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MDU6SXNzdWU3NTkyNzg3NTg=
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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 "
] | 1,607,419,727,000
| 1,607,420,830,000
| 1,607,420,830,000
|
CONTRIBUTOR
|
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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CONTRIBUTOR
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`datasets.stanford.edu` is invalid.
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MDExOlB1bGxSZXF1ZXN0NTM0Mjg4MDg2
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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! 😄"
] | 1,607,417,448,000
| 1,607,545,318,000
| 1,607,534,725,000
|
CONTRIBUTOR
|
- 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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MDExOlB1bGxSZXF1ZXN0NTM0MjQ4NzI5
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|
add thaiqa_squad
|
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[] | 1,607,415,278,000
| 1,607,452,578,000
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CONTRIBUTOR
|
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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MDExOlB1bGxSZXF1ZXN0NTM0MjQ0MTA1
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adding hybrid_qa
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[] | 1,607,415,019,000
| 1,607,450,968,000
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MEMBER
|
Adding HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data
https://github.com/wenhuchen/HybridQA
|
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MDExOlB1bGxSZXF1ZXN0NTM0MTk2MDc0
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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"
] | 1,607,412,436,000
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CONTRIBUTOR
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added para_pat
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[
"Updated with Translation feature type. Working on dataset tags and README",
"merging since the CI is fixed on master"
] | 1,607,408,927,000
| 1,607,953,277,000
| 1,607,953,277,000
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CONTRIBUTOR
|
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"
] | 1,607,391,955,000
| 1,607,474,775,000
| 1,607,474,775,000
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CONTRIBUTOR
|
`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"
] | 1,607,388,608,000
| 1,607,711,298,000
| 1,607,711,298,000
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CONTRIBUTOR
|
- **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."
] | 1,607,387,498,000
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| 1,607,469,928,000
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CONTRIBUTOR
|
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"
] | 1,607,385,405,000
| 1,607,528,168,000
| 1,607,528,168,000
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CONTRIBUTOR
|
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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MDExOlB1bGxSZXF1ZXN0NTM0MDE4MjQ2
| 1,273
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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 "
] | 1,607,384,334,000
| 1,607,954,209,000
| 1,607,954,209,000
|
CONTRIBUTOR
|
First PR (ever). Hopefully this movies dataset is useful to others!
|
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MDExOlB1bGxSZXF1ZXN0NTM0MDA4NTg4
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SMS Spam Dataset
|
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[] | 1,607,383,086,000
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CONTRIBUTOR
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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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MDExOlB1bGxSZXF1ZXN0NTM0MDAyODIz
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add DFKI SmartData Corpus
|
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[] | 1,607,382,228,000
| 1,607,449,283,000
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CONTRIBUTOR
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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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| 1,269
|
Adding OneStopEnglish corpus dataset
|
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[
"Hi @lhoestq, thanks for the review.\r\nI have made all the changes, PTAL! :) "
] | 1,607,378,711,000
| 1,607,539,418,000
| 1,607,528,033,000
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CONTRIBUTOR
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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 ?"
] | 1,607,377,226,000
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Has part
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[
"merging since the CI is fixed on master"
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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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MDExOlB1bGxSZXF1ZXN0NTMzODE4NjY0
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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 !"
] | 1,607,360,811,000
| 1,607,446,946,000
| 1,607,446,946,000
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CONTRIBUTOR
|
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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MDExOlB1bGxSZXF1ZXN0NTMzODE4MDM2
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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 !)"
] | 1,607,360,745,000
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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! :-)"
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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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Added NewsPH Raw Dataset
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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 ?"
] | 1,607,354,273,000
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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."
] | 1,607,351,637,000
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CONTRIBUTOR
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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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Add Swahili news classification dataset
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Add Swahili news classification dataset
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adding LiMiT 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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[] | 1,607,349,521,000
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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 ?"
] | 1,607,348,628,000
| 1,607,443,258,000
| 1,607,443,258,000
|
NONE
|
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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[] | 1,607,348,514,000
| 1,607,438,689,000
| 1,607,438,689,000
|
CONTRIBUTOR
|
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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MDExOlB1bGxSZXF1ZXN0NTMzNjczMDcx
| 1,252
|
Add Naver sentiment movie corpus
|
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[] | 1,607,348,025,000
| 1,607,437,953,000
| 1,607,437,297,000
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CONTRIBUTOR
|
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 :)"
] | 1,607,347,388,000
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MEMBER
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|
added Nergrit dataset
|
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[] | 1,607,346,372,000
| 1,607,438,009,000
| 1,607,438,009,000
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CONTRIBUTOR
|
Nergrit Corpus is a dataset collection for Indonesian Named Entity Recognition, Statement Extraction, and Sentiment Analysis. This PR is only for the Named Entity Recognition.
