Lingua\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\nOk, I will create another branch and submit a fresh PR.",
"> Any reason to have english as the default config over the other languages ?\r\n\r\nThe data for all other languages has a direct reference to English article. Thus, I kept English as default.",
"closing in favor of #1470 "
] | 2020-12-08T14:30:13Z | 2020-12-14T10:39:52Z | 2020-12-14T10:39:52Z |
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Hello,
This is my first PR.
I have added Wiki Lingua Dataset along with dataset card to the best of my knowledge.
There was one hiccup though. I was unable to create dummy data because the data is in pkl format.
From the document, I see that:
```At the moment it supports data files in the following format: txt, csv, tsv, jsonl, json, xml```
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adding capes
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[] | 2020-12-08T13:46:13Z | 2020-12-09T15:40:09Z | 2020-12-09T15:27:45Z |
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Adding Parallel corpus of theses and dissertation abstracts in Portuguese and English from CAPES
https://sites.google.com/view/felipe-soares/datasets#h.p_kxOR6EhHm2a6
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add W&I + LOCNESS dataset (BEA-2019 workshop shared task on GEC)
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"I created a clean PR where I also incorporated the suggested changes here: https://github.com/huggingface/datasets/pull/1449\r\n"
] | 2020-12-08T13:31:34Z | 2020-12-10T09:53:54Z | 2020-12-10T09:53:28Z |
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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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[README] Added Windows command to enable slow tests
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[] | 2020-12-08T13:29:04Z | 2020-12-08T13:56:33Z | 2020-12-08T13:56:32Z |
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The Windows command to run slow tests has caused issues, so this adds a functional Windows command.
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adding eitb_parcc
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Adding EiTB-ParCC: Parallel Corpus of Comparable News
http://opus.nlpl.eu/EiTB-ParCC.php
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adding opus_openoffice
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Adding Opus OpenOffice: http://opus.nlpl.eu/OpenOffice.php
8 languages, 28 bitexts
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Add Danish NER dataset
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CONTRIBUTOR
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arxiv dataset added
|
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[
"Readme added\r\n",
"@lhoestq is it looking alright ? "
] | 2020-12-08T12:50:51Z | 2020-12-09T18:05:16Z | 2020-12-09T18:05:16Z |
CONTRIBUTOR
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**adding arXiv dataset**: arXiv dataset and metadata of 1.7M+ scholarly papers across STEM
dataset link: https://www.kaggle.com/Cornell-University/arxiv
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added dutch_social
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closed
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[
"Closing this since a new pull request has been made. "
] | 2020-12-08T12:47:50Z | 2020-12-08T16:09:05Z | 2020-12-08T16:09:05Z |
CONTRIBUTOR
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WIP
As some tests did not clear! 👎🏼
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can't load "german_legal_entity_recognition" dataset
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[
"Please if you could tell me more about the error? \r\n\r\n1. Please check the directory you've been working on\r\n2. Check for any typos",
"> Please if you could tell me more about the error?\r\n> \r\n> 1. Please check the directory you've been working on\r\n> 2. Check for any typos\r\n\r\nError happens during the execution of this line:\r\ndataset = load_dataset(\"german_legal_entity_recognition\")\r\n\r\nAlso, when I try to open mentioned links via Opera I have errors \"404: Not Found\" and \"This XML file does not appear to have any style information associated with it. The document tree is shown below.\" respectively.",
"Hello @nataly-obr, the `german_legal_entity_recognition` dataset has not yet been released (it is part of the coming soon v2 release).\r\n\r\nYou can still access it now if you want, but you will need to install `datasets` via the master branch:\r\n`pip install git+https://github.com/huggingface/datasets.git@master`\r\n\r\nPlease let me know if it solves the issue :) "
] | 2020-12-08T12:42:01Z | 2020-12-16T16:03:13Z | 2020-12-16T16:03:13Z |
NONE
| null | null | null | null |
FileNotFoundError: Couldn't find file locally at german_legal_entity_recognition/german_legal_entity_recognition.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/german_legal_entity_recognition/german_legal_entity_recognition.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/german_legal_entity_recognition/german_legal_entity_recognition.py
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Add OPUS Ted Talks 2013
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"merging since the CI is fixed on master"
] | 2020-12-08T12:38:38Z | 2020-12-16T16:57:50Z | 2020-12-16T16:57:49Z |
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The Snips Built In Intents 2016 dataset.
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[
"It is not clear how to automatically add the dummy data if the source data is a more complex json format. Should I manually take a fraction of the source data and include it as dummy data?",
"Will tag the dataset and update the dataset card."
] | 2020-12-08T11:40:10Z | 2020-12-08T15:27:52Z | 2020-12-08T15:27:52Z |
CONTRIBUTOR
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This PR proposes to add the Snips.ai built in intents dataset. The first configuration added is for the intent labels only, but the dataset includes entity slots that may in future be added as alternate configurations.
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add hrenwac_para
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[] | 2020-12-08T11:24:16Z | 2020-12-08T18:44:20Z | 2020-12-08T18:41:23Z |
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Adding EUconst, a parallel corpus collected from the European Constitution.
