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https://github.com/huggingface/datasets/pull/1383
| 1,383
|
added conv ai 2
|
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"@lhoestq Thank you for the suggestions. I added the changes to the branch and seems after rebasing it to master, all the commits previous commits got added. Should I create a new PR or should I keep this one only ? ",
"closing this one in favor of #1527 "
] | 2020-12-09T13:30:12Z
| 2020-12-13T18:54:42Z
| 2020-12-13T18:54:41Z
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Dataset : https://github.com/DeepPavlov/convai/tree/master/2018
|
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https://github.com/huggingface/datasets/pull/1382
| 1,382
|
adding UNPC
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"merging since the CI just had a connection error"
] | 2020-12-09T13:21:41Z
| 2020-12-09T17:53:06Z
| 2020-12-09T17:53:06Z
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Adding United Nations Parallel Corpus
http://opus.nlpl.eu/UNPC.php
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https://github.com/huggingface/datasets/pull/1381
| 1,381
|
Add twi text c3
|
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[
"looks like this PR includes changes about other datasets\r\n\r\nCan you only include the changes related to twi text c3 please ?",
"Hi @lhoestq , I have removed the unnecessary files. Can you please confirm?",
"You might need to either find a way to go back to the commit before it changes 389 files or create a new branch.",
"okay, I have created another branch, see the latest pull https://github.com/huggingface/datasets/pull/1518 @cstorm125 ",
"Hii please follow me",
"Closing this one in favor of #1518"
] | 2020-12-09T13:16:38Z
| 2020-12-13T18:39:27Z
| 2020-12-13T18:39:27Z
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Added Twi texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
|
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https://github.com/huggingface/datasets/pull/1380
| 1,380
|
Add Tatoeba Dataset
|
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[] | 2020-12-09T13:16:04Z
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https://github.com/huggingface/datasets/pull/1379
| 1,379
|
Add yoruba text c3
|
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[
"looks like this PR includes changes about other datasets\r\n",
"Thanks for the review. I'm a bit confused how to remove the files. Every time I add a new branch name using the following commands:\r\n\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit checkout -b a-descriptive-name-for-my-changes\r\n\r\nand push to the origin, this issue occurs",
"Can you try to create the branch from the master branch of your fork ?\r\n\r\nfirst update your master branch:\r\n```\r\ngit checkout master\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push\r\n```\r\n\r\nthen create a new one:\r\n```\r\ngit checkout -b my-new-branch\r\n```",
"I think you were still having the files because you were creating the new branch from a branch in which you've committed the files, instead of creating the new branch from the master branch",
"Got it, will correct that. Thanks",
"@lhoestq , I have removed the unnecessary files. Looks like I still have one error. How do I resolve this?",
"> @lhoestq , I have removed the unnecessary files. Looks like I still have one error. How do I resolve this?\r\n\r\nI think it's connection error on piqa dataset. Can you try triggering the test again? I usually resolve similar issues with:\r\n```\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push -u -f origin your_branch_name\r\n```",
"thank you @cstorm125 ",
"I have created another pull request for this https://github.com/huggingface/datasets/pull/1515 @cstorm125 @lhoestq ",
"Hii please follow me",
"merging since the CI is fixed on master",
"Great, thanks a lot"
] | 2020-12-09T13:16:03Z
| 2020-12-13T18:45:12Z
| 2020-12-13T18:37:33Z
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Added Yoruba texts for training embeddings and language models based on the paper https://www.aclweb.org/anthology/2020.lrec-1.335/
|
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https://github.com/huggingface/datasets/pull/1378
| 1,378
|
Add FACTCK.BR dataset
|
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[
"@lhoestq done!",
"merging since the CI is fixed on master"
] | 2020-12-09T13:06:22Z
| 2020-12-17T12:38:45Z
| 2020-12-15T15:34:11Z
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This PR adds [FACTCK.BR](https://github.com/jghm-f/FACTCK.BR) dataset from [FACTCK.BR: a new dataset to study fake news](https://dl.acm.org/doi/10.1145/3323503.3361698).
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https://github.com/huggingface/datasets/pull/1377
| 1,377
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adding marathi-wiki dataset
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"Can you make it a draft PR until you've added the dataset please ? @ekdnam ",
"Done",
"Thanks for your contribution, @ekdnam. 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."
] | 2020-12-09T13:01:20Z
| 2022-10-03T09:39:09Z
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Adding marathi-wiki-articles dataset.
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https://github.com/huggingface/datasets/pull/1376
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Add SETimes Dataset
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https://github.com/huggingface/datasets/pull/1375
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Add OPUS EMEA Dataset
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| 1,374
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Add OPUS Tilde Model Dataset
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https://github.com/huggingface/datasets/pull/1373
| 1,373
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Add OPUS ECB Dataset
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https://github.com/huggingface/datasets/pull/1372
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Add OPUS Books Dataset
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[
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| 2020-12-14T09:56:28Z
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https://github.com/huggingface/datasets/pull/1371
| 1,371
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Adding Scielo
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| 2020-12-09T17:53:37Z
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Adding Scielo: Parallel corpus of full-text articles in Portuguese, English and Spanish from SciELO
https://sites.google.com/view/felipe-soares/datasets#h.p_92uSCyAjWSRB
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https://github.com/huggingface/datasets/pull/1370
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Add OPUS PHP Dataset
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https://github.com/huggingface/datasets/pull/1369
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Use passed --cache_dir for modules cache
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[
"I have a question: why not using a tmp dir instead, like the DummyDataGeneratorDownloadManager does?",
"Hi @lhoestq, I am trying to understand better the logic...\r\n\r\nWhy do we have a `dynamic_module_path` besides the modules cache path?\r\n```python\r\nDYNAMIC_MODULES_PATH = os.path.join(HF_MODULES_CACHE, \"datasets_modules\")\r\n```\r\nMoreover, 2 subdirectories (for datasets and for metrics) were created inside it:\r\n```python\r\nDATASETS_PATH = os.path.join(DYNAMIC_MODULES_PATH, \"datasets\")\r\nMETRICS_PATH = os.path.join(DYNAMIC_MODULES_PATH, \"metrics\")\r\n```",
"Hi :) \r\nThe modules cache path is the path added to `sys.path`.\r\nTherefore inside we need to have a folder that is going to be a package: `datasets_modules`.\r\nThis package will contain dynamic modules, i.e. datasets and metrics modules added on-the-fly.\r\nThen we have two sub-modules `datasets_modules.datasets` and `datasets_modules.metrics`.\r\n\r\nMaybe we can make things more explicit in the code with some comments explaining the structure, and maybe better variable naming as well..\r\n\r\nAlso I wanted to say that I started to work on offline loading of modules in #1726 and actually it lead to do similar changes to what you did to control the path where modules are stored.",
"Hi @lhoestq, I see...\r\n\r\nIndeed I was also creating a draft for test_load, to clarify the expected behavior... ;)\r\n\r\nSo, for the command line:\r\n```sh\r\npython datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>\r\n```\r\nthe `cache_dir` argument refers to dataset cache dir. We do not have control over the modules cache dir, but we would like to have. And if I understand well, you suggest adding another argument `dynamic_module_path`. Am I right?",
"> So, for the command line:\r\n> \r\n> ```shell\r\n> python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>\r\n> ```\r\n> \r\n> the `cache_dir` argument refers to dataset cache dir. We do not have control over the modules cache dir, but we would like to have. And if I understand well, you suggest adding another argument `dynamic_module_path`. Am I right?\r\n\r\nYes the cache_dir is used to download files and also so save the dataset arrow files.\r\nThis is indeed different from the path for dynamic modules.\r\n\r\nI suggested to have `dynamic_module_path` as a parameter but actually this is the parent directory `hf_modules_cache` that we would need (it's the one that is passed to `init_dynamic_modules ` that we need to add to `sys.path`).\r\n\r\nCurrently it's already possible to override it using the env variable `HF_MODULES_CACHE` but we can imagine having it as a parameter as well.\r\n\r\nThis way the user controls both the `cache_dir` and the `hf_modules_cache` which are the two places used by the library to read/write stuff.\r\n\r\n",
"I think #1726 is going to be merged pretty soon. Maybe can work on this as soon as it's merged to avoid doing the same things twice and to avoid conflicts ?",
"I agree. Indeed I took some of your code in one of my last commit, to try to implement the logic you described."