|
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MDExOlB1bGxSZXF1ZXN0NTMzNjQwNjA1
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Add doc2dial dataset
|
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[
"It not always practical to use nested `Sequence`. If you have troubles with sequence you can use lists instead. \r\n\r\nFor example\r\n```python\r\n\r\nfeatures=datasets.Features(\r\n {\r\n \"dial_id\": datasets.Value(\"string\"),\r\n \"doc_id\": datasets.Value(\"string\"),\r\n \"domain\": datasets.Value(\"string\"),\r\n \"turns\": [\r\n {\r\n \"turn_id\": datasets.Value(\"int32\"),\r\n \"role\": datasets.Value(\"string\"),\r\n \"da\": datasets.Value(\"string\"),\r\n \"reference\": [\r\n {\r\n \"keys\" : datasets.Value(\"string\"),\r\n \"values\": datasets.Value(\"string\"), \r\n }\r\n\r\n ],\r\n \"utterance\": datasets.Value(\"string\"),\r\n }\r\n ],\r\n }\r\n),\r\n```\r\n\r\nthis way `turns` will be a list of dict, and the \"reference\" key of `turns` will be a list of dict as well",
"No problem thanks for all your help getting this to the final stages! Added .gitignore, removed .lock and applied the changes you asked for."
] | 1,607,344,749,000
| 1,607,962,634,000
| 1,607,962,634,000
|
CONTRIBUTOR
|
### Doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset v0.9
Once complete this will add the [Doc2dial](https://doc2dial.github.io/data.html) dataset from the generic data sets list.
|
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|
Update step-by-step guide about the dataset cards
|
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[] | 1,607,343,132,000
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MEMBER
|
Small update in the step-by-step guide about the dataset cards to indicate it can be created and completing while exploring the dataset.
|
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Adding indonlu dataset
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"looks like this PR includes changes about many files other than the ones for IndoNLU\r\nCould you create another branch and another PR please ?",
"> looks like this PR includes changes about many files other than the ones for IndoNLU\r\n> Could you create another branch and another PR please ?\r\n\r\nOkay I'll make it"
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IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for Bahasa Indonesia. It contains 12 datasets.
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Add Google Turkish Treebank Dataset
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Add Google Noun Verb Dataset
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adding bprec
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"looks like this PR includes changes to many files other than the ones related to bprec\r\nCan you create another branch and another PR please ?",
"> looks like this PR includes changes to many files other than the ones related to bprec\r\n> Can you create another branch and another PR please ?\r\n\r\nYes, I realized I messed this one up, learning my way :) I'll close this one and open another hopefully clean PR :) Thanks!"
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MDExOlB1bGxSZXF1ZXN0NTMzNTQ1OTQ0
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Opus elhuyar dataset for MT task having languages pair in Spanish to Basque
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Opus elhuyar dataset for MT task having languages pair in Spanish to Basque
More info : http://opus.nlpl.eu/Elhuyar.php
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Multi Domain Sentiment Analysis Dataset (MDSA)
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[
"can you also run `make style` to format the code ?",
"I'll come back to this one in sometime :) @lhoestq ",
"Also if you would use `xml.etree.ElementTree` to parse the XML it would be awesome, because right now you're using an external dependency `xmltodict `",
"> Also if you would use xml.etree.ElementTree to parse the XML it would be awesome, because right now you're using an external dependency xmltodict\r\n\r\nIts pseudo xml so elementtree fails. xmltodict seems to be working quite good for this. do we have examples of pseudo xml datasets?",
"for the other pseudo xml the text is parsed manually",
"Can you add `xmltodict` to the test dependencies in setup.py please to fix the CI please ?",
"Also can you add the dataset card with the tags and run `make style` ?",
"Hi :) have you had a chance to fix the test dependency and apply `make style` ?\r\n\r\nFeel fee to ping me when it's ready for a review",
"Thanks for your contribution, @abhishekkrthakur. Are you still interested in adding this dataset?\r\n\r\nWe are removing the dataset scripts from this GitHub repo and moving them to the Hugging Face Hub: https://huggingface.co/datasets\r\n\r\nWe would suggest you create this dataset there. Please, feel free to tell us if you need some help."
] | 1,607,335,035,000
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add yelp_review_full dataset
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"Moved to https://github.com/huggingface/datasets/pull/1315"
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CONTRIBUTOR
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This corresponds to the Yelp-5 requested in https://github.com/huggingface/datasets/issues/353
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adding poem_sentiment
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Adding poem_sentiment dataset.
