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1,312
Jigsaw toxicity pred
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2020-12-08T15:19:14Z
2020-12-11T12:11:32Z
2020-12-11T12:11:32Z
CONTRIBUTOR
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Requires manually downloading data from Kaggle.
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Add OPUS Bible Corpus (102 Languages)
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[ "@lhoestq done" ]
2020-12-08T14:57:08Z
2020-12-09T15:30:57Z
2020-12-09T15:30:56Z
CONTRIBUTOR
null
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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
null
null
null
null
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](ccoltekin@sfs.uni-tuebingen.de)
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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
CONTRIBUTOR
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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
CONTRIBUTOR
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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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1,307
adding capes
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closed
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2020-12-08T13:46:13Z
2020-12-09T15:40:09Z
2020-12-09T15:27:45Z
CONTRIBUTOR
null
null
null
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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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759,448,427
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1,306
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
CONTRIBUTOR
null
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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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1,305
[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
CONTRIBUTOR
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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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1,304
adding eitb_parcc
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2020-12-08T13:20:54Z
2020-12-09T18:02:54Z
2020-12-09T18:02:03Z
CONTRIBUTOR
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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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2020-12-08T13:20:21Z
2020-12-10T09:37:10Z
2020-12-10T09:37:10Z
CONTRIBUTOR
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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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2020-12-08T13:13:54Z
2020-12-10T09:35:26Z
2020-12-10T09:35:26Z
CONTRIBUTOR
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759,419,945
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1,301
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
null
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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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[ "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
null
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WIP As some tests did not clear! 👎🏼
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1,299
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
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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
CONTRIBUTOR
null
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OPUS Ted Talks 2013
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2020-12-08T12:25:39Z
2023-09-24T09:51:49Z
2020-12-08T12:35:50Z
CONTRIBUTOR
null
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1,296
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
null
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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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2020-12-08T11:40:06Z
2020-12-11T17:42:20Z
2020-12-11T17:42:20Z
CONTRIBUTOR
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759,365,246
MDExOlB1bGxSZXF1ZXN0NTM0MzgzMjg5
1,294
adding opus_euconst
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2020-12-08T11:24:16Z
2020-12-08T18:44:20Z
2020-12-08T18:41:23Z
CONTRIBUTOR
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Adding EUconst, a parallel corpus collected from the European Constitution. 21 languages, 210 bitexts
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2020-12-08T11:16:41Z
2020-12-08T11:34:47Z
2020-12-08T11:34:38Z
NONE
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arXiv dataset added
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2020-12-08T11:08:28Z
2020-12-08T14:02:13Z
2020-12-08T14:02:13Z
CONTRIBUTOR
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adding pubmed_qa dataset
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2020-12-08T11:05:44Z
2020-12-09T08:54:50Z
2020-12-09T08:54:50Z
CONTRIBUTOR
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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
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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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1,289
Jigsaw toxicity classification dataset added
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2020-12-08T10:38:51Z
2020-12-08T15:17:48Z
2020-12-08T15:17:48Z
CONTRIBUTOR
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The dataset requires manually downloading data from Kaggle.