] | 2020-12-09T10:59:59Z
| 2022-07-06T15:19:47Z
| null |
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When passed `--cache_dir` arg:
```shell
python datasets-cli test datasets/<my-dataset-folder> --save_infos --all_configs --cache_dir <my-cache-dir>
```
it is not used for caching the modules, which are cached in the default location at `.cache/huggingface/modules`.
With this fix, the modules will be cached at `<my-cache-dir>/modules`.
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| 1,368
|
Re-adding narrativeqa dataset
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"@lhoestq I think I've fixed the dummy data - it finally passes! I'll add the model card now.",
"@lhoestq - pretty happy with it now",
"> Awesome thank you !\r\n> \r\n> Could you try to reduce the size of the dummy_data.zip file before we merge ? (it's 300KB right now)\r\n> \r\n> To do so feel free to take a look inside it and remove all the unnecessary files and chunks of text, to only keep a few examples. The idea is to have a zip file that is only a few KB\r\n\r\nAh, it only contains 1 example for each split. I think the problem is that I include an entire story (like in the full dataset). We can probably get away with a summarised version.",
"> Nice thank you, can you make it even lighter if possible ? Something round 10KB would be awesone\r\n> We try to keep the repo light so that it doesn't take ages to clone. So we have to make sure the dummy data are as small as possible for every single dataset.\r\n\r\nHave trimmed a little more out of each example now."
] | 2020-12-09T10:53:09Z
| 2020-12-11T13:30:59Z
| 2020-12-11T13:30:59Z
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An update of #309.
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https://github.com/huggingface/datasets/pull/1367
| 1,367
|
adding covid-tweets-japanese
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[
"I think it's because the file you download uncompresses into a file and not a folder so `--autogenerate` couldn't create dummy data for you. See in your dummy_data.zip if there is a file there. If not, manually create your dummy data and compress them to dummy_data.zip.",
"@cstorm125 Thank you for the comment! \r\nAs you point out, it seems my code has something wrong about downloading and uncompressing the file.\r\nHowever, my manually created dummy data seems to contain a file of the required format.\r\n\r\nOn Colaboratory,\r\n`!unzip /content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data.zip`\r\nreturns:\r\n\r\n```\r\nArchive: /content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data.zip\r\n creating: content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data/\r\n extracting: content/datasets/datasets/covid_tweets_japanese/dummy/1.1.0/dummy_data/data.csv.bz2 \r\n```\r\n\r\nThe original data is `data.csv.bz2`, and I had a very hard time dealing with uncompressing bzip2.\r\nI think I could handle it, but there may be problems remain."
] | 2020-12-09T10:34:01Z
| 2020-12-09T17:25:14Z
| 2020-12-09T17:25:14Z
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Adding COVID-19 Japanese Tweets Dataset as part of the sprint.
Testing with dummy data is not working (the file is said to not exist). Sorry for the incomplete PR.
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Adding Hope EDI dataset
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[
"@lhoestq Have addressed your comments. Please review. Thanks."
] | 2020-12-09T10:30:23Z
| 2020-12-14T14:27:57Z
| 2020-12-14T14:27:57Z
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https://github.com/huggingface/datasets/pull/1365
| 1,365
|
Add Mkqa dataset
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[
"the `RemoteDatasetTest ` error pf the CI is fixed on master so it's fine",
"merging since the CI is fixed on master"
] | 2020-12-09T10:06:33Z
| 2020-12-10T15:37:56Z
| 2020-12-10T15:37:56Z
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# MKQA: Multilingual Knowledge Questions & Answers Dataset
Adding the [MKQA](https://github.com/apple/ml-mkqa) dataset as part of the sprint π
There is no official data splits so I added just a `train` split.
differently from the original:
- answer:type field is a ClassLabel (I thought it might be possible to train on this as a label for categorizing questions)
- answer:entity field has a default value of empty string '' (since this key is not available for all in original)
- answer:alias has default value of []
- [x] All tests passed
- [x] Added dummy data
- [x] Added data card (as much as I could)
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https://github.com/huggingface/datasets/pull/1364
| 1,364
|
Narrative QA (Manual Download Stories) Dataset
|
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[
"Hi ! Maybe we can rename it `narrativeqa_manual` to make it explicit that this one requires manual download contrary to `narrativeqa` ?\r\nIt's important to have this one as well, in case the `narrativeqa` one suffers from download issues (checksums or dead links for example).\r\n\r\nYou can also copy the dataset card from `narrativeqa` and add the dummy data as well",
"Thanks @lhoestq will do all this and submit a request in the coming days. π ",
"Closing this as another pull request is already done. "
] | 2020-12-09T09:33:59Z
| 2021-01-25T15:31:51Z
| 2021-01-25T15:31:31Z
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Narrative QA with manual download for stories.
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https://github.com/huggingface/datasets/pull/1363
| 1,363
|
Adding OPUS MultiUN
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| 2020-12-09T17:54:20Z
| 2020-12-09T17:54:20Z
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|
Adding UnMulti
http://www.euromatrixplus.net/multi-un/
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https://github.com/huggingface/datasets/pull/1362
| 1,362
|
adding opus_infopankki
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[
"Thanks Quentin !"
] | 2020-12-09T08:57:10Z
| 2020-12-09T18:16:20Z
| 2020-12-09T18:13:48Z
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Adding opus_infopankki
http://opus.nlpl.eu/infopankki-v1.php
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https://github.com/huggingface/datasets/pull/1361
| 1,361
|
adding bprec
|
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[
"@lhoestq I think this is ready for review, I assume the errors (connection) are unrelated to the PR :) ",
"merging since the CI is fixed on master"
] | 2020-12-09T08:02:45Z
| 2020-12-16T17:04:44Z
| 2020-12-16T17:04:44Z
|
CONTRIBUTOR
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|
Brand-Product Relation Extraction Corpora in Polish
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https://github.com/huggingface/datasets/pull/1360
| 1,360
|
add wisesight1000
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[] | 2020-12-09T07:41:30Z
| 2020-12-10T14:28:41Z
| 2020-12-10T14:28:41Z
|
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`wisesight1000` contains Thai social media texts randomly drawn from the full `wisesight-sentiment`, tokenized by human annotators. Out of the labels `neg` (negative), `neu` (neutral), `pos` (positive), `q` (question), 250 samples each. Some texts are removed because they look like spam.Because these samples are representative of real world content, we believe having these annotaed samples will allow the community to robustly evaluate tokenization algorithms.
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https://github.com/huggingface/datasets/pull/1359
| 1,359
|
Add JNLPBA
|
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[] | 2020-12-09T06:48:51Z
| 2020-12-10T14:24:36Z
| 2020-12-10T14:24:36Z
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https://github.com/huggingface/datasets/pull/1358
| 1,358
|
Add spider dataset
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| 2020-12-10T15:12:31Z
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This PR adds the Spider dataset, a large-scale complex and cross-domain semantic parsing and text-to-SQL dataset annotated by 11 Yale students. The goal of the Spider challenge is to develop natural language interfaces to cross-domain databases.