https://github.com/google-research-datasets/poem-sentiment
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Add AmbigQA dataset
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[] | 1,607,332,039,000
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| 1,607,434,732,000
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CONTRIBUTOR
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# AmbigQA: Answering Ambiguous Open-domain Questions Dataset
Adding the [AmbigQA](https://nlp.cs.washington.edu/ambigqa/) dataset as part of the sprint 🎉 (from Open dataset list for Dataset sprint)
Added both the light and full versions (as seen on the dataset homepage)
The json format changes based on the value of one 'type' field, so I set the unavailable field to an empty list. This is explained in the README -> Data Fields
```py
train_light_dataset = load_dataset('./datasets/ambig_qa',"light",split="train")
val_light_dataset = load_dataset('./datasets/ambig_qa',"light",split="validation")
train_full_dataset = load_dataset('./datasets/ambig_qa',"full",split="train")
val_full_dataset = load_dataset('./datasets/ambig_qa',"full",split="validation")
for example in train_light_dataset:
for i,t in enumerate(example['annotations']['type']):
if t =='singleAnswer':
# use the example['annotations']['answer'][i]
# example['annotations']['qaPairs'][i] - > is []
print(example['annotations']['answer'][i])
else:
# use the example['annotations']['qaPairs'][i]
# example['annotations']['answer'][i] - > is []
print(example['annotations']['qaPairs'][i])
```
- [x] All tests passed
- [x] Added dummy data
- [x] Added data card (as much as I could)
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Opus finlex dataset of language pair Finnish and Swedish
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[] | 1,607,327,637,000
| 1,607,434,233,000
| 1,607,434,233,000
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CONTRIBUTOR
|
Added Opus_finlex dataset of language pair Finnish and Swedish
More info : http://opus.nlpl.eu/Finlex.php
|
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Wino bias
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[
"Closing this PR because of messed up history and opening another one after discussion with Quentin Lhoest.\r\n"
] | 1,607,325,162,000
| 1,607,633,292,000
| 1,607,633,281,000
|
CONTRIBUTOR
|
The PR will fail circleCi tests because of the requirement of manual loading of data. Fresh PR because of messed up history of the previous one.
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Added ade_corpus_v2, with 3 configs for relation extraction and classification task
|
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[
"@lhoestq I have added the tags they are in separate files for 3 different configs",
"@lhoestq thanks for the review I added your suggested changes.",
"merging since the CI is fixed on master"
] | 1,607,324,714,000
| 1,607,968,154,000
| 1,607,968,154,000
|
CONTRIBUTOR
|
Adverse Drug Reaction Data: ADE-Corpus-V2 dataset added configs for different tasks with given data
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Add Curiosity Dialogs Dataset
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[
"@lhoestq I tried manually creating the dummy files. But unfortunately it was raising an error during testing the dummy data (regarding JSON parsing).\r\n\r\nThe JSONs are pretty big so I cannot actually open it without crashing the text editor.\r\n\r\n Do you have any suggestions?",
"@lhoestq I have made all the changes you mentioned."
] | 1,607,320,860,000
| 1,608,471,249,000
| 1,607,525,429,000
|
CONTRIBUTOR
|
Add Facebook [Curiosity Dialogs](https://github.com/facebookresearch/curiosity) Dataset.
|
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Add Grail QA dataset
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[] | 1,607,320,005,000
| 1,607,432,599,000
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CONTRIBUTOR
|
For more information: https://dki-lab.github.io/GrailQA/
|
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MDExOlB1bGxSZXF1ZXN0NTMzMzQzMzAz
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Add Urdu Sentiment Corpus (USC)
|
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| 1,607,364,316,000
| 1,607,359,403,000
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@lhoestq opened a clean PR containing only relevant files.
old PR #1140
|
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Add Urdu fake news dataset
|
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"merging since the CI is fixed on master"
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| 1,607,364,295,000
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CONTRIBUTOR
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@lhoestq opened a clean PR containing only relevant files.
old PR #1125
|
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Muchocine - Spanish movie reviews dataset
|
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[
"Hi @mapmeld !\r\nhave you had a chance to take a look at my suggestions ?\r\n\r\nFeel free to ping me if you have questions or when you're ready for a review",
"@lhoestq unfortunately I don't have any more information about where the dataset comes from",
"It's fine, you can just add the sections titles back and leave the content with `[More Information Needed]`\r\n\r\n",
"added missing sections, updated the Python code ✅ "
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MDExOlB1bGxSZXF1ZXN0NTMzMjg1ODI2
| 1,228
|
add opus_100 dataset
|
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[
"done."
] | 1,607,296,644,000
| 1,607,525,640,000
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CONTRIBUTOR
|
This PR will add [opus100 dataset](http://opus.nlpl.eu/opus-100.php).
|
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readme: remove link to Google's responsible AI practices
|
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[] | 1,607,296,642,000
| 1,607,330,119,000
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CONTRIBUTOR
|
...maybe we'll find a company that reallly stands behind responsible AI practices ;)
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjc2OTU3
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Add menyo_20k_mt dataset
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[
"looks like your PR includes changes about many other files than the ones for menyo 20k mt\r\nCan you create another branch and another PR please ?",
"Yes, I will"
] | 1,607,292,975,000
| 1,607,628,134,000
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CONTRIBUTOR
|
Add menyo_20k_mt dataset
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjc1ODcx
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Add Winobias dataset
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[
"Will make another pull request with cleaner history"
] | 1,607,292,500,000
| 1,607,323,559,000
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CONTRIBUTOR
|
Pardon me for different commits with same message. There were conflicts after I rebased master while simultaneously pushing my changes to local repo, hence the duplicate entries.