21 languages, 210 bitexts
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add hrenwac_para
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Pubmed QA dataset:
PQA-L(abeled) 1k
PQA-U(labeled) 61.2k
PQA-A(rtifical labeled) 211.3k
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imdb dataset cannot be downloaded
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[
"Hi @rabeehk , I am unable to reproduce your problem locally.\r\nCan you try emptying the cache (removing the content of `/idiap/temp/rkarimi/cache_home_1/datasets`) and retry ?",
"Hi,\r\nthanks, I did remove the cache and still the same error here\r\n\r\n```\r\n>>> a = datasets.load_dataset(\"imdb\", split=\"train\")\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\nDownloading and preparing dataset imdb/plain_text (download: 80.23 MiB, generated: 127.06 MiB, post-processed: Unknown size, total: 207.28 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/imdb/plain_text/1.0.0/90099cb476936b753383ba2ae6ab2eae419b2e87f71cd5189cb9c8e5814d12a3...\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads\r\nTraceback (most recent call last): \r\n File \"<stdin>\", line 1, in <module>\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py\", line 611, in load_dataset\r\n ignore_verifications=ignore_verifications,\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 476, in download_and_prepare\r\n dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 558, in _download_and_prepare\r\n verify_splits(self.info.splits, split_dict)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/info_utils.py\", line 73, in verify_splits\r\n raise NonMatchingSplitsSizesError(str(bad_splits))\r\ndatasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='unsupervised', num_bytes=67125548, num_examples=50000, dataset_name='imdb'), 'recorded': SplitInfo(name='unsupervised', num_bytes=4902716, num_examples=3680, dataset_name='imdb')}]\r\n```\r\n\r\ndatasets version\r\n```\r\ndatasets 1.1.2 <pip>\r\ntensorflow-datasets 4.1.0 <pip>\r\n\r\n```",
"resolved with moving to version 1.1.3"
] | 2020-12-08T10:47:36Z | 2020-12-24T17:38:09Z | 2020-12-24T17:38:09Z |
CONTRIBUTOR
| null | null | null | null |
hi
please find error below getting imdb train spli:
thanks
`
datasets.load_dataset>>> datasets.load_dataset("imdb", split="train")`
errors
```
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Downloading and preparing dataset imdb/plain_text (download: 80.23 MiB, generated: 127.06 MiB, post-processed: Unknown size, total: 207.28 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/imdb/plain_text/1.0.0/90099cb476936b753383ba2ae6ab2eae419b2e87f71cd5189cb9c8e5814d12a3...
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 558, in _download_and_prepare
verify_splits(self.info.splits, split_dict)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/info_utils.py", line 73, in verify_splits
raise NonMatchingSplitsSizesError(str(bad_splits))
datasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='unsupervised', num_bytes=67125548, num_examples=50000, dataset_name='imdb'), 'recorded': SplitInfo(name='unsupervised', num_bytes=7486451, num_examples=5628, dataset_name='imdb')}]
```
|
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The dataset requires manually downloading data from Kaggle.
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| 759,309,457 |
MDExOlB1bGxSZXF1ZXN0NTM0MzM2Mzgz
| 1,288 |
Add CodeSearchNet corpus dataset
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"@lhoestq ready for a second review"
] | 2020-12-08T10:07:50Z | 2020-12-09T17:05:28Z | 2020-12-09T17:05:28Z |
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This PR adds the CodeSearchNet corpus proxy dataset for semantic code search: https://github.com/github/CodeSearchNet
I have had a few issues, mentioned below. Would appreciate some help on how to solve them.
## Issues generating dataset card
Is there something wrong with my declaration of the dataset features ?
```
features=datasets.Features(
{
"repository_name": datasets.Value("string"),
"func_path_in_repository": datasets.Value("string"),
"func_name": datasets.Value("string"),
"whole_func_string": datasets.Value("string"),
"language": datasets.Value("string"),
"func_code_string": datasets.Value("string"),
"func_code_tokens": datasets.Sequence(datasets.Value("string")),
"func_documentation_string": datasets.Value("string"),
"func_documentation_tokens": datasets.Sequence(datasets.Value("string")),
"split_name": datasets.Value("string"),
"func_code_url": datasets.Value("string"),
# TODO - add licensing info in the examples
}
),
```
When running the streamlite app for tagging the dataset on my machine, I get the following error :
## Issues with dummy data
Due to the unusual structure of the data, I have been unable to generate dummy data automatically.
I tried to generate it manually, but pytests fail when using the manually-generated dummy data ! Pytests work fine when using the real data.
```
============================================================================================== test session starts ==============================================================================================
platform linux -- Python 3.7.9, pytest-6.1.2, py-1.9.0, pluggy-0.13.1
plugins: xdist-2.1.0, forked-1.3.0
collected 1 item
tests/test_dataset_common.py F [100%]
=================================================================================================== FAILURES ====================================================================================================
________________________________________________________________________ LocalDatasetTest.test_load_dataset_all_configs_code_search_net _________________________________________________________________________
self = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_code_search_net>, dataset_name = 'code_search_net'
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
tests/test_dataset_common.py:237:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/test_dataset_common.py:198: in check_load_dataset
self.parent.assertTrue(len(dataset[split]) > 0)
E AssertionError: False is not true
--------------------------------------------------------------------------------------------- Captured stdout call ----------------------------------------------------------------------------------------------
Downloading and preparing dataset code_search_net/all (download: 1.00 MiB, generated: 1.00 MiB, post-processed: Unknown size, total: 2.00 MiB) to /tmp/tmppx78sj24/code_search_net/all/1.0.0...