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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
CONTRIBUTOR
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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 : ![image](https://user-images.githubusercontent.com/33657802/101469132-9ed12c80-3944-11eb-94ff-2d9c1d0ea080.png) ## 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
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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 git@github.com: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, eval_output_dir='outputs/finetune-adapter/test-n-1-lr-1e-02-e-20')\r\nSome weights of T5ForConditionalGeneration were not initialized from the model checkpoint at t5-small and are newly initialized: ['encoder.block.0.layer.0.adapter_controller.meta_up_sampler.weight_generator.0.weight', 'encoder.block.0.layer.0.adapter_controller.meta_up_sampler.weight_generator.0.bias', 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'decoder.block.4.layer.2.adapter_controller.meta_up_sampler.bias_generator.1.bias', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.weight', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.bias', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.weight', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.bias', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.weight', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.bias', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.weight', 'decoder.block.4.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.bias', 'decoder.block.4.layer.2.adapter_controller.post_layer_norm.weight', 'decoder.block.4.layer.2.adapter_controller.post_layer_norm.bias', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.weight_generator.0.weight', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.weight_generator.0.bias', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.weight_generator.1.weight', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.weight_generator.1.bias', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.bias_generator.0.weight', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.bias_generator.0.bias', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.bias_generator.1.weight', 'decoder.block.5.layer.0.adapter_controller.meta_up_sampler.bias_generator.1.bias', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.weight_generator.0.weight', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.weight_generator.0.bias', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.weight_generator.1.weight', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.weight_generator.1.bias', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.bias_generator.0.weight', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.bias_generator.0.bias', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.bias_generator.1.weight', 'decoder.block.5.layer.0.adapter_controller.meta_down_sampler.bias_generator.1.bias', 'decoder.block.5.layer.0.adapter_controller.post_layer_norm.weight', 'decoder.block.5.layer.0.adapter_controller.post_layer_norm.bias', '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
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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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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
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null
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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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759,269,920
MDExOlB1bGxSZXF1ZXN0NTM0MzAzNDk0
1,284
Update coqa dataset url
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2020-12-08T09:16:38Z
2020-12-08T18:19:09Z
2020-12-08T18:19:09Z
CONTRIBUTOR
null
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`datasets.stanford.edu` is invalid.
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759,251,457
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1,283
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
null
null
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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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759,208,335
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1,282
add thaiqa_squad
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2020-12-08T08:14:38Z
2020-12-08T18:36:18Z
2020-12-08T18:36:18Z
CONTRIBUTOR
null
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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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1,281
adding hybrid_qa
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2020-12-08T08:10:19Z
2020-12-08T18:09:28Z
2020-12-08T18:07:00Z
CONTRIBUTOR
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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
null
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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
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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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[ "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
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`craigslist_bargains` dataset from [here](https://worksheets.codalab.org/worksheets/0x453913e76b65495d8b9730d41c7e0a0c/)
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1,276
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
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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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[ "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
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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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1,274
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
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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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758,935,768
MDExOlB1bGxSZXF1ZXN0NTM0MDE4MjQ2
1,273
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
CONTRIBUTOR
null
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First PR (ever). Hopefully this movies dataset is useful to others!
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1,272
Psc
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2020-12-07T23:19:36Z
2020-12-07T23:48:05Z
2020-12-07T23:47:48Z
CONTRIBUTOR
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758,924,203
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SMS Spam Dataset
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2020-12-07T23:18:06Z
2020-12-08T17:42:19Z
2020-12-08T17:42:19Z
CONTRIBUTOR
null
null
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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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2020-12-07T23:03:48Z
2020-12-08T17:41:23Z
2020-12-08T17:41:23Z
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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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
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 ?" ]
2020-12-07T21:40:26Z
2020-12-09T13:45:05Z
2020-12-09T13:45:05Z
CONTRIBUTOR
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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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2020-12-07T17:31:16Z
2020-12-07T17:32:29Z
2020-12-07T17:32:29Z
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
CONTRIBUTOR
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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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Adding msr_genomics_kbcomp dataset