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjY2Njg1
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adding conceptnet5
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"Thank you. I'll make those changes. but I'm having problems trying to push my changes to my fork\r\n",
"Hi, I've removed the TODO, and added a README.md. How do I push these changes?\r\n",
"Also, what docstring are you recommending?\r\n",
"> Hi, I've removed the TODO, and added a README.md. How do I push these changes?\r\n\r\nyou can just commit and push your changes to the same branch as your first commit.",
"@ghomasHudson I've tried it but still getting code quality error. I've removed all blank lines, etc. required by flake8. Don't know what else to do",
"> @ghomasHudson I've tried it but still getting code quality error. I've removed all blank lines, etc. required by flake8. Don't know what else to do\r\n\r\nDid you run `make style` before committing? When I run it, it fixes some things (e.g. Splitting line 96 which is currently too long).",
"I think @yjernite is looking into this. I did \"make style\" but nothing happens",
"looks like your PR includes changes about many other files than the ones related to conceptnet5\r\n\r\ncould you create another branch and another PR please ?",
"@lhoestq I'm not sure what I did wrong. What did I push that wasn't conceptnet5? How do I see this?\r\n\r\n did this\r\n\r\nmake style\r\nflake8 datasets\r\ngit add datasets/<your_dataset_name>\r\ngit commit\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit pull\r\ngit push -u origin conceptnet5",
"Thanks for rebasing and force push :) ",
"Yeah! Thank you @lhoestq, @ghomasHudson and @yjernite !"
] | 1,607,288,813,000
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Adding the conceptnet5 and omcs txt files used to create the conceptnet5 dataset. Conceptne5 is a common sense dataset. More info can be found here: https://github.com/commonsense/conceptnet5/wiki
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🇸🇪 Added Swedish Reviews dataset for sentiment classification in Sw…
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perhaps: @lhoestq 🤗
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Add numeric fused head dataset
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[
"> Thanks for adding this @ghomasHudson!\r\n> I added some comments for some of the fields.\r\n> \r\n> Also, I'm not sure about this since I haven't used the library yet, but maybe it's worth adding the identification and resolution as two separate datasets?\r\n\r\nThanks for replying @yanaiela - I hope this will make your dataset more accessible to a wider audience - I've added the changes to the model card you suggested.\r\n\r\nIn terms of the identification and resolution tasks, I've currently added them as separate `splits` in huggingface/datasets so you can load identification like this:\r\n\r\n```\r\nimport datasets\r\ndataset = datasets.load_dataset(\"numeric_fused_head\", \"identification\")\r\nprint(dataset[\"train\"][0])\r\n>> {\"tokens\": [\"The\", \"quick\", \"brown\", \"fox\",....], \"start_index\": 11, \"end_index\": 12, \"label\": 0}\r\n```\r\nAnd resolution like this:\r\n\r\n```\r\nimport datasets\r\ndataset = datasets.load_dataset(\"numeric_fused_head\", \"resolution\")\r\nprint(dataset[\"train\"][0])\r\n>> {\"tokens\": [\"The\", \"quick\", \"brown\", \"fox\",....], \"head\": [\"AGE\"], \"anchors_indices\": [12], ...}\r\n```",
"I hope so too, thanks!\r\n\r\nRe the splits, that makes sense to me."
] | 1,607,287,613,000
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CONTRIBUTOR
|
Adding the [NFH: Numeric Fused Head](https://nlp.biu.ac.il/~lazary/fh/) dataset.
Everything looks sensible and I've included both the identification and resolution tasks. I haven't personally used this dataset in my research so am unable to specify what the default configuration / supervised keys should be.
I've filled out the basic info on the model card to the best of my knowledge but it's a little tricky to understand exactly what the fields represent.
Dataset author: @yanaiela
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Add HKCanCor
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[] | 1,607,286,727,000
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CONTRIBUTOR
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This PR adds the [Hong Kong Cantonese Corpus](http://compling.hss.ntu.edu.sg/hkcancor/), by [Luke and Wong 2015](http://compling.hss.ntu.edu.sg/hkcancor/data/LukeWong_Hong-Kong-Cantonese-Corpus.pdf).
The dummy data included here was manually created, as the original dataset uses a xml-like format (see a copy hosted [here](https://github.com/fcbond/hkcancor/blob/master/sample/d1_v.txt) for example) that requires a few processing steps.
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add Korean HateSpeech dataset
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[
"It looks like you forgot to `make style` (I forget it a lot too 🤦 )\r\n+ add dummy data",
"hi @cceyda 👋, thanks for the hint! it looks like i've run into some other errors though in `_split_generators` or `_generate_examples`. do you have any idea of what's wrong here? 😅",
"I get the same errors on another pr too, so it probably has something to do with circleci, waiting on help.",
"the `RemoteDatasetTest ` error on the CI is fixed on master so it's fine",
"merging since the CI is fixed on master"
] | 1,607,286,689,000
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Add Korean NER dataset
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[] | 1,607,285,946,000
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CONTRIBUTOR
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Supersedes #1177
> This PR adds the [Korean named entity recognition dataset](https://github.com/kmounlp/NER). This dataset has been used in many downstream tasks, such as training [KoBERT](https://github.com/SKTBrain/KoBERT) for NER, as seen in this [KoBERT-CRF implementation](https://github.com/eagle705/pytorch-bert-crf-ner).