Dataset code_search_net downloaded and prepared to /tmp/tmppx78sj24/code_search_net/all/1.0.0. Subsequent calls will reuse this data.
--------------------------------------------------------------------------------------------- Captured stderr call ----------------------------------------------------------------------------------------------
... (irrelevant info - Deprecation warnings)
============================================================================================ short test summary info ============================================================================================
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_code_search_net - AssertionError: False is not true
========================================================================================= 1 failed, 4 warnings in 3.00s ========================================================================================
```
## Note : Data structure in S3
The data is stored on S3, and organized by programming languages.
It is stored in the following repository structure:
```
.
├── <language_name> # e.g. python
│ └── final
│ └── jsonl
│ ├── test
│ │ └── <language_name>_test_0.jsonl.gz
│ ├── train
│ │ ├── <language_name>_train_0.jsonl.gz
│ │ ├── <language_name>_train_1.jsonl.gz
│ │ ├── ...
│ │ └── <language_name>_train_n.jsonl.gz
│ └── valid
│ └── <language_name>_valid_0.jsonl.gz
├── <language_name>_dedupe_definitions_v2.pkl
└── <language_name>_licenses.pkl
```
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'iwslt2017-ro-nl', cannot be downloaded
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[
"the same issue with datasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=split), ..... ",
"even with setting master like the following command, still remains \r\n\r\ndatasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=\"train\", script_version=\"master\")\r\n",
"Looks like the data has been moved from its original location to google drive\r\n\r\nNew url: https://drive.google.com/u/0/uc?id=12ycYSzLIG253AFN35Y6qoyf9wtkOjakp&export=download",
"Fixed by #4481 "
] | 2020-12-08T09:56:55Z | 2022-06-13T10:41:33Z | 2022-06-13T10:41:33Z |
CONTRIBUTOR
| null | null | null | null |
Hi
I am trying
`>>> datasets.load_dataset("iwslt2017", 'iwslt2017-ro-nl', split="train")`
getting this error thank you for your help
```
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
Downloading and preparing dataset iwsl_t217/iwslt2017-ro-nl (download: 314.07 MiB, generated: 39.92 MiB, post-processed: Unknown size, total: 354.00 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/iwsl_t217/iwslt2017-ro-nl/1.0.0/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd...
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/iwslt2017/cca6935a0851a8ceac1202a62c958738bdfa23c57a51bc52ac1c5ebd2aa172cd/iwslt2017.py", line 118, in _split_generators
dl_dir = dl_manager.download_and_extract(MULTI_URL)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 254, in download_and_extract
return self.extract(self.download(url_or_urls))
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 179, in download
num_proc=download_config.num_proc,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/py_utils.py", line 216, in map_nested
return function(data_struct)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 308, in cached_path
use_etag=download_config.use_etag,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/file_utils.py", line 477, in get_from_cache
raise ConnectionError("Couldn't reach {}".format(url))
ConnectionError: Couldn't reach https://wit3.fbk.eu/archive/2017-01-trnmted//texts/DeEnItNlRo/DeEnItNlRo/DeEnItNlRo-DeEnItNlRo.tgz
```
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[libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): terminate called after throwing an instance of 'google::protobuf::FatalException' what(): CHECK failed: (index) >= (0): Aborted
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[
"I remember also getting the same issue for several other translation datasets like all the iwslt2017 group, this is blokcing me and I really need to fix it and I was wondering if you have an idea on this. @lhoestq thanks,. ",
"maybe there is an empty line or something inside these datasets? could you tell me why this is happening? thanks ",
"I just checked and the wmt16 en-ro doesn't have empty lines\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nd = load_dataset(\"wmt16\", \"ro-en\", split=\"train\")\r\nlen(d) # 610320\r\nlen(d.filter(lambda x: len(x[\"translation\"][\"en\"].strip()) > 0)) # 610320\r\nlen(d.filter(lambda x: len(x[\"translation\"][\"ro\"].strip()) > 0)) # 610320\r\n# also tested for split=\"validation\" and \"test\"\r\n```\r\n\r\nCan you open an issue on the `transformers` repo ? also cc @sgugger ",
"Hi @lhoestq \r\nI am not really sure which part is causing this, to me this is more related to dataset library as this is happening for some of the datassets below please find the information to reprodcue the bug, this is really blocking me and I appreciate your help\r\n\r\n\r\n## Environment info\r\n- `transformers` version: 3.5.1\r\n- Platform: GPU\r\n- Python version: 3.7 \r\n- PyTorch version (GPU?): 1.0.4\r\n- Tensorflow version (GPU?): - \r\n- Using GPU in script?: - \r\n- Using distributed or parallel set-up in script?: - \r\n\r\n### Who can help\r\n tokenizers: @mfuntowicz\r\n Trainer: @sgugger\r\n TextGeneration: @TevenLeScao \r\n nlp datasets: [different repo](https://github.com/huggingface/nlp)\r\n rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)\r\n examples/seq2seq: @patil-suraj\r\n\r\n## Information\r\nHi\r\nI am testing seq2seq model with T5 on different datasets and this is always getting the following bug, this is really blocking me as this fails for many datasets. could you have a look please? thanks \r\n\r\n```\r\n[libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): \r\nterminate called after throwing an instance of 'google::protobuf::FatalException'\r\n what(): CHECK failed: (index) >= (0): \r\nAborted\r\n\r\n```\r\n\r\nTo reproduce the error please run on 1 GPU:\r\n```\r\ngit clone [email protected]:rabeehk/debug-seq2seq.git\r\npython setup.py develop \r\ncd seq2seq \r\npython finetune_t5_trainer.py temp.json\r\n\r\n```\r\n\r\nFull output of the program:\r\n\r\n```\r\n(internship) rkarimi@vgnh008:/idiap/user/rkarimi/dev/debug-seq2seq/seq2seq$ python finetune_t5_trainer.py temp.json \r\n2020-12-12 15:38:16.234542: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory\r\n2020-12-12 15:38:16.234598: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.