Dataset website: https://yale-lily.github.io/spider
Paper link: https://www.aclweb.org/anthology/D18-1425/
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https://github.com/huggingface/datasets/pull/1357
| 1,357
|
Youtube caption corrections
|
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[
"Sorry about forgetting flake8.\r\nRather than use up the circleci resources on a new push with only formatting changes, I will wait to push until the results from all tests finish and/or any feedback comes in... probably tomorrow for me.",
"\r\nSo... my normal work is with mercurial and seem to have clearly forked this up using git... :(\r\n\r\nWhat I did is after calling:\r\n```\r\ngit fetch upstream\r\ngit rebase upstream/master\r\n```\r\n\r\nI then I attempt to pull in my most recent changes UI commit changes based on @lhoestq's feedback with:\r\n```\r\ngit pull\r\n``` \r\n... which I now suspect undid the above fetch and rebase. Will look into fixing later today when I have more time. Sorry!\r\n",
"My dummy data seems quite large as a single row is composed of tokens/labels for an entire youtube video, with at least one row required for each file, which in this case 1 file per 13 youtube channels.\r\n\r\nTo make it smaller I passed `--n_lines 1` to reduce about 5x.\r\n\r\nI then manually reduced size of the particularly long youtube lectures to get the size to about 30KB. However, after recompressing into a zip, and running dummy data test I got the following error:\r\n`FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_youtube_caption_corrections - OSError: Cannot find data file. `, despite file being there, which I haven't had a chance yet to debug.",
"I wrote a small script to generate a smaller json file for the dummy_data, with the hope that I could resolve the pytest error noted above (in case related to a manual typo I could have introduce), however the test contains to fail locally... here's to hoping it can pass on remote!",
"Sorry for delayed comments here. Last commit made two changes:\r\n- Increased the valency of the labels from just True/False to more categories to describe the various types of diffs encountered. This required some rewrite of the README\r\n- Reduced the number of remote files to be downloaded from 13 to 4, by combining all 13 of the channel-specific files together, and the splitting them up in a way to meet Github file size requirements. This also reduces size of the dummy-data.",
"@lhoestq, thank you for the great feedback, especially given how busy you guys are now! \r\n\r\nI checked out GitHub release tags and looks cool. I have added the version tag to the url, instead of the commit sha as originally suggested, with the hope that it serves the same purpose of pinning the content to this url. Please let me know if I have misunderstood.\r\n\r\nIn regard to dynamically changing the number of files downloaded by first downloading a JSON listing the files, I love that idea. But I am a little confused, as I was thinking that any changes to the dataset itself would require a new PR with an updated `dataset_infos.json`, e.g. `num_examples` would increase. \r\n\r\nIf the purpose of this is not to permit dynamic (without a PR needed) growth of the number of files, but instead to provide stability to the consumers of the dataset, maybe I continued use the release tags, maintaining access to old releases could serve this purpose? I am still learning about these release tags... ",
"For dynamic datasets, i.e. datasets that evolve over time, we support custom configurations: they are configurations that are not part of the BUILDER_CONFIGS or in the dataset_infos.json\r\n\r\nFor example for wikipedia, you can use the latest wiki dump by specifying `date=` inside `load_dataset()`. A configuration is created on the fly for this date and is used to build the dataset using the latest data.\r\n\r\nTherefore we don't need to have PRs to update the script for each wikipedia release.\r\n\r\nOne downside though is that we don't have metadata in advance such as the size of the dataset.\r\n\r\nI think this could be a nice addition for the youtube caption dataset in the future to be have a system of releases and be able to load the version we want easily. What do you think ?",
"\r\n\r\n\r\n\r\n> For dynamic datasets, i.e. datasets that evolve over time, we support custom configurations: they are configurations that are not part of the BUILDER_CONFIGS or in the dataset_infos.json\r\n> \r\n \r\n> I think this could be a nice addition for the youtube caption dataset in the future to be have a system of releases and be able to load the version we want easily. What do you think ?\r\n\r\nThank you for the suggestion! This sounds great! I will take a look at the some datasets that do this, and would love to give it a try in the future, if I continue to grow the captions dataset in a meaningful way. \r\n\r\nAppreciate all the help on this. It has been a really great experience for me. :)",
"Excited to merge! And sorry to be such a github n00b, but from what I've quickly read, I don't 'Close pull request', but rather the next steps are action taken on your end... Please let me know if there is some action to be taken at my end first. :/",
"Alright merging this one then :) "
] | 2020-12-09T05:52:34Z
| 2020-12-15T18:12:56Z
| 2020-12-15T18:12:56Z
|
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This PR adds a new dataset of YouTube captions, error and corrections. This dataset was created in just the last week, as inspired by this sprint!
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https://github.com/huggingface/datasets/pull/1356
| 1,356
|
Add StackOverflow StackSample dataset
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[
"@lhoestq Thanks for the review and suggestions! I've added your comments and pushed the changes. I'm having issues with the dummy data still. When I run the dummy data test\r\n\r\n```bash\r\nRUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_so_stacksample\r\n```\r\nI get this error: \r\n\r\n```\r\n___________________________________________ LocalDatasetTest.test_load_dataset_all_configs_so_stacksample ____________________________________________\r\n\r\nself = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_so_stacksample>, dataset_name = 'so_stacksample'\r\n\r\n @slow\r\n def test_load_dataset_all_configs(self, dataset_name):\r\n configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)\r\n> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)\r\n\r\ntests/test_dataset_common.py:237: \r\n_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ \r\ntests/test_dataset_common.py:198: in check_load_dataset\r\n self.parent.assertTrue(len(dataset[split]) > 0)\r\nE AssertionError: False is not true\r\n\r\nFAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_so_stacksample - AssertionError: False is not true\r\n```\r\n\r\nI tried formatting the data similar to other datasets, but I think I don't have my csv's in the zip folder with the proper name. I also ran the command that's supposed to outline the exact steps I need to perform to get them into the correct format, but I followed them and they don't seem to be working still :/. Any help would be greatly appreciated!\r\n",
"Ok I found the issue with the dummy data.\r\nIt's currently failing because it's not generating a single example using the dummy csv file.\r\nThat's because there's only only line in the dummy csv file, and this line is skipped using the `next()` call used to ignore the headers of the csv.\r\n\r\nTo fix the dummy data you must add headers to the dummy csv files.",
"Also can you make sure that all the original CSV files have headers ? i.e. check that their first line is just the column names",
"> Ok I found the issue with the dummy data.\r\n> It's currently failing because it's not generating a single example using the dummy csv file.\r\n> That's because there's only only line in the dummy csv file, and this line is skipped using the `next()` call used to ignore the headers of the csv.\r\n> \r\n> To fix the dummy data you must add headers to the dummy csv files.\r\n\r\nOh man, I bamboozled myself! Thank you @lhoestq for catching that! I've updated the dummy csv's to include headers and also confirmed that they all have headers, so I am not throwing away any information with that `next()` call. When I run the test locally for the dummy data it passes, so hopefully it is good to go :D",
"merging since the Ci is fixed on master"
] | 2020-12-09T04:59:51Z
| 2020-12-21T14:48:21Z
| 2020-12-21T14:48:21Z
|
NONE
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This PR adds the StackOverflow StackSample dataset from Kaggle: https://www.kaggle.com/stackoverflow/stacksample
Ran through all of the steps. However, since my dataset requires manually downloading the data, I was unable to run the pytest on the real dataset (the dummy data pytest passed).