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Add WMT20 MLQE 3 shared tasks
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[
"Thanks for the comments Quentin!\r\nI integrated them",
"It should be ok now!\r\nSorry I wasn't attentive enough.\r\n(tests are currently failing, I understand it's from other datasets)",
"merging since the CI is fixed on master"
] | 1,607,284,752,000
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3 tasks for the WMT 20 MLQE shared tasks -> 3 different datasets
(I re-created #1137 because it was too messy).
Note that in L199 `task3.py`, I used `logging.warning` to print some missing data in the train set.
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adding DataCommons fact checking
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[] | 1,607,284,572,000
| 1,608,135,768,000
| 1,608,135,768,000
|
MEMBER
|
Adding the data from: https://datacommons.org/factcheck/
Had to cheat a bit with the dummy data as the test doesn't recognize `.txt.gz`: had to rename uncompressed files with the `.gz` extension manually without actually compressing
|
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| 1,216
|
Add limit
|
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[
"My bad, didn't see this on the open dataset list. Closing this since it overlaps with PR#1256"
] | 1,607,283,978,000
| 1,607,413,931,000
| 1,607,413,931,000
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CONTRIBUTOR
|
This PR adds [LiMiT](https://github.com/ilmgut/limit_dataset), a dataset for literal motion classification/extraction by [Manotas et al., 2020](https://www.aclweb.org/anthology/2020.findings-emnlp.88.pdf).
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjUyNjUx
| 1,215
|
Add irc disentanglement
|
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|
[
"looks like this PR includes changes about many files other than the ones for irc_disentanglement\r\n\r\nCould you please create a new branch and create another PR please ?",
"closing in favor of #1586 "
] | 1,607,283,046,000
| 1,608,135,505,000
| 1,608,135,505,000
|
CONTRIBUTOR
|
added files for irc disentanglement dataset
was unable to test dummy data as a result of vpn/proxy issues
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjUyNTgx
| 1,214
|
adding medical-questions-pairs dataset
|
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[] | 1,607,283,012,000
| 1,607,524,973,000
| 1,607,524,973,000
|
CONTRIBUTOR
|
This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors.
Dataset : https://github.com/curai/medical-question-pair-dataset
Paper : https://drive.google.com/file/d/1CHPGBXkvZuZc8hpr46HeHU6U6jnVze-s/view
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MDExOlB1bGxSZXF1ZXN0NTMzMjM4NzEz
| 1,213
|
add taskmaster3
|
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[]
|
[
"(you were unlucky, my rule of thumb for reducing the dummy data is to check whether they're above 50KB and you're at 52KB ^^')",
"> (you were unlucky, my rule of thumb for reducing the dummy data is to check whether they're above 50KB and you're at 52KB ^^')\r\n\r\nOops :(\r\n\r\nThanks for the suggestion, will reduce the size"
] | 1,607,277,363,000
| 1,607,511,910,000
| 1,607,511,629,000
|
MEMBER
|
Adding Taskmaster-3 dataset
https://github.com/google-research-datasets/Taskmaster/tree/master/TM-3-2020.
The dataset structure almost same as original dataset with these two changes
1. In original dataset, each `apis` has a `args` filed which is a `dict` with variable keys, which represent the name and value of the args. Here converted that to a `list` of `dict` with keys `arg_name` and `arg_value`. For ex.
```python
args = {"name.movie": "Mulan", "name.theater": ": "Mountain AMC 16"}
```
becomes
```python
[
{
"arg_name": "name.movie",
"arg_value": "Mulan"
},
{
"arg_name": "name.theater",
"arg_value": "Mountain AMC 16"
}
]
```
2. Each `apis` has a `response` which is also a `dict` with variable keys representing response name/type and it's value. As above converted it to `list` of `dict` with keys `response_name` and `response_value`.
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjM1MTky
| 1,212
|
Add Sanskrit Classic texts in datasets
|
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[
"merging since the CI is fixed on master"
] | 1,607,275,891,000
| 1,607,367,848,000
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CONTRIBUTOR
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MDExOlB1bGxSZXF1ZXN0NTMzMjMxNDY3
| 1,211
|
Add large spanish corpus
|
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[] | 1,607,274,410,000
| 1,607,520,996,000
| 1,607,520,996,000
|
MEMBER
|
Adds a collection of Spanish corpora that can be useful for pretraining language models.
Following a nice suggestion from @yjernite we provide the user with three main ways to preprocess / load either
* the whole corpus (17GB!)
* one specific sub-corpus
* the whole corpus, but return a single split. this is useful if you want to cache the whole preprocessing step once and interact with individual sub-corpora
See the dataset card for more details.
Ready for review!
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjI2NDQ2
| 1,210
|
Add XSUM Hallucination Annotations Dataset
|
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|
[
"@lhoestq All necessary modifications have been done."