\r\n12/12/2020 15:38:32 - WARNING - __main__ - Process rank: -1, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False\r\n12/12/2020 15:38:32 - INFO - __main__ - Training/evaluation parameters Seq2SeqTrainingArguments(output_dir='outputs/test', overwrite_output_dir=True, do_train=True, do_eval=True, do_predict=False, evaluate_during_training=False, evaluation_strategy=<EvaluationStrategy.NO: 'no'>, prediction_loss_only=False, per_device_train_batch_size=64, per_device_eval_batch_size=64, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=1, eval_accumulation_steps=None, learning_rate=0.01, weight_decay=0.0, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, max_grad_norm=1.0, num_train_epochs=2, max_steps=-1, warmup_steps=500, logging_dir='runs/Dec12_15-38-32_vgnh008', logging_first_step=True, logging_steps=200, save_steps=200, save_total_limit=1, no_cuda=False, seed=42, fp16=False, fp16_opt_level='O1', local_rank=-1, tpu_num_cores=None, tpu_metrics_debug=False, debug=False, dataloader_drop_last=False, eval_steps=200, dataloader_num_workers=0, past_index=-1, run_name='outputs/test', disable_tqdm=False, remove_unused_columns=True, label_names=None, load_best_model_at_end=False, metric_for_best_model=None, greater_is_better=None, label_smoothing=0.1, sortish_sampler=False, predict_with_generate=True, adafactor=False, encoder_layerdrop=None, decoder_layerdrop=None, dropout=None, attention_dropout=None, lr_scheduler='linear', fixed_length_emb=None, encoder_projection=None, encoder_pooling=None, projection_length=None, only_projection_bottleneck=False, concat_projection_token=False, gcs_bucket='ruse-xcloud-bucket', temperature=10, train_adapters=True, do_finetune=True, parametric_task_embedding=False, 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'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.post_layer_norm.weight', 'decoder.block.5.layer.2.adapter_controller.post_layer_norm.bias']\r\nYou should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140079090376272 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140079090376272 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\nUsing custom data configuration default\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140082549312272 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140082549312272 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140082549365648 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nReusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)\r\n12/12/2020 15:38:44 - INFO - filelock - Lock 140082549365648 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nLoading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-6810ece2a440c3be.arrow\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549560848 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549560848 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\nUsing custom data configuration default\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549560848 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549560848 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549365200 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nReusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)\r\n12/12/2020 15:38:45 - INFO - filelock - Lock 140082549365200 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nLoading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-9a2822394a3a4e34.arrow\r\n12/12/2020 15:38:45 - INFO - seq2seq.metrics.metrics - selected metric <function build_compute_metrics_fn.<locals>.classification_metrics at 0x7f66b464cc20> for task boolq\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - ***** Running training *****\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Num examples = 10\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Num Epochs = 2\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Instantaneous batch size per device = 64\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Total train batch size (w. parallel, distributed & accumulation) = 64\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Gradient Accumulation steps = 1\r\n12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer - Total optimization steps = 2\r\n{'loss': 529.79443359375, 'learning_rate': 2e-05, 'epoch': 1.0} \r\n100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2.37it/s]12/12/2020 15:38:46 - INFO - seq2seq.trainers.trainer - \r\n\r\nTraining completed. Do not forget to share your model on huggingface.co/models =)\r\n\r\n\r\n{'epoch': 2.0} \r\n100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00, 2.43it/s]\r\n12/12/2020 15:38:46 - INFO - seq2seq.trainers.trainer - Saving model checkpoint to outputs/test\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079084929680 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079084929680 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock\r\nUsing custom data configuration default\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079084929360 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079084929360 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079085355216 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nReusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)\r\n12/12/2020 15:38:59 - INFO - filelock - Lock 140079085355216 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock\r\nLoading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-164dd1d57e9fa69a.arrow\r\n12/12/2020 15:38:59 - INFO - seq2seq.metrics.metrics - selected metric <function build_compute_metrics_fn.<locals>.classification_metrics at 0x7f66b40c67a0> for task boolq\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - ***** Running training *****\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Num examples = 1\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Num Epochs = 2\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Instantaneous batch size per device = 64\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Total train batch size (w. parallel, distributed & accumulation) = 64\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Gradient Accumulation steps = 1\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Total optimization steps = 2\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Continuing training from checkpoint, will skip to saved global_step\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Continuing training from epoch 2\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Continuing training from global step 