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https://github.com/huggingface/datasets/pull/1355
| 1,355
|
Addition of py_ast dataset
|
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[] | 2020-12-09T04:59:17Z
| 2020-12-09T16:19:49Z
| 2020-12-09T16:19:48Z
|
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|
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@lhoestq as discussed in PR #1195
|
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| null | null | null | true
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https://github.com/huggingface/datasets/pull/1354
| 1,354
|
Add TweetQA dataset
|
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[] | 2020-12-09T04:44:01Z
| 2020-12-10T15:10:30Z
| 2020-12-10T15:10:30Z
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|
This PR adds the TweetQA dataset, the first dataset for QA on social media data by leveraging news media and crowdsourcing.
Paper: https://arxiv.org/abs/1907.06292
Repository: https://tweetqa.github.io/
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/pull/1353
| 1,353
|
New instruction for how to generate dataset_infos.json
|
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closed
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[] | 2020-12-09T04:24:40Z
| 2020-12-10T13:45:15Z
| 2020-12-10T13:45:15Z
|
NONE
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|
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|
Add additional instructions for how to generate dataset_infos.json for manual download datasets. Information courtesy of `Taimur Ibrahim` from the slack channel
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/pull/1352
| 1,352
|
change url for prachathai67k to internet archive
|
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|
[] |
closed
| false
|
[] | 2020-12-09T04:20:37Z
| 2020-12-10T13:42:17Z
| 2020-12-10T13:42:17Z
|
CONTRIBUTOR
| false
|
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|
`prachathai67k` is currently downloaded from git-lfs of PyThaiNLP github. Since the size is quite large (~250MB), I moved the URL to archive.org in order to prevent rate limit issues.
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/pull/1351
| 1,351
|
added craigslist_bargians
|
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|
[] |
closed
| false
|
[] | 2020-12-09T01:02:31Z
| 2020-12-10T14:14:34Z
| 2020-12-10T14:14:34Z
|
CONTRIBUTOR
| false
|
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|
`craigslist_bargains` data set from [here](https://worksheets.codalab.org/worksheets/0x453913e76b65495d8b9730d41c7e0a0c/)
(Cleaned up version of #1278)
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/pull/1350
| 1,350
|
add LeNER-Br dataset
|
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closed
| false
|
[
"I don't know what happened, my first commit passed on all checks, but after just a README.md update one of the scripts failed, is it normal? π ",
"Looks like a flaky connection error, I've launched a re-run, it should be fine :)",
"The RemoteDatasetTest error in the CI is just a connection error, we can ignore it",
"merging since the CI is fixed on master"
] | 2020-12-09T00:06:38Z
| 2020-12-10T14:11:33Z
| 2020-12-10T14:11:33Z
|
CONTRIBUTOR
| false
|
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|
Adding the LeNER-Br dataset, a Portuguese language dataset for named entity recognition
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/pull/1349
| 1,349
|
initial commit for MultiReQA
|
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"looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n\r\nCan you create another branch and another PR please ?",
"> looks like this dataset includes changes about many other files than the ones for multi_re_qa\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\nSure I will do that. Thank you."
] | 2020-12-08T23:44:34Z
| 2020-12-09T16:46:37Z
| 2020-12-09T16:46:37Z
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Added MultiReQA, which is a dataset containing the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA.
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https://github.com/huggingface/datasets/pull/1348
| 1,348
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add Yoruba NER dataset
|
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[
"Thank you. Okay, other pull requests only have one dataset",
"The `RemoteDatasetTest` error in the CI is just a connection error, we can ignore it",
"merging since the CI is fixed on master",
"Thank you very much"
] | 2020-12-08T23:42:35Z
| 2020-12-10T14:30:25Z
| 2020-12-10T14:09:43Z
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Added Yoruba GV dataset based on this paper
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https://github.com/huggingface/datasets/pull/1346
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Add MultiBooked dataset
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[
"There' still an issue with the dummy data, let me take a look"
] | 2020-12-08T22:49:36Z
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| 2020-12-15T17:02:09Z
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Add dataset.
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https://github.com/huggingface/datasets/pull/1345
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First commit of NarrativeQA Dataset
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[] | 2020-12-08T22:31:59Z
| 2021-01-25T15:31:52Z
| 2020-12-09T09:29:52Z
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Added NarrativeQA dataset and included a manual downloading option to download scripts from the original scripts provided by the authors.
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https://github.com/huggingface/datasets/pull/1344
| 1,344
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Add hausa ner corpus
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[] | 2020-12-08T22:25:04Z
| 2020-12-08T23:11:55Z
| 2020-12-08T23:11:55Z
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Added Hausa VOA NER data
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https://github.com/huggingface/datasets/pull/1343
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Add LiveQA
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[] | 2020-12-08T21:52:36Z
| 2020-12-14T09:40:28Z
| 2020-12-14T09:40:28Z
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This PR adds LiveQA, the Chinese real-time/timeline-based QA task by [Liu et al., 2020](https://arxiv.org/pdf/2010.00526.pdf).
|
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https://github.com/huggingface/datasets/pull/1342
| 1,342
|
[yaml] Fix metadata according to pre-specified scheme
|
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[] | 2020-12-08T21:26:34Z
| 2020-12-09T15:37:27Z
| 2020-12-09T15:37:26Z
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@lhoestq @yjernite
|
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https://github.com/huggingface/datasets/pull/1341
| 1,341
|
added references to only data card creator to all guides
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[] | 2020-12-08T21:11:11Z
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We can now use the wonderful online form for dataset cards created by @evrardts
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https://github.com/huggingface/datasets/pull/1340
| 1,340
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:fist: Β‘Viva la Independencia!
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[
"I've added the changes / fixes - ready for a second pass :)"
] | 2020-12-08T20:43:43Z
| 2020-12-14T10:36:01Z
| 2020-12-14T10:36:01Z
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Adds the Catalonia Independence Corpus for stance-detection of Tweets.
Ready for review!
|
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https://github.com/huggingface/datasets/pull/1339
| 1,339
|
hate_speech_18 initial commit
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[
"> Nice thanks !\r\n> \r\n> Can you rename the dataset folder and the dataset script name `hate_speech18` instead of `hate_speech_18` to follow the snake case convention we're using ?\r\n> \r\n> Also it looks like the dummy_data.zip file is quite big (almost 4MB).\r\n> Can you try to reduce its size ?\r\n> \r\n> To do so feel free to take a look inside it and remove all the unnecessary files or chunks of texts. The idea is to only keep a few examples\r\n\r\nDone, thanks! ",
"Re-opened in https://github.com/huggingface/datasets/pull/1486"
] | 2020-12-08T20:10:08Z
| 2020-12-12T16:17:32Z
| 2020-12-12T16:17:32Z
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https://github.com/huggingface/datasets/pull/1338
| 1,338
|
Add GigaFren Dataset
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[
"@lhoestq fixed"
] | 2020-12-08T19:42:04Z
| 2020-12-14T10:03:47Z
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https://github.com/huggingface/datasets/pull/1336
| 1,336
|
Add dataset Yoruba BBC Topic Classification
|
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[] | 2020-12-08T19:12:18Z
| 2020-12-10T11:27:41Z
| 2020-12-10T11:27:41Z
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Added new dataset Yoruba BBC Topic Classification
Contains loading script as well as dataset card including YAML tags.