] | 1,607,272,819,000
| 1,608,471,296,000
| 1,608,137,831,000
|
CONTRIBUTOR
|
Adding Google [XSum Hallucination Annotations](https://github.com/google-research-datasets/xsum_hallucination_annotations) dataset.
|
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[AfriBooms] Dataset exists already
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[
"It's so cool seeing all these datasets fly by and see how they are still of interest. I did my internship at the research group of Liesbeth Augustinus et al. They're a very kind group of people!",
"merging since the CI is fixed on master"
] | 1,607,272,513,000
| 1,607,359,944,000
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When trying to add "AfriBooms": https://docs.google.com/spreadsheets/d/12ShVow0M6RavnzbBEabm5j5dv12zBaf0y-niwEPPlo4/edit#gid=1386399609 I noticed that the dataset exists already as a config of Universal Dependencies (universal_dependencies.py). I checked and the data exactly matches so that the new data link does not give any new data.
This PR improves the config's description a bit by linking to the paper.
|
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Add HKCanCor
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[] | 1,607,271,283,000
| 1,607,286,197,000
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CONTRIBUTOR
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(Apologies, didn't manage the branches properly and the PR got too messy. Going to open a new PR with everything in order)
|
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Add msr_genomics_kbcomp Dataset
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Adding Enriched WebNLG dataset
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[
"Nice :) \r\n\r\ncould you add the tags and also remove all the dummy data files that are not zipped ? The diff currently shows 800 files changes xD",
"Aaaaand it's rebase time - the new one is at #1264 !",
"closing this one since a new PR was created"
] | 1,607,268,980,000
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MEMBER
|
This pull requests adds the `en` and `de` versions of the [Enriched WebNLG](https://github.com/ThiagoCF05/webnlg) dataset
|
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MDExOlB1bGxSZXF1ZXN0NTMzMjA4NDI1
| 1,205
|
add lst20 with manual download
|
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[
"The pytest suite doesn't allow manual downloads so we just make sure that the `datasets-cli test` command to run without errors instead",
"@lhoestq Changes made. Thank you for the review. I've made some same mistakes for https://github.com/huggingface/datasets/pull/1253 too. Will fix them before review."
] | 1,607,266,150,000
| 1,607,531,590,000
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CONTRIBUTOR
|
passed on local:
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_lst20
```
Not sure how to test:
```
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_real_dataset_lst20
```
```
LST20 Corpus is a dataset for Thai language processing developed by National Electronics and Computer Technology Center (NECTEC), Thailand.
It offers five layers of linguistic annotation: word boundaries, POS tagging, named entities, clause boundaries, and sentence boundaries.
At a large scale, it consists of 3,164,002 words, 288,020 named entities, 248,181 clauses, and 74,180 sentences, while it is annotated with
16 distinct POS tags. All 3,745 documents are also annotated with one of 15 news genres. Regarding its sheer size, this dataset is
considered large enough for developing joint neural models for NLP.
Manually download at https://aiforthai.in.th/corpus.php
```
|
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adding meta_woz dataset
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Add Neural Code Search Dataset
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[
"> Really good thanks !\r\n> \r\n> I left a few comments\r\n\r\nThanks, resolved them :) ",
"looks like this PR includes changes about many other files than the ones for Code Search\r\n\r\ncan you create another branch and another PR please ?",
"> looks like this PR includes changes about many other files than the ones for Code Search\r\n> \r\n> can you create another branch and another PR please ?\r\n\r\nOkay sure"
] | 1,607,263,959,000
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| 1,202
|
Medical question pairs
|
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[] | 1,607,263,747,000
| 1,607,276,488,000
| 1,607,276,488,000
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CONTRIBUTOR
|
This dataset consists of 3048 similar and dissimilar medical question pairs hand-generated and labeled by Curai's doctors.
Dataset : https://github.com/curai/medical-question-pair-dataset
Paper : https://drive.google.com/file/d/1CHPGBXkvZuZc8hpr46HeHU6U6jnVze-s/view
**No splits added**
|
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adding medical-questions-pairs
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Update ADD_NEW_DATASET.md
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[] | 1,607,261,492,000
| 1,607,329,959,000
| 1,607,329,959,000
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CONTRIBUTOR
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Windows needs special treatment again: unfortunately adding `torch` to the requirements does not work well (crashing the installation). Users should first install torch manually and then continue with the other commands.
This issue arises all the time when adding torch as a dependency, but because so many novice users seem to participate in adding datasets, it may be useful to add an explicit note for Windows users to ensure that they do not run into issues.
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|
Turkish NER dataset, script works fine, couldn't generate dummy data
|
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[
"the .DUMP file looks like a txt with one example per line so adding `--match_text_files *.DUMP --n_lines 50` to the dummy generation command might work .",
"We can close this PR since a new PR was open at #1268 "
] | 1,607,256,003,000
| 1,608,135,204,000
| 1,608,135,204,000
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CONTRIBUTOR
|
I've written the script (Turkish_NER.py) that includes dataset. The dataset is a zip inside another zip, and it's extracted as .DUMP file. However, after preprocessing I only get .arrow file. After I ran the script with no error messages, I get .arrow file of dataset, LICENSE and dataset_info.json.