2\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Will skip the first 0 steps in the first epoch\r\n 0%| | 0/2 [00:00<?, ?it/s]12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - \r\n\r\nTraining completed. Do not forget to share your model on huggingface.co/models =)\r\n\r\n\r\n{'epoch': 2.0} \r\n 0%| | 0/2 [00:00<?, ?it/s]\r\n12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer - Saving model checkpoint to outputs/finetune-adapter/test-n-1-lr-1e-02-e-20/boolq\r\n12/12/2020 15:39:07 - INFO - seq2seq.utils.utils - using task specific params for boolq: {'max_length': 3}\r\n12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer - ***** Running Evaluation *****\r\n12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer - Num examples = 3269\r\n12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer - Batch size = 64\r\n100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 52/52 [00:12<00:00, 4.86it/s][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): \r\nterminate called after throwing an instance of 'google::protobuf::FatalException'\r\n what(): CHECK failed: (index) >= (0): \r\nAborted\r\n```\r\n\r\n\r\n\r\n",
"solved see https://github.com/huggingface/transformers/issues/9079?_pjax=%23js-repo-pjax-container ",
"Hii please follow me"
] | 2020-12-08T09:44:15Z | 2020-12-12T19:36:22Z | 2020-12-12T16:22:36Z |
CONTRIBUTOR
| null | null | null | null |
Hi
I am getting this error when evaluating on wmt16-ro-en using finetune_trainer.py of huggingface repo. thank for your help
{'epoch': 20.0}
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [00:16<00:00, 1.22it/s]
12/08/2020 10:41:19 - INFO - seq2seq.trainers.trainer - Saving model checkpoint to outputs/experiment/joint/finetune/lr-2e-5
12/08/2020 10:41:24 - INFO - __main__ - {'wmt16-en-ro': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1998), 'qnli': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 5462), 'scitail': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1303)}
12/08/2020 10:41:24 - INFO - __main__ - *** Evaluate ***
12/08/2020 10:41:24 - INFO - seq2seq.utils.utils - using task specific params for wmt16-en-ro: {'max_length': 300, 'num_beams': 4}
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - ***** Running Evaluation *****
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Num examples = 1998
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer - Batch size = 64
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 32/32 [00:37<00:00, 1.19s/it][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0):
terminate called after throwing an instance of 'google::protobuf::FatalException'
what(): CHECK failed: (index) >= (0):
Aborted
|
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| 759,278,758 |
MDU6SXNzdWU3NTkyNzg3NTg=
| 1,285 |
boolq does not work
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[
"here is the minimal code to reproduce\r\n\r\n`datasets>>> datasets.load_dataset(\"boolq\", \"train\")\r\n\r\nthe errors\r\n\r\n```\r\n`cahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\nUsing custom data configuration train\r\nDownloading and preparing dataset boolq/train (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /idiap/temp/rkarimi/cache_home_1/datasets/boolq/train/0.1.0/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11...\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py\", line 611, in load_dataset\r\n ignore_verifications=ignore_verifications,\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 476, in download_and_prepare\r\n dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 531, in _download_and_prepare\r\n split_generators = self._split_generators(dl_manager, **split_generators_kwargs)\r\n File \" /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/boolq/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11/boolq.py\", line 74, in _split_generators\r\n downloaded_files = dl_manager.download_custom(urls_to_download, tf.io.gfile.copy)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py\", line 149, in download_custom\r\n custom_download(url, path)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/tensorflow/python/lib/io/file_io.py\", line 516, in copy_v2\r\n compat.path_to_bytes(src), compat.path_to_bytes(dst), overwrite)\r\n\r\n\r\n\r\n```",
"This has been fixed by #881 \r\nthis fix will be available in the next release soon.\r\n\r\nIf you don't want to wait for the release you can actually load the latest version of boolq by specifying `script_version=\"master\"` in `load_dataset`",
"thank you this solved this issue, for now seems to work, thanks "
] | 2020-12-08T09:28:47Z | 2020-12-08T09:47:10Z | 2020-12-08T09:47:10Z |
CONTRIBUTOR
| null | null | null | null |
Hi
I am getting this error when trying to load boolq, thanks for your help
ts_boolq_default_0.1.0_2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11.lock
Traceback (most recent call last):
File "finetune_t5_trainer.py", line 274, in <module>
main()
File "finetune_t5_trainer.py", line 147, in main
for task in data_args.tasks]
File "finetune_t5_trainer.py", line 147, in <listcomp>
for task in data_args.tasks]
File "/remote/idiap.svm/user.active/rkarimi/dev/ruse/seq2seq/tasks/tasks.py", line 58, in get_dataset
dataset = self.load_dataset(split=split)
File "/remote/idiap.svm/user.active/rkarimi/dev/ruse/seq2seq/tasks/tasks.py", line 54, in load_dataset
return datasets.load_dataset(self.task.name, split=split)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py", line 611, in load_dataset
ignore_verifications=ignore_verifications,
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 476, in download_and_prepare
dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py", line 531, in _download_and_prepare
split_generators = self._split_generators(dl_manager, **split_generators_kwargs)
File " /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/boolq/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11/boolq.py", line 74, in _split_generators
downloaded_files = dl_manager.download_custom(urls_to_download, tf.io.gfile.copy)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py", line 149, in download_custom
custom_download(url, path)
File "/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/tensorflow/python/lib/io/file_io.py", line 516, in copy_v2
compat.path_to_bytes(src), compat.path_to_bytes(dst), overwrite)
tensorflow.python.framework.errors_impl.AlreadyExistsError: file already exists
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Update coqa dataset url
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`datasets.stanford.edu` is invalid.