|
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https://github.com/huggingface/datasets/pull/1335
| 1,335
|
Added Bianet dataset
|
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[
"merging since the Ci is fixed on master"
] | 2020-12-08T19:10:32Z
| 2020-12-14T10:00:56Z
| 2020-12-14T10:00:56Z
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Hi :hugs:, This is a PR for [Bianet: A parallel news corpus in Turkish, Kurdish and English; Source](http://opus.nlpl.eu/Bianet.php) dataset
|
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https://github.com/huggingface/datasets/pull/1334
| 1,334
|
Add QED Amara Dataset
|
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https://github.com/huggingface/datasets/pull/1333
| 1,333
|
Add Tanzil Dataset
|
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[] | 2020-12-08T18:45:15Z
| 2020-12-10T11:17:56Z
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https://github.com/huggingface/datasets/pull/1332
| 1,332
|
Add Open Subtitles Dataset
|
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[] | 2020-12-08T18:31:45Z
| 2020-12-10T11:17:38Z
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https://github.com/huggingface/datasets/pull/1331
| 1,331
|
First version of the new dataset hausa_voa_topics
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| 2020-12-10T11:09:53Z
| 2020-12-10T11:09:53Z
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Contains loading script as well as dataset card including YAML tags.
|
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https://github.com/huggingface/datasets/pull/1330
| 1,330
|
added un_ga dataset
|
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[
"Looks like this PR includes changes about many other files than the ones for un_ga\r\n\r\nCan you create another branch an another PR please ?",
"@lhoestq, Thank you for suggestions. I have made the changes and raised the new PR https://github.com/huggingface/datasets/pull/1569. "
] | 2020-12-08T17:58:38Z
| 2020-12-14T17:52:34Z
| 2020-12-14T17:52:34Z
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|
Hi :hugs:, This is a PR for [United nations general assembly resolutions: A six-language parallel corpus](http://opus.nlpl.eu/UN.php) dataset
|
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https://github.com/huggingface/datasets/pull/1329
| 1,329
|
Add yoruba ner corpus
|
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[] | 2020-12-08T17:54:00Z
| 2020-12-08T23:11:12Z
| 2020-12-08T23:11:12Z
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https://github.com/huggingface/datasets/pull/1328
| 1,328
|
Added the NewsPH Raw dataset and corresponding dataset card
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[] | 2020-12-08T17:25:45Z
| 2020-12-10T11:04:34Z
| 2020-12-10T11:04:34Z
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This PR adds the original NewsPH dataset which is used to autogenerate the NewsPH-NLI dataset. Reopened a new PR as the previous one had problems.
Paper: https://arxiv.org/abs/2010.11574
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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https://github.com/huggingface/datasets/pull/1327
| 1,327
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Add msr_genomics_kbcomp dataset
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TEP: Tehran English-Persian parallel corpus
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[] | 2020-12-08T16:56:53Z
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TEP: Tehran English-Persian parallel corpus
more info : http://opus.nlpl.eu/TEP.php
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https://github.com/huggingface/datasets/pull/1325
| 1,325
|
Add humicroedit dataset
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[
"Updated the commit with the generated yaml tags",
"merging since the CI is fixed on master"
] | 2020-12-08T16:35:46Z
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Pull request for adding humicroedit dataset
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https://github.com/huggingface/datasets/issues/1324
| 1,324
|
β Sharing ElasticSearch indexed dataset
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"default": false,
"description": "Requesting to add a new dataset",
"id": 2067376369,
"name": "dataset request",
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[
"Hello @pietrolesci , I am not sure to understand what you are trying to do here.\r\n\r\nIf you're looking for ways to save a dataset on disk, you can you the `save_to_disk` method:\r\n```python\r\n>>> import datasets\r\n>>> loaded_dataset = datasets.load(\"dataset_name\")\r\n>>> loaded_dataset.save_to_disk(\"/path/on/your/disk\")\r\n```\r\n\r\nThe saved dataset can later be retrieved using:\r\n```python\r\n>>> loaded_dataset = datasets.Dataset.load_from_disk(\"/path/on/your/disk\")\r\n```\r\n\r\nAlso, I'd recommend posting your question directly in the issue section of the [elasticsearch repo](https://github.com/elastic/elasticsearch)",
"Hi @SBrandeis,\n\nThanks a lot for picking up my request. \n\nMaybe I can clarify my use-case with a bit of context. Say I have the IMDb dataset. I create an ES index on it. Now I can save and reload the dataset from disk normally. Once I reload the dataset, it is easy to retrieve the ES index on my machine. I was wondering: is there a way I can share the (now) indexed version of the IMDb dataset with my colleagues without requiring them to re-index it?\n\nThanks a lot in advance for your consideration.\n\nBest,\n\nPietro",
"Thanks for the clarification.\r\n\r\nI am not familiar with ElasticSearch, but if I understand well you're trying to migrate your data along with the ES index.\r\nMy advice would be to check out ES documentation, for instance, this might help you: https://www.elastic.co/guide/en/cloud/current/ec-migrate-data.html\r\n\r\nLet me know if it helps"
] | 2020-12-08T16:25:58Z
| 2020-12-22T07:50:56Z
| null |
NONE
| null | null |
Hi there,
First of all, thank you very much for this amazing library. Datasets have become my preferred data structure for basically everything I am currently doing.
**Question:** I'm working with a dataset and I have an elasticsearch container running at localhost:9200. I added an elasticsearch index and I was wondering
- how can I know where it has been saved?
- how can I share the indexed dataset with others?
I tried to dig into the docs, but could not find anything about that.
Thank you very much for your help.
Best,
Pietro
Edit: apologies for the wrong label
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https://github.com/huggingface/datasets/pull/1323
| 1,323
|
Add CC-News dataset of English language articles
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[
"@vblagoje nice work, please add the README.md file and it would be ready",
"@lhoestq @tanmoyio @yjernite please have a look at the dataset card. Don't forget that the dataset is still hosted on my private gs bucket and should eventually be moved to the HF bucket",
"I will move the files soon and ping you when it's done and with the new URLs :) ",
"Hi !\r\n\r\nI just moved the file to a HF bucket. It's available at https://storage.googleapis.com/huggingface-nlp/datasets/cc_news/cc_news.tar.gz\r\n\r\nSorry for the delay ^^'",
"@lhoestq no worries, updated PR with the new URL and rebased to master\r\n"
] | 2020-12-08T16:18:15Z
| 2021-02-01T16:55:49Z
| 2021-02-01T16:55:49Z
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Adds [CC-News](https://commoncrawl.org/2016/10/news-dataset-available/) dataset. It contains 708241 English language news articles. Although each article has a language field these tags are not reliable. I've used Spacy language detection [pipeline](https://spacy.io/universe/project/spacy-langdetect) to confirm that the article language is indeed English.
The prepared dataset is temporarily hosted on my private Google Storage [bucket](https://storage.googleapis.com/hf_datasets/cc_news.tar.gz). We can move it to HF storage and update this PR before merging.
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https://github.com/huggingface/datasets/pull/1322
| 1,322
|
add indonlu benchmark datasets
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| 2020-12-13T01:54:28Z
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The IndoNLU benchmark is a collection of resources for training, evaluating, and analyzing natural language understanding systems for the Indonesian language. There are 12 datasets in IndoNLU.
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https://github.com/huggingface/datasets/pull/1321
| 1,321
|
added dutch_social
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[
"@lhoestq \r\nUpdated the `dummy_data.zip `(<10kb)I had to reduce it to just a few samples. \r\nTrain-Test-Dev (20-5-5 samples) \r\n\r\nBut the push also added changes from other PRs (probably because of a rebase!) So the files changed tab shows 466 files were changed! \r\n",
"Thanks ! The dummy data are all good now :) \r\n\r\nLooks like this PR includes changes to many other files than the ones for dutch_social now.\r\n\r\nCan you create another branch and another PR please ?",
"> \r\n> Can you create another branch and another PR please ?\r\n@lhoestq \r\n\r\nI did a rebase. Now it doesn't include the other files. Does that help? \r\n\r\n",
"Yes thanks !"