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Add ALT
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[
"the `RemoteDatasetTest ` erros in the CI are fixed on master so it's fine",
"used `Translation ` feature type and fixed few typos as you suggested.",
"Sorry, I made a mistake. please see new PR here. https://github.com/huggingface/datasets/pull/1436"
] | 1,607,253,930,000
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CONTRIBUTOR
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ALT dataset -- https://www2.nict.go.jp/astrec-att/member/mutiyama/ALT/
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add taskmaster-2
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[] | 1,607,252,718,000
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MEMBER
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Adding taskmaster-2 dataset.
https://github.com/google-research-datasets/Taskmaster/tree/master/TM-2-2020
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Add IWSLT'15 English-Vietnamese machine translation Data
|
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[
"Thanks ! feel free to ping me once you've added the tags in the dataset card :) ",
"merging since the CI is fixed on master"
] | 1,607,250,991,000
| 1,607,711,211,000
| 1,607,711,211,000
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CONTRIBUTOR
|
Preprocessed Dataset from IWSLT'15 English-Vietnamese machine translation: English-Vietnamese.
from https://nlp.stanford.edu/projects/nmt/data/iwslt15.en-vi/
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addition of py_ast
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[
"Hi @reshinthadithyan !\r\n\r\nAs mentioned on the Slack, it would be better in this case to parse the file lines into the following feature structure:\r\n```python\r\n\"ast\": datasets.Sequence(\r\n {\r\n \"type\": datasets.Value(\"string\"),\r\n \"value\": datasets.Value(\"string\"),\r\n \"children\": datasets.Sequence(datasets.Value(\"int32\")),\r\n },\r\n)\r\n```\r\n\r\nHere are a few more things to fix before we can move forward:\r\n- the class name needs to be the CamelCase equivalent of the script name, so here it will have to be `PyAst`\r\n- the `README.md` needs to have the tags at the top\r\n- The homepage/info list at the top should be in the same format as the template (added a suggestion)\r\n- You should add the dataset tags and field description to the README as described here: https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card\r\n\r\nGood luck, let us know if you need any help!",
"Hello @yjernite, changes have been made as we talked. Hope this would suffice. Thanks. Feel free to point out any room to improvement.",
"Good progress! Here's what still needs to be done:\r\n- first, you need to rebase to master for the tests to pass :)\r\n- the information in your `Data Fields` paragraph should go into `Data Instances`. Data fields should describe the fields one by one, as in e.g. https://github.com/huggingface/datasets/tree/master/datasets/eli5#data-fields\r\n- you still need to add the YAML tags obtained with the tagging app\r\n\r\nShould be good to go after that!",
"Hello @yjernite, changes as talked are being done.",
"Looks like this PR includes changes about many other files than the ones for py_ast\r\n\r\nCould you create another branch and another PR please ?"
] | 1,607,248,852,000
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CONTRIBUTOR
|
The dataset consists of parsed Parsed ASTs that were used to train and evaluate the DeepSyn tool.
The Python programs are collected from GitHub repositories
by removing duplicate files, removing project forks (copy of another existing repository)
,keeping only programs that parse and have at most 30'000 nodes in the AST and
we aim to remove obfuscated files
|
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Add msr_text_compression
|
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"the `RemoteDatasetTest ` error in the CI is fixed on master so it's fine"
] | 1,607,245,571,000
| 1,607,511,225,000
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CONTRIBUTOR
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Add [MSR Abstractive Text Compression Dataset](https://msropendata.com/datasets/f8ce2ec9-7fbd-48f7-a8bb-2d2279373563)
|
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|
add taskmaster-1
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[] | 1,607,227,797,000
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MEMBER
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Adding Taskmaster-1 dataset
https://github.com/google-research-datasets/Taskmaster/tree/master/TM-1-2019
|
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| 1,192
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Add NewsPH_NLI dataset
|
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[] | 1,607,227,231,000
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CONTRIBUTOR
|
This PR adds the NewsPH-NLI Dataset, the first benchmark dataset for sentence entailment in the low-resource Filipino language. Constructed through exploting the structure of news articles. Contains 600,000 premise-hypothesis pairs, in 70-15-15 split for training, validation, and testing.
Link to the paper: https://arxiv.org/pdf/2010.11574.pdf
Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
|
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Added Translator Human Parity Data For a Chinese-English news transla…
|
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[
"Can you run `make style` to format the code and fix the CI please ?",
"> Can you run `make style` to format the code and fix the CI please ?\r\n\r\nI ran `make style` before this PR and just a few minutes ago. No changes to the code. Not sure why the CI is failing.",
"Also, I attempted to see if I can get the source Chinese sentences from `wmt17` dataset. But this call `data = load_dataset('wmt17', \"zh-en\")` failed with this error: `FileNotFoundError: Couldn't find file at https://storage.googleapis.com/tfdataset-data/downloadataset/uncorpus/UNv1.0.en-zh.tar.gz`. I think it should be possible and fairly straightforward to get the pairing source sentences from it. I just can not test it right now.",
"The `RemoteDatasetTest ` errors in the CI are fixed on master so it's fine",
"merging since the CI is fixed on master"
] | 1,607,225,653,000
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CONTRIBUTOR
|
…tion system from Open dataset list for Dataset sprint, Microsoft Datasets tab.