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Add dutch book review dataset
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"> Really cool thanks !\r\n> \r\n> I left some (minor) comments\r\n\r\nThank you for your comments! 👍 I went ahead and improved the dataset card using your suggestions and some tweaks of my own. I hope you like it! 😄"
] | 2020-12-08T08:50:48Z | 2020-12-09T20:21:58Z | 2020-12-09T17:25:25Z |
CONTRIBUTOR
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- Name: Dutch Book Review Dataset (DBRD)
- Description: The DBRD (pronounced dee-bird) dataset contains over 110k book reviews along with associated binary sentiment polarity labels and is intended as a benchmark for sentiment classification in Dutch.
- Paper: https://arxiv.org/abs/1910.00896
- Data: https://github.com/benjaminvdb/DBRD
- Motivation: A large (real-life) dataset of Dutch book reviews and sentiment polarity (positive/negative), based on the associated rating.
Checks
- [x] Create the dataset script /datasets/dbrd/dbrd.py using the template
- [x] Fill the _DESCRIPTION and _CITATION variables
- [x] Implement _info(), _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 thaiqa_squad
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Example format is a little different from SQuAD since `thaiqa` always have one answer per question so I added a check to convert answers to lists if they are not already one to future-proof additional questions that might have multiple answers.
`thaiqa_squad` is an open-domain, extractive question answering dataset (4,000 questions in `train` and 74 questions in `dev`) in [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format, originally created by [NECTEC](https://www.nectec.or.th/en/) from Wikipedia articles and adapted to [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) format by [PyThaiNLP](https://github.com/PyThaiNLP/).
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adding hybrid_qa
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Adding HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data
https://github.com/wenhuchen/HybridQA
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disaster response messages dataset
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[
"I have added the Readme.md as well, the PR is ready for review. \r\n\r\nThank you ",
"Hi @lhoestq I have updated the code and files. Please if you could check once.\r\n\r\nThank you"
] | 2020-12-08T07:27:16Z | 2020-12-09T16:21:57Z | 2020-12-09T16:21:57Z |
CONTRIBUTOR
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[
"Updated with Translation feature type. Working on dataset tags and README",
"merging since the CI is fixed on master"
] | 2020-12-08T06:28:47Z | 2020-12-14T13:41:17Z | 2020-12-14T13:41:17Z |
CONTRIBUTOR
| null | null | 0 |
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Dataset link : https://figshare.com/articles/ParaPat_The_Multi-Million_Sentences_Parallel_Corpus_of_Patents_Abstracts/12627632
Working on README.md currently
|
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Craigslist bargains
|
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[
"Seeing this in the CircleCI builds, this is what I was originally getting before I started messing around with the download URLS to try to fix this:\r\n\r\n`FileNotFoundError: [Errno 2] No such file or directory: '/tmp/tmpwvji917g/extracted/d6185140afb24ad8fee67392100a478269cba286b0d88915a137fdf88872de14/dummy_data/train__VARIABLE_MISUSE__SStuB.txt-00001-of-00300'`\r\n\r\nCould this be because of the files in my `dummy_data.zip`? I had to manually create it, and it looked like the test was looking for the following files, so I created the `.zip` with this structure:\r\n\r\n```\r\nArchive: dummy_data.zip\r\n creating: dummy_data/\r\n inflating: dummy_data/blobtest \r\n inflating: dummy_data/parsed.jsontrain \r\n inflating: dummy_data/parsed.jsonvalidation \r\n```",
"Going to close this out and link to a new (cleaner) PR"
] | 2020-12-08T01:45:55Z | 2020-12-09T00:46:15Z | 2020-12-09T00:46:15Z |
CONTRIBUTOR
| null | null | 0 |
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`craigslist_bargains` dataset from [here](https://worksheets.codalab.org/worksheets/0x453913e76b65495d8b9730d41c7e0a0c/)
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add One Million Posts Corpus
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"merging since the CI is fixed on master"
] | 2020-12-08T00:50:08Z | 2020-12-11T18:28:18Z | 2020-12-11T18:28:18Z |
CONTRIBUTOR
| null | null | 0 |
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- **Name:** One Million Posts Corpus
- **Description:** The “One Million Posts” corpus is an annotated data set consisting of user comments posted to an Austrian newspaper website (in German language).