] | 2020-12-08T16:07:54Z
| 2020-12-16T10:14:17Z
| 2020-12-16T10:14:17Z
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The Dutch social media tweets dataset. Which has a total of more than 210k tweets in dutch language. These tweets have been machine annotated with sentiment scores (`label` feature) and `industry` and `hisco_codes`
It can be used for sentiment analysis, multi-label classification and entity tagging
|
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https://github.com/huggingface/datasets/pull/1320
| 1,320
|
Added the WikiText-TL39 dataset and corresponding card
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[] | 2020-12-08T16:00:26Z
| 2020-12-10T11:24:53Z
| 2020-12-10T11:24:53Z
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This PR adds the WikiText-TL-39 Filipino Language Modeling dataset. Restarted a new pull request since there were problems with the earlier one.
Paper: https://arxiv.org/abs/1907.00409
Repo: https://github.com/jcblaisecruz02/Filipino-Text-Benchmarks
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https://github.com/huggingface/datasets/pull/1319
| 1,319
|
adding wili-2018 language identification dataset
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[
"@lhoestq Not sure what happened, I just changed the py file but it is showing some TensorFlow error now.",
"You can ignore it.\r\nIt's caused by the Tensorflow update that happened 30min ago. They added breaking changes.\r\nI'm working on a fix on the master branch right now\r\n",
"oh okay, btw I have made the required change for reading the CSV, I think it should be fine now, please take a look at it when you have some time.",
"merging since the CI is fixed on master"
] | 2020-12-08T16:00:09Z
| 2020-12-14T21:20:32Z
| 2020-12-14T21:20:32Z
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https://github.com/huggingface/datasets/pull/1318
| 1,318
|
ethos first commit
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[
"> Nice thanks !\r\n> \r\n> I left a few comments\r\n> \r\n> Also it looks like this PR includes changes about other files than the ones for ethos\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\n@lhoestq Should I close this PR? The new one is the: #1453",
"You can create another PR and close this one if you don't mind",
"> You can create another PR and close this one if you don't mind\r\n\r\nPerfect! You should see the #1453 PR for the fixed version! Thanks"
] | 2020-12-08T15:59:47Z
| 2020-12-10T14:45:57Z
| 2020-12-10T14:45:57Z
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Ethos passed all the tests except from this one:
RUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_<your-dataset-name>
with this error:
E OSError: Cannot find data file.
E Original error:
E [Errno 2] No such file or directory:
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https://github.com/huggingface/datasets/pull/1317
| 1,317
|
add 10k German News Article Dataset
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[
"You can just create another branch from master on your fork and create another PR:\r\n\r\nfirst update your master branch\r\n```\r\ngit checkout master\r\ngit fetch upstream\r\ngit rebase upstream/master\r\ngit push\r\n```\r\n\r\nthen create a new branch\r\n```\r\ngit checkout -b my-new-branch-name\r\n```\r\n\r\nThen you can add, commit and push the gnad10 files and open a new PR",
"closing in favor of #1572 "
] | 2020-12-08T15:44:25Z
| 2021-09-17T16:55:51Z
| 2020-12-16T16:50:43Z
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https://github.com/huggingface/datasets/pull/1316
| 1,316
|
Allow GitHub releases as dataset source
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[] | 2020-12-08T15:39:35Z
| 2020-12-10T10:12:00Z
| 2020-12-10T10:12:00Z
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|
# Summary
Providing a GitHub release URL to `DownloadManager.download()` currently throws a `ConnectionError: Couldn't reach [DOWNLOAD_URL]`. This PR fixes this problem by adding an exception for GitHub releases in `datasets.utils.file_utils.get_from_cache()`.
# Reproduce
```
import datasets
url = 'http://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz'
result = datasets.utils.file_utils.get_from_cache(url)
# Returns: ConnectionError: Couldn't reach http://github.com/benjaminvdb/DBRD/releases/download/v3.0/DBRD_v3.tgz
```
# Cause
GitHub releases returns a HTTP status 403 (FOUND), indicating that the request is being redirected (to AWS S3, in this case). `get_from_cache()` checks whether the status is 200 (OK) or if it is part of two exceptions (Google Drive or Firebase), otherwise the mentioned error is thrown.
# Solution
Just like the exceptions for Google Drive and Firebase, add a condition for GitHub releases URLs that return the HTTP status 403. If this is the case, continue normally.
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https://github.com/huggingface/datasets/pull/1315
| 1,315
|
add yelp_review_full
|
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closed
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[] | 2020-12-08T15:38:27Z
| 2020-12-09T15:55:49Z
| 2020-12-09T15:55:49Z
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This corresponds to the Yelp-5 requested in https://github.com/huggingface/datasets/issues/353
I included the dataset card.
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https://github.com/huggingface/datasets/pull/1314
| 1,314
|
Add snips built in intents 2016 12
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[
"It is not clear how to automatically add the dummy data if the source data is a more complex json format. Should I manually take a fraction of the source data and include it as dummy data?\r\n",
"Added a fraction of the real data as dummy data.",
"merging since the CI is fixed on master"
] | 2020-12-08T15:30:19Z
| 2020-12-14T09:59:07Z
| 2020-12-14T09:59:07Z
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This PR proposes to add the Snips.ai built in intents dataset. The first configuration added is for the intent labels only, but the dataset includes entity slots that may in future be added as alternate configurations.
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https://github.com/huggingface/datasets/pull/1313
| 1,313
|
Add HateSpeech Corpus for Polish
|
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[
"@lhoestq Do you think using the ClassLabel is correct if we don't know the meaning of them?",
"Once we find out the meanings we can still add them to the dataset card",
"Feel free to ping me when the PR is ready for the final review"
] | 2020-12-08T15:23:53Z
| 2020-12-16T16:48:45Z
| 2020-12-16T16:48:45Z
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This PR adds a HateSpeech Corpus for Polish, containing offensive language examples.
- **Homepage:** http://zil.ipipan.waw.pl/HateSpeech
- **Paper:** http://www.qualitativesociologyreview.org/PL/Volume38/PSJ_13_2_Troszynski_Wawer.pdf
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|
https://github.com/huggingface/datasets/pull/1312
| 1,312
|
Jigsaw toxicity pred
|
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[] | 2020-12-08T15:19:14Z
| 2020-12-11T12:11:32Z
| 2020-12-11T12:11:32Z
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Requires manually downloading data from Kaggle.
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https://github.com/huggingface/datasets/pull/1311
| 1,311
|
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
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|
https://github.com/huggingface/datasets/pull/1310
| 1,310
|
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
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This PR adds the OffensEval-TR 2020 dataset which is a Turkish offensive language corpus by me and @basakbuluz. The corpus consist of randomly sampled tweets and annotated in a similar way to [OffensEval](https://sites.google.com/site/offensevalsharedtask/) and [GermEval](https://projects.fzai.h-da.de/iggsa/).
- **Homepage:** [offensive-turkish](https://coltekin.github.io/offensive-turkish/)
- **Paper:** [A Corpus of Turkish Offensive Language on Social Media](https://coltekin.github.io/offensive-turkish/troff.pdf)
- **Point of Contact:** [ΓaΔrΔ± ΓΓΆltekin](ccoltekin@sfs.uni-tuebingen.de)
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https://github.com/huggingface/datasets/pull/1309
| 1,309
|
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. π€ \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! π€ "
] | 2020-12-08T14:40:56Z
| 2020-12-14T12:32:33Z
| 2020-12-14T10:20:55Z
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Did not spent much time writing README, might update later.