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2020-12-07T16:01:30Z
2020-12-08T18:08:55Z
2020-12-08T18:08:47Z
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Add Google Sentence Compression dataset
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2020-12-07T15:47:43Z
2020-12-08T17:01:59Z
2020-12-08T17:01:59Z
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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 ?" ]
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
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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
CONTRIBUTOR
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Add Swahili news classification dataset
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2020-12-07T14:15:13Z
2020-12-08T14:44:19Z
2020-12-08T14:44:19Z
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Add Swahili news classification dataset
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adding LiMiT dataset
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2020-12-07T14:00:41Z
2020-12-08T14:58:28Z
2020-12-08T14:42:51Z
CONTRIBUTOR
null
null
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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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2020-12-07T13:58:41Z
2020-12-08T17:17:54Z
2020-12-08T17:17:53Z
MEMBER
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null
null
null
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
null
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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
CONTRIBUTOR
null
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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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758,511,388
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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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null
null
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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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1,251
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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1,250
added Nergrit dataset
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2020-12-07T13:06:12Z
2020-12-08T14:33:29Z
2020-12-08T14:33:29Z
CONTRIBUTOR
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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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758,472,863
MDExOlB1bGxSZXF1ZXN0NTMzNjQwNjA1
1,249
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." ]
2020-12-07T12:39:09Z
2020-12-14T16:17:14Z
2020-12-14T16:17:14Z
CONTRIBUTOR
null
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### 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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758,454,438
MDExOlB1bGxSZXF1ZXN0NTMzNjI0ODY5
1,248
Update step-by-step guide about the dataset cards
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2020-12-07T12:12:12Z
2020-12-07T13:19:24Z
2020-12-07T13:19:23Z
MEMBER
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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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1,247
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" ]
2020-12-07T11:38:45Z
2020-12-08T14:11:50Z
2020-12-08T14:11:50Z
CONTRIBUTOR
null
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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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arXiv dataset added
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2020-12-07T11:20:23Z
2020-12-07T14:22:58Z
2020-12-07T14:22:58Z
CONTRIBUTOR
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[ "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." ]
2020-12-07T11:09:17Z
2023-09-24T09:40:49Z
2022-10-03T09:39:32Z
CONTRIBUTOR
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2020-12-07T10:32:54Z
2020-12-07T11:04:23Z
2020-12-07T11:04:23Z
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[ "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." ]
2020-12-07T10:26:05Z
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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!" ]
2020-12-07T10:15:49Z
2020-12-08T14:33:49Z
2020-12-08T14:33:48Z
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2020-12-07T10:03:34Z
2020-12-19T14:55:12Z
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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." ]
2020-12-07T09:57:15Z
2023-09-24T09:40:59Z
2022-10-03T09:39:43Z
CONTRIBUTOR
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add yelp_review_full dataset
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[ "Moved to https://github.com/huggingface/datasets/pull/1315" ]
2020-12-07T09:35:36Z
2020-12-08T15:43:24Z
2020-12-08T15:00:50Z
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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2020-12-07T09:11:52Z
2020-12-09T16:36:10Z
2020-12-09T16:02:45Z
CONTRIBUTOR
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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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2020-12-07T09:07:19Z
2020-12-08T13:38:52Z
2020-12-08T13:38:52Z
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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2020-12-07T07:53:57Z
2020-12-08T13:30:33Z
2020-12-08T13:30:33Z
CONTRIBUTOR
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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" ]
2020-12-07T07:12:42Z
2020-12-10T20:48:12Z
2020-12-10T20:48:01Z
CONTRIBUTOR
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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" ]
2020-12-07T07:05:14Z
2020-12-14T17:49:14Z
2020-12-14T17:49:14Z
CONTRIBUTOR
null
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Adverse Drug Reaction Data: ADE-Corpus-V2 dataset added configs for different tasks with given data
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MDExOlB1bGxSZXF1ZXN0NTMzMzk5NTY3
1,233
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." ]
2020-12-07T06:01:00Z
2020-12-20T13:34:09Z
2020-12-09T14:50:29Z
CONTRIBUTOR
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Add Facebook [Curiosity Dialogs](https://github.com/facebookresearch/curiosity) Dataset.
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758,180,669
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1,232
Add Grail QA dataset
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2020-12-07T05:46:45Z
2020-12-08T13:03:19Z
2020-12-08T13:03:19Z
CONTRIBUTOR
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For more information: https://dki-lab.github.io/GrailQA/
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1,231
Add Urdu Sentiment Corpus (USC)
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2020-12-07T03:25:20Z
2020-12-07T18:05:16Z
2020-12-07T16:43:23Z
CONTRIBUTOR
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@lhoestq opened a clean PR containing only relevant files. old PR #1140
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[ "merging since the CI is fixed on master" ]
2020-12-07T03:19:50Z
2020-12-07T18:04:55Z
2020-12-07T16:57:54Z
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 ✅ " ]
2020-12-07T02:23:29Z
2020-12-21T10:09:09Z
2020-12-21T10:09:09Z
CONTRIBUTOR
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MDExOlB1bGxSZXF1ZXN0NTMzMjg1ODI2
1,228
add opus_100 dataset
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[ "done." ]
2020-12-06T23:17:24Z
2020-12-09T14:54:00Z
2020-12-09T14:54:00Z
CONTRIBUTOR
null
null
null
null
This PR will add [opus100 dataset](http://opus.nlpl.eu/opus-100.php).