- **Paper:** https://dl.acm.org/doi/10.1145/3077136.3080711
- **Data:** https://github.com/OFAI/million-post-corpus
- **Motivation:** Big German (real-life) dataset containing different annotations around forum moderation with expert annotations.
### 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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Yoruba GV NER added
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"Thank you. Okay, I will add the dataset card."
] | 2020-12-08T00:31:38Z | 2020-12-08T23:25:28Z | 2020-12-08T23:25:28Z |
CONTRIBUTOR
| null | null | 0 |
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I just added Yoruba GV NER dataset from this paper https://www.aclweb.org/anthology/2020.lrec-1.335/
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oclar-dataset
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[
"merging since the CI is fixed on master"
] | 2020-12-07T23:56:45Z | 2020-12-09T15:36:08Z | 2020-12-09T15:36:08Z |
CONTRIBUTOR
| null | null | 0 |
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Opinion Corpus for Lebanese Arabic Reviews (OCLAR) corpus is utilizable for Arabic sentiment classification on reviews, including hotels, restaurants, shops, and others. : [homepage](http://archive.ics.uci.edu/ml/datasets/Opinion+Corpus+for+Lebanese+Arabic+Reviews+%28OCLAR%29#)
|
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Created wiki_movies dataset.
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[
"looks like your PR includes changes about many other files than the ones for wiki_movies\r\n\r\nCan you create another branch and another PR please ?",
"I'm happy to. What's the best way to do that (sorry, I'm new to PRs etc.)?",
"Sure !\r\n\r\nFirst please save your new dataset files somewhere.\r\nThen you can do in this order:\r\n```\r\ngit checkout master\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push\r\ngit checkout -b my-new-branch-name\r\n```\r\nThis will create a new branch from the updated master branch.\r\nThen you can re-add your files and commit + push them\r\n\r\nOnce it's done you should be able to create a new PR using your new branch :) ",
"Done!",
"closing in favor of #1485 "
] | 2020-12-07T23:38:54Z | 2020-12-14T13:56:49Z | 2020-12-14T13:56:49Z |
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First PR (ever). Hopefully this movies dataset is useful to others!
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Psc
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SMS Spam Dataset
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Hi :) I added this [SMS Spam Dataset](http://archive.ics.uci.edu/ml/datasets/SMS+Spam+Collection)
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add DFKI SmartData Corpus
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- **Name:** DFKI SmartData Corpus
- **Description:** DFKI SmartData Corpus is a dataset of 2598 German-language documents which has been annotated with fine-grained geo-entities, such as streets, stops and routes, as well as standard named entity types.
- **Paper:** https://www.dfki.de/fileadmin/user_upload/import/9427_lrec_smartdata_corpus.pdf
- **Data:** https://github.com/DFKI-NLP/smartdata-corpus
- **Motivation:** Contains fine-grained NER labels for German.
### 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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Adding OneStopEnglish corpus dataset
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[
"Hi @lhoestq, thanks for the review.\r\nI have made all the changes, PTAL! :) "
] | 2020-12-07T22:05:11Z | 2020-12-09T18:43:38Z | 2020-12-09T15:33:53Z |
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This PR adds OneStopEnglish Corpus containing texts classified into reading levels (elementary, intermediate, advance) for automatic readability assessment and text simplification.
Link to the paper: https://www.aclweb.org/anthology/W18-0535.pdf
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new pr for Turkish NER
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"Can you run `make style` to fix the code format ?\r\n\r\nAlso it looks like the file `file_downloaded/TWNERTC_TC_Coarse Grained NER_DomainIndependent_NoiseReduction.zip/TWNERTC_TC_Coarse Grained NER_DomainIndependent_NoiseReduction.DUMP` is missing inside the dummy_data.zip\r\n\r\n\r\n(note that `TWNERTC_TC_Coarse Grained NER_DomainIndependent_NoiseReduction.zip` is a directory name, not an actual zip file)",
"Hi Quentin, thank you for your patience with me. I've fixed the preprocessing pipeline, got this very weird error that Yacine told me to push. I've pushed it and after I'll find out that it will work, I will have my final pr on styling.",
"looks like you removed the dataset script file in your latest commit, is it expected ?"
] | 2020-12-07T21:40:26Z | 2020-12-09T13:45:05Z | 2020-12-09T13:45:05Z |
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Has part
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"merging since the CI is fixed on master"
] | 2020-12-07T20:32:03Z | 2020-12-11T18:25:42Z | 2020-12-11T18:25:42Z |
CONTRIBUTOR
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removing unzipped hansards dummy data
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MEMBER
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which were added by mistake
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Add CovidQA dataset
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"It seems to share the same name as this dataset: https://openreview.net/forum?id=JENSKEEzsoU",
"> It seems to share the same name as this dataset: https://openreview.net/forum?id=JENSKEEzsoU\r\n\r\nyou're right it can be confusing. I'll add the organization/research group for clarity: `covid_qa_castorini`. I added the dataset you shared as `covid_qa_deepset` in another PR (#1182) ",
"Thanks for avoiding the name collision !"