|
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|
Add Fake News Detection in Filipino dataset
|
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[
"Hi! I'm the author of this paper (surprised to see our datasets have been added already).\r\n\r\nThat paper link only leads to the conference index, here's a link to the actual paper: https://www.aclweb.org/anthology/2020.lrec-1.316/\r\n\r\nWould it be fine if I also edited your gsheet entry to reflect this change?",
"Hi Jan, please go ahead and update. I see you are also in the sprint slack channel. Let me know if what else needs updating. Thanks.\r\n"
] | 1,607,224,335,000
| 1,607,355,567,000
| 1,607,355,567,000
|
CONTRIBUTOR
|
This PR adds the Fake News Filipino Dataset, a low-resource fake news detection corpora in Filipino. Contains 3,206 expertly-labeled news samples, half of which are real and half of which are fake.
Link to the paper: http://www.lrec-conf.org/proceedings/lrec2020/index.html
Link to the dataset/repo: https://github.com/jcblaisecruz02/Tagalog-fake-news
|
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MDExOlB1bGxSZXF1ZXN0NTMzMTI4NjY1
| 1,189
|
Add Dengue dataset in Filipino
|
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[] | 1,607,223,047,000
| 1,607,355,538,000
| 1,607,355,538,000
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CONTRIBUTOR
|
This PR adds the Dengue Dataset, a benchmark dataset for low-resource multiclass classification, with 4,015 training, 500 testing, and 500 validation examples, each labeled as part of five classes. Each sample can be a part of multiple classes. Collected as tweets.
Link to the paper: https://ieeexplore.ieee.org/document/8459963
Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
|
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MDExOlB1bGxSZXF1ZXN0NTMzMTI2MTcw
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|
adding hind_encorp dataset
|
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[
"help needed in dummy data",
"extension of the file is .plaintext so dummy data generation is failing\r\n",
"you can add the `--match_text_file \"*.plaintext\"` flag when generating the dummy data\r\n\r\nalso it looks like the PR is empty, is this expected ?",
"yes it is expected because I made all my changes in PR #1186 then I again run code and open PR #1188 to see if this time test passes or not only so there is no code change from #1186 to #1188 \r\ni tried --match_text_file \"*.plaintext\" this time it is also not generating dummy data don't know why",
"well this PR includes no code change at all, can you make sure you added your changes in this one ?",
"feel free to ping me when you have added the files so I can take a look and help you with the dummy data",
"how to do that i dont know did i have to open new PR\r\n",
" actually all my changes are visible in #1186 but don't know how to show same changes here",
"these are a the which i did in #1186 and same in #1188 \r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\nthese same codes are in both #1186 and #1188 so because it is already present from PR #1186 because of that it is showing zeor code change in #1188 because it is already present from #1186 how i can show or highlight those changes\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n\r\n",
"well for me https://github.com/huggingface/datasets/pull/1188/files is blank",
"This PR tries to merge the master branch of you fork into this repo, however I can't find changes with your files inside your master branch.\r\n\r\nMaybe you can fork again the repo and try to create another PR ?",
"@lhoestq i opened a new pr #1438 but this time it fails many circl ci tests",
"Closing this one since a new PR was created"
] | 1,607,221,125,000
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CONTRIBUTOR
|
adding Hindi_Encorp05 dataset
|
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Added AQUA-RAT (Algebra Question Answering with Rationales) Dataset
|
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closed
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[
"merging since the CI is fixed on master"
] | 1,607,220,772,000
| 1,607,355,432,000
| 1,607,355,432,000
|
CONTRIBUTOR
|
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https://api.github.com/repos/huggingface/datasets/issues/1186
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https://github.com/huggingface/datasets/pull/1186
| 757,826,660
|
MDExOlB1bGxSZXF1ZXN0NTMzMTI1NjE4
| 1,186
|
all test passed
|
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closed
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False
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[
"looks like this PR includes changes to 5000 files\r\ncould you create a new branch and a new PR ?"
] | 1,607,220,752,000
| 1,607,353,615,000
| 1,607,353,615,000
|
CONTRIBUTOR
|
need help creating dummy data
|
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https://api.github.com/repos/huggingface/datasets/issues/1185
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| 757,825,413
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MDExOlB1bGxSZXF1ZXN0NTMzMTI0NzE1
| 1,185
|
Add Hate Speech Dataset in Filipino
|
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closed
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False
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|
[] | 1,607,220,116,000
| 1,607,355,333,000
| 1,607,355,333,000
|
CONTRIBUTOR
|
This PR adds the Hate Speech Dataset, a text classification dataset in Filipino, consisting 10k tweets (training set) that are labeled as hate speech or non-hate speech. Released with 4,232 validation and 4,232 testing samples. Collected during the 2016 Philippine Presidential Elections.
Link to the paper: https://pcj.csp.org.ph/index.php/pcj/issue/download/29/PCJ%20V14%20N1%20pp1-14%202019
Link to the dataset/repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
|
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| true
|
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