Copied description and some stuff from tensorflow_datasets
https://github.com/tensorflow/datasets/blob/master/tensorflow_datasets/summarization/samsum.py
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https://github.com/huggingface/datasets/pull/1308
| 1,308
|
Add Wiki Lingua Dataset
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[
"I am done adding the dataset. Requesting to review and advise.",
"looks like this PR has changes about many other files than the ones for WIki Lingua \r\n\r\nCan you create another branch and another PR please ?",
"Any reason to have english as the default config over the other languages ?",
"> looks like this PR has changes about many other files than the ones for WIki Lingua\r\n> \r\n> Can you create another branch and another PR please ?\r\n\r\nOk, I will create another branch and submit a fresh PR.",
"> Any reason to have english as the default config over the other languages ?\r\n\r\nThe data for all other languages has a direct reference to English article. Thus, I kept English as default.",
"closing in favor of #1470 "
] | 2020-12-08T14:30:13Z
| 2020-12-14T10:39:52Z
| 2020-12-14T10:39:52Z
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Hello,
This is my first PR.
I have added Wiki Lingua Dataset along with dataset card to the best of my knowledge.
There was one hiccup though. I was unable to create dummy data because the data is in pkl format.
From the document, I see that:
```At the moment it supports data files in the following format: txt, csv, tsv, jsonl, json, xml```
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https://github.com/huggingface/datasets/pull/1307
| 1,307
|
adding capes
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[] | 2020-12-08T13:46:13Z
| 2020-12-09T15:40:09Z
| 2020-12-09T15:27:45Z
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Adding Parallel corpus of theses and dissertation abstracts in Portuguese and English from CAPES
https://sites.google.com/view/felipe-soares/datasets#h.p_kxOR6EhHm2a6
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https://github.com/huggingface/datasets/pull/1306
| 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
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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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https://github.com/huggingface/datasets/pull/1305
| 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
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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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https://github.com/huggingface/datasets/pull/1304
| 1,304
|
adding eitb_parcc
|
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[] | 2020-12-08T13:20:54Z
| 2020-12-09T18:02:54Z
| 2020-12-09T18:02:03Z
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|
Adding EiTB-ParCC: Parallel Corpus of Comparable News
http://opus.nlpl.eu/EiTB-ParCC.php
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https://github.com/huggingface/datasets/pull/1303
| 1,303
|
adding opus_openoffice
|
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[] | 2020-12-08T13:20:21Z
| 2020-12-10T09:37:10Z
| 2020-12-10T09:37:10Z
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|
Adding Opus OpenOffice: http://opus.nlpl.eu/OpenOffice.php
8 languages, 28 bitexts
|
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https://github.com/huggingface/datasets/pull/1302
| 1,302
|
Add Danish NER dataset
|
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| 2020-12-10T09:35:26Z
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|
https://github.com/huggingface/datasets/pull/1301
| 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
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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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https://github.com/huggingface/datasets/pull/1300
| 1,300
|
added dutch_social
|
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[] |
closed
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|
[
"Closing this since a new pull request has been made. "
] | 2020-12-08T12:47:50Z
| 2020-12-08T16:09:05Z
| 2020-12-08T16:09:05Z
|
CONTRIBUTOR
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WIP
As some tests did not clear! ππΌ
|
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| null | null | null | true
|
https://github.com/huggingface/datasets/issues/1299
| 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 |
FileNotFoundError: Couldn't find file locally at german_legal_entity_recognition/german_legal_entity_recognition.py, or remotely at https://raw.githubusercontent.com/huggingface/datasets/1.1.3/datasets/german_legal_entity_recognition/german_legal_entity_recognition.py or https://s3.amazonaws.com/datasets.huggingface.co/datasets/datasets/german_legal_entity_recognition/german_legal_entity_recognition.py
|
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Add OPUS Ted Talks 2013
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[
"merging since the CI is fixed on master"
] | 2020-12-08T12:38:38Z
| 2020-12-16T16:57:50Z
| 2020-12-16T16:57:49Z
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OPUS Ted Talks 2013
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[] | 2020-12-08T12:25:39Z
| 2023-09-24T09:51:49Z
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https://github.com/huggingface/datasets/pull/1296
| 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
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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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https://github.com/huggingface/datasets/pull/1295
| 1,295
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add hrenwac_para
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[] | 2020-12-08T11:40:06Z
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https://github.com/huggingface/datasets/pull/1294
| 1,294
|
adding opus_euconst
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[] | 2020-12-08T11:24:16Z
| 2020-12-08T18:44:20Z
| 2020-12-08T18:41:23Z
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Adding EUconst, a parallel corpus collected from the European Constitution.
21 languages, 210 bitexts
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https://github.com/huggingface/datasets/pull/1293
| 1,293
|
add hrenwac_para
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[] | 2020-12-08T11:16:41Z
| 2020-12-08T11:34:47Z
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NONE
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https://github.com/huggingface/datasets/pull/1292
| 1,292
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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
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https://github.com/huggingface/datasets/pull/1291
| 1,291
|
adding pubmed_qa dataset
|
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[] | 2020-12-08T11:05:44Z
| 2020-12-09T08:54:50Z
| 2020-12-09T08:54:50Z
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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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https://github.com/huggingface/datasets/issues/1290
| 1,290
|
imdb dataset cannot be downloaded
|
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[
"Hi @rabeehk , I am unable to reproduce your problem locally.\r\nCan you try emptying the cache (removing the content of `/idiap/temp/rkarimi/cache_home_1/datasets`) and retry ?",
"Hi,\r\nthanks, I did remove the cache and still the same error here\r\n\r\n```\r\n>>> a = datasets.load_dataset(\"imdb\", split=\"train\")\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\nDownloading and preparing dataset imdb/plain_text (download: 80.23 MiB, generated: 127.06 MiB, post-processed: Unknown size, total: 207.28 MiB) to /idiap/temp/rkarimi/cache_home_1/datasets/imdb/plain_text/1.0.0/90099cb476936b753383ba2ae6ab2eae419b2e87f71cd5189cb9c8e5814d12a3...\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads\r\nTraceback (most recent call last): \r\n File \"<stdin>\", line 1, in <module>\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py\", line 611, in load_dataset\r\n ignore_verifications=ignore_verifications,\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 476, in download_and_prepare\r\n dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 558, in _download_and_prepare\r\n verify_splits(self.info.splits, split_dict)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/info_utils.py\", line 73, in verify_splits\r\n raise NonMatchingSplitsSizesError(str(bad_splits))\r\ndatasets.utils.info_utils.NonMatchingSplitsSizesError: [{'expected': SplitInfo(name='unsupervised', num_bytes=67125548, num_examples=50000, dataset_name='imdb'), 'recorded': SplitInfo(name='unsupervised', num_bytes=4902716, num_examples=3680, dataset_name='imdb')}]\r\n```\r\n\r\ndatasets version\r\n```\r\ndatasets 1.1.2 <pip>\r\ntensorflow-datasets 4.1.0 <pip>\r\n\r\n```",
"resolved with moving to version 1.1.3"
] | 2020-12-08T10:47:36Z
| 2020-12-24T17:38:09Z
| 2020-12-24T17:38:09Z
|
CONTRIBUTOR
| null | null |
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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https://github.com/huggingface/datasets/pull/1289
| 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
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The dataset requires manually downloading data from Kaggle.
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https://github.com/huggingface/datasets/pull/1288
| 1,288
|
Add CodeSearchNet corpus dataset
|
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[
"@lhoestq ready for a second review"
] | 2020-12-08T10:07:50Z
| 2020-12-09T17:05:28Z
| 2020-12-09T17:05:28Z
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This PR adds the CodeSearchNet corpus proxy dataset for semantic code search: https://github.com/github/CodeSearchNet
I have had a few issues, mentioned below. Would appreciate some help on how to solve them.