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MDExOlB1bGxSZXF1ZXN0NTMzMjg1ODIx
1,227
readme: remove link to Google's responsible AI practices
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2020-12-06T23:17:22Z
2020-12-07T08:35:19Z
2020-12-06T23:20:41Z
CONTRIBUTOR
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...maybe we'll find a company that reallly stands behind responsible AI practices ;)
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758,036,979
MDExOlB1bGxSZXF1ZXN0NTMzMjc2OTU3
1,226
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" ]
2020-12-06T22:16:15Z
2020-12-10T19:22:14Z
2020-12-10T19:22:14Z
CONTRIBUTOR
null
null
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Add menyo_20k_mt dataset
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758,035,501
MDExOlB1bGxSZXF1ZXN0NTMzMjc1ODcx
1,225
Add Winobias dataset
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[ "Will make another pull request with cleaner history" ]
2020-12-06T22:08:20Z
2020-12-07T06:45:59Z
2020-12-07T06:40:50Z
CONTRIBUTOR
null
null
null
null
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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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 !" ]
2020-12-06T21:06:53Z
2020-12-09T16:38:16Z
2020-12-09T14:37:17Z
CONTRIBUTOR
null
null
null
null
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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2020-12-06T21:02:54Z
2020-12-08T10:54:56Z
2020-12-08T10:54:56Z
CONTRIBUTOR
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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." ]
2020-12-06T20:46:53Z
2020-12-08T11:17:56Z
2020-12-08T11:17:55Z
CONTRIBUTOR
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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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2020-12-06T20:32:07Z
2020-12-09T16:34:18Z
2020-12-09T16:34:18Z
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" ]
2020-12-06T20:31:29Z
2020-12-08T15:21:09Z
2020-12-08T11:05:42Z
MEMBER
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758,013,368
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1,219
Add Korean NER dataset
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2020-12-06T20:19:06Z
2021-12-29T00:50:59Z
2020-12-08T10:25:33Z
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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758,009,113
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1,218
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" ]
2020-12-06T19:59:12Z
2020-12-15T15:27:30Z
2020-12-15T15:27:29Z
CONTRIBUTOR
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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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1,217
adding DataCommons fact checking
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2020-12-06T19:56:12Z
2020-12-16T16:22:48Z
2020-12-16T16:22:48Z
MEMBER
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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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758,005,982
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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" ]
2020-12-06T19:46:18Z
2020-12-08T07:52:11Z
2020-12-08T07:52:11Z
CONTRIBUTOR
null
null
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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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1,215
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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 " ]
2020-12-06T19:30:46Z
2020-12-16T16:18:25Z
2020-12-16T16:18:25Z
CONTRIBUTOR
null
null
null
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added files for irc disentanglement dataset was unable to test dummy data as a result of vpn/proxy issues
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adding medical-questions-pairs dataset
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2020-12-06T19:30:12Z
2020-12-09T14:42:53Z
2020-12-09T14:42:53Z
CONTRIBUTOR
null
null
null
null
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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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" ]
2020-12-06T17:56:03Z
2020-12-09T11:05:10Z
2020-12-09T11:00:29Z
CONTRIBUTOR
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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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1,212
Add Sanskrit Classic texts in datasets
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[ "merging since the CI is fixed on master" ]
2020-12-06T17:31:31Z
2020-12-07T19:04:08Z
2020-12-07T19:04:08Z
CONTRIBUTOR
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