] | 2020-12-07T17:06:51Z | 2020-12-08T17:02:26Z | 2020-12-08T17:02:26Z |
CONTRIBUTOR
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This PR adds CovidQA, a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle’s COVID-19 Open Research Dataset Challenge.
Link to the paper: https://arxiv.org/pdf/2004.11339.pdf
Link to the homepage: https://covidqa.ai
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enriched webnlg dataset rebase
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"I've removed the `en` within `de` and reciprocally; but I don't think I will be able to thin it more than this. (Edit: ignore the close, I missclicked !)"
] | 2020-12-07T17:05:45Z | 2020-12-09T17:00:29Z | 2020-12-09T17:00:27Z |
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Rebase of #1206 !
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Added kannada news headlines classification dataset.
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"Hi! Let me know if any more comments! Will fix it! :-)"
] | 2020-12-07T16:35:37Z | 2020-12-10T14:30:55Z | 2020-12-09T18:01:31Z |
CONTRIBUTOR
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Manual Download of a kaggle dataset. Mostly followed process as ms_terms.
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For more information: https://www.aclweb.org/anthology/D13-1155.pdf
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[
"looks like this PR has changes to many files other than the ones for `NewsPH`\r\n\r\nCan you create another branch and another PR please ?"
] | 2020-12-07T15:17:53Z | 2020-12-08T16:27:15Z | 2020-12-08T16:27:15Z |
NONE
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Added the raw version of the NewsPH dataset, which was used to automatically generate the NewsPH-NLI corpus. Dataset of news articles in Filipino from mainstream Philippine news sites on the internet. Can be used as a language modeling dataset or to reproduce the NewsPH-NLI dataset.
Paper: https://arxiv.org/abs/2010.11574
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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Add KorQPair dataset
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[
"dummy data is missing",
"Hey @cceyda, thanks for pointing that out. I thought I'd added it, but seems like that wasn't the case. Just pushed a new commit with the dummy data."
] | 2020-12-07T14:33:57Z | 2021-12-29T00:49:40Z | 2020-12-08T15:11:41Z |
CONTRIBUTOR
| null | null | 0 |
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This PR adds a [Korean paired question dataset](https://github.com/songys/Question_pair) containing labels indicating whether two questions in a given pair are semantically identical. This dataset was used to evaluate the performance of [KoGPT2](https://github.com/SKT-AI/KoGPT2#subtask-evaluations) on a phrase detection downstream task.
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arXiv dataset added
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[
"Need help"
] | 2020-12-07T14:23:33Z | 2020-12-08T14:07:15Z | 2020-12-08T14:07:15Z |
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Add Swahili news classification dataset
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Add Swahili news classification dataset
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Adding LiMiT: The Literal Motion in Text Dataset
https://github.com/ilmgut/limit_dataset
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[doc] nlp/viewer ➡️datasets/viewer
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cc @srush
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Added WikiText-TL-39
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[
"looks like this PR also includes changes about another dataset `covid_qa_deepset`\r\n\r\nCould you create another branch and another PR that only includes the changes for the wikitext-tl-39 dataset ?"
] | 2020-12-07T13:43:48Z | 2020-12-08T16:00:58Z | 2020-12-08T16:00:58Z |
NONE
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This PR adds the WikiText-TL-39 Filipino Language Modeling dataset.
Paper: https://arxiv.org/abs/1907.00409
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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add thainer
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[] | 2020-12-07T13:41:54Z | 2020-12-08T14:44:49Z | 2020-12-08T14:44:49Z |
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ThaiNER (v1.3) is a 6,456-sentence named entity recognition dataset created from expanding the 2,258-sentence
[unnamed dataset](http://pioneer.chula.ac.th/~awirote/Data-Nutcha.zip) by
[Tirasaroj and Aroonmanakun (2012)](http://pioneer.chula.ac.th/~awirote/publications/).
It is used to train NER taggers in [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp).
The NER tags are annotated by [Tirasaroj and Aroonmanakun (2012)]((http://pioneer.chula.ac.th/~awirote/publications/))
for 2,258 sentences and the rest by [@wannaphong](https://github.com/wannaphong/).
The POS tags are done by [PyThaiNLP](https://github.com/PyThaiNLP/pythainlp)'s `perceptron` engine trained on `orchid_ud`.
[@wannaphong](https://github.com/wannaphong/) is now the only maintainer of this dataset.
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| 1,252 |
Add Naver sentiment movie corpus
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[] | 2020-12-07T13:33:45Z | 2020-12-08T14:32:33Z | 2020-12-08T14:21:37Z |
CONTRIBUTOR
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Supersedes #1168
> This PR adds the [Naver sentiment movie corpus](https://github.com/e9t/nsmc), a dataset containing Korean movie reviews from Naver, the most commonly used search engine in Korea. This dataset is often used to benchmark models on Korean NLP tasks, as seen in [this paper](https://www.aclweb.org/anthology/2020.lrec-1.199.pdf).
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Add Wiki Atomic Edits Dataset (43M edits)
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"@lhoestq fixed :)"
] | 2020-12-07T13:23:08Z | 2020-12-14T10:05:01Z | 2020-12-14T10:05:00Z |
CONTRIBUTOR
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