## Issues generating dataset card
Is there something wrong with my declaration of the dataset features ?
```
features=datasets.Features(
{
"repository_name": datasets.Value("string"),
"func_path_in_repository": datasets.Value("string"),
"func_name": datasets.Value("string"),
"whole_func_string": datasets.Value("string"),
"language": datasets.Value("string"),
"func_code_string": datasets.Value("string"),
"func_code_tokens": datasets.Sequence(datasets.Value("string")),
"func_documentation_string": datasets.Value("string"),
"func_documentation_tokens": datasets.Sequence(datasets.Value("string")),
"split_name": datasets.Value("string"),
"func_code_url": datasets.Value("string"),
# TODO - add licensing info in the examples
}
),
```
When running the streamlite app for tagging the dataset on my machine, I get the following error :
## Issues with dummy data
Due to the unusual structure of the data, I have been unable to generate dummy data automatically.
I tried to generate it manually, but pytests fail when using the manually-generated dummy data ! Pytests work fine when using the real data.
```
============================================================================================== test session starts ==============================================================================================
platform linux -- Python 3.7.9, pytest-6.1.2, py-1.9.0, pluggy-0.13.1
plugins: xdist-2.1.0, forked-1.3.0
collected 1 item
tests/test_dataset_common.py F [100%]
=================================================================================================== FAILURES ====================================================================================================
________________________________________________________________________ LocalDatasetTest.test_load_dataset_all_configs_code_search_net _________________________________________________________________________
self = <tests.test_dataset_common.LocalDatasetTest testMethod=test_load_dataset_all_configs_code_search_net>, dataset_name = 'code_search_net'
@slow
def test_load_dataset_all_configs(self, dataset_name):
configs = self.dataset_tester.load_all_configs(dataset_name, is_local=True)
> self.dataset_tester.check_load_dataset(dataset_name, configs, is_local=True)
tests/test_dataset_common.py:237:
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
tests/test_dataset_common.py:198: in check_load_dataset
self.parent.assertTrue(len(dataset[split]) > 0)
E AssertionError: False is not true
--------------------------------------------------------------------------------------------- Captured stdout call ----------------------------------------------------------------------------------------------
Downloading and preparing dataset code_search_net/all (download: 1.00 MiB, generated: 1.00 MiB, post-processed: Unknown size, total: 2.00 MiB) to /tmp/tmppx78sj24/code_search_net/all/1.0.0...
Dataset code_search_net downloaded and prepared to /tmp/tmppx78sj24/code_search_net/all/1.0.0. Subsequent calls will reuse this data.
--------------------------------------------------------------------------------------------- Captured stderr call ----------------------------------------------------------------------------------------------
... (irrelevant info - Deprecation warnings)
============================================================================================ short test summary info ============================================================================================
FAILED tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_code_search_net - AssertionError: False is not true
========================================================================================= 1 failed, 4 warnings in 3.00s ========================================================================================
```
## Note : Data structure in S3
The data is stored on S3, and organized by programming languages.
It is stored in the following repository structure:
```
.
βββ <language_name> # e.g. python
βΒ Β βββ final
βΒ Β βββ jsonl
βΒ Β βββ test
βΒ Β βΒ Β βββ <language_name>_test_0.jsonl.gz
βΒ Β βββ train
βΒ Β βΒ Β βββ <language_name>_train_0.jsonl.gz
βΒ Β βΒ Β βββ <language_name>_train_1.jsonl.gz
βΒ Β βΒ Β βββ ...
βΒ Β βΒ Β βββ <language_name>_train_n.jsonl.gz
βΒ Β βββ valid
βΒ Β βββ <language_name>_valid_0.jsonl.gz
βββ <language_name>_dedupe_definitions_v2.pkl
βββ <language_name>_licenses.pkl
```
|
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'iwslt2017-ro-nl', cannot be downloaded
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"id": 2067388877,
"name": "dataset bug",
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[
"the same issue with datasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=split), ..... ",
"even with setting master like the following command, still remains \r\n\r\ndatasets.load_dataset(\"iwslt2017\", 'iwslt2017-en-nl', split=\"train\", script_version=\"master\")\r\n",
"Looks like the data has been moved from its original location to google drive\r\n\r\nNew url: https://drive.google.com/u/0/uc?id=12ycYSzLIG253AFN35Y6qoyf9wtkOjakp&export=download",
"Fixed by #4481 "
] | 2020-12-08T09:56:55Z
| 2022-06-13T10:41:33Z
| 2022-06-13T10:41:33Z
|
CONTRIBUTOR
| null | null |
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, 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'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%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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 |
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%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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%|βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ| 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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https://github.com/huggingface/datasets/issues/1285
| 1,285
|
boolq does not work
|
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[
"here is the minimal code to reproduce\r\n\r\n`datasets>>> datasets.load_dataset(\"boolq\", \"train\")\r\n\r\nthe errors\r\n\r\n```\r\n`cahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\nUsing custom data configuration train\r\nDownloading and preparing dataset boolq/train (download: Unknown size, generated: Unknown size, post-processed: Unknown size, total: Unknown size) to /idiap/temp/rkarimi/cache_home_1/datasets/boolq/train/0.1.0/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11...\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets\r\ncahce dir /idiap/temp/rkarimi/cache_home_1/datasets/downloads\r\nTraceback (most recent call last):\r\n File \"<stdin>\", line 1, in <module>\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/load.py\", line 611, in load_dataset\r\n ignore_verifications=ignore_verifications,\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 476, in download_and_prepare\r\n dl_manager=dl_manager, verify_infos=verify_infos, **download_and_prepare_kwargs\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/builder.py\", line 531, in _download_and_prepare\r\n split_generators = self._split_generators(dl_manager, **split_generators_kwargs)\r\n File \" /idiap/home/rkarimi/.cache/huggingface/modules/datasets_modules/datasets/boolq/2987db1f15deaa19500ae24de560eabeaf1f8ef51df88c0470beeec72943bf11/boolq.py\", line 74, in _split_generators\r\n downloaded_files = dl_manager.download_custom(urls_to_download, tf.io.gfile.copy)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/datasets/utils/download_manager.py\", line 149, in download_custom\r\n custom_download(url, path)\r\n File \"/idiap/user/rkarimi/libs/anaconda3/envs/internship/lib/python3.7/site-packages/tensorflow/python/lib/io/file_io.py\", line 516, in copy_v2\r\n compat.path_to_bytes(src), compat.path_to_bytes(dst), overwrite)\r\n\r\n\r\n\r\n```",
"This has been fixed by #881 \r\nthis fix will be available in the next release soon.\r\n\r\nIf you don't want to wait for the release you can actually load the latest version of boolq by specifying `script_version=\"master\"` in `load_dataset`",
"thank you this solved this issue, for now seems to work, thanks "
] | 2020-12-08T09:28:47Z
| 2020-12-08T09:47:10Z
| 2020-12-08T09:47:10Z
|
CONTRIBUTOR
| null | null |
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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https://github.com/huggingface/datasets/pull/1284
| 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
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CONTRIBUTOR
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`datasets.stanford.edu` is invalid.
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https://github.com/huggingface/datasets/pull/1283
| 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! π I went ahead and improved the dataset card using your suggestions and some tweaks of my own. I hope you like it! π"
] | 2020-12-08T08:50:48Z
| 2020-12-09T20:21:58Z
| 2020-12-09T17:25:25Z
|
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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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https://github.com/huggingface/datasets/pull/1282
| 1,282
|
add thaiqa_squad
|
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[] | 2020-12-08T08:14:38Z
| 2020-12-08T18:36:18Z
| 2020-12-08T18:36:18Z
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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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