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https://api.github.com/repos/huggingface/datasets/issues/1087 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1087/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1087/comments | https://api.github.com/repos/huggingface/datasets/issues/1087/events | https://github.com/huggingface/datasets/pull/1087 | 756,794,430 | MDExOlB1bGxSZXF1ZXN0NTMyMjc5NDI3 | 1,087 | Add Big Patent dataset | {
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"@lhoestq reduced the dummy data size to around 19MB in total and added the dataset card.",
"@lhoestq so I ended up removing all the nested JSON objects in the gz datafile and keep only one object with minimal content: `{\"publication_number\": \"US-8230922-B2\", \"abstract\": \"dummy abstract\", \"application_number\": \"US-201113163519-A\", \"description\": \"dummy description\"}`. \r\n\r\nThey're reduced to 35KB in total (2.5KB per domain and 17.5KB for all domains), hopefully, they're small enough."
] | 1,607,056,650,000 | 1,607,275,260,000 | 1,607,275,259,000 | CONTRIBUTOR | null | * More info on the dataset: https://evasharma.github.io/bigpatent/
* There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later. | {
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"> Thanks for adding this one !\r\n> \r\n> I left a few comments\r\n> \r\n> after the change you'll need to regenerate the dataset_infos.json file as well\r\n\r\ndataset_infos.json regenerated",
"looks like this PR includes changes to many files other that the ones for CDT\r\ncould you create another branch and another PR please ?"
] | 1,607,045,291,000 | 1,607,094,242,000 | 1,607,094,242,000 | CONTRIBUTOR | null | - **Name:** *Cyberbullying Detection Task*
- **Description:** *The Cyberbullying Detection task was part of 2019 edition of PolEval competition. The goal is to predict if a given Twitter message contains a cyberbullying (harmful) content.*
- **Data:** *https://github.com/ptaszynski/cyberbullying-Polish*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.* | {
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"Ready for review"
] | 1,607,042,901,000 | 1,608,134,311,000 | 1,608,134,310,000 | MEMBER | null | Mutual friends dataset
WIP
TODO:
- scenario_kbs (bug with pyarrow conversion)
- download from codalab checksums bug | {
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- **Description**: *Polish CDSCorpus consists of 10K Polish sentence pairs which are human-annotated for semantic relatedness and entailment. The dataset may be used for the evaluation of compositional distributional semantics models of Polish. The dataset was presented at ACL 2017. Please refer to the Wróblewska and Krasnowska-Kieraś (2017) for a detailed description of the resource.*
- **Data**: *http://2019.poleval.pl/index.php/tasks/*
- **Motivation**: *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.* | {
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"Will slim down the dummy files in the morning"
] | 1,607,040,364,000 | 1,607,101,920,000 | 1,607,101,920,000 | MEMBER | null | https://github.com/mhardalov/exams-qa
`multilingual` configs have all languages mixed together
`crosslingual` mixes the languages for test but separates them for train and dec, so I've made one config per language for train/dev data and one config with the joint test set | {
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"merging since the CI is fixed on master"
] | 1,607,038,740,000 | 1,607,076,818,000 | 1,607,076,818,000 | CONTRIBUTOR | null | Add news topic classification dataset in Myanmar / Burmese languagess
This data was collected in 2017 by Aye Hninn Khine , and published on GitHub with a GPL license
https://github.com/ayehninnkhine/MyanmarNewsClassificationSystem
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- Webpage/repo: https://github.com/google-research-datasets/KELM-corpus
- Paper: https://arxiv.org/pdf/2010.12688.pdf | {
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"Dataset card added, so ready for review!"
] | 1,607,036,964,000 | 1,607,275,135,000 | 1,607,275,135,000 | MEMBER | null | This PR adds the full set of 176 languages from the balanced train/dev/test splits of WikiANN / PAN-X from: https://github.com/afshinrahimi/mmner
Until now, only 40 of these languages were available in `datasets` as part of the XTREME benchmark
Courtesy of the dataset author, we can now download this dataset from a Dropbox URL without needing a manual download anymore 🥳, so at some point it would be worth updating the PAN-X subset of XTREME as well 😄
Link to gist with some snippets for producing dummy data: https://gist.github.com/lewtun/5b93294ab6dbcf59d1493dbe2cfd6bb9
P.S. @yjernite I think I was confused about needing to generate a set of YAML tags per config, so ended up just adding a single one in the README. | {
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- **Description:** *The NKJP-NER is based on a human-annotated part of NKJP. We extracted sentences with named entities of exactly one type. The task is to predict the type of the named entity.*
- **Data:** *https://klejbenchmark.com/tasks/*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.*
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"pan"
] | 1,607,028,929,000 | 1,607,099,799,000 | 1,607,073,320,000 | MEMBER | null | Add QUAC (Question Answering in Context)
I linearized most of the dictionnaries to lists.
Referenced to the authors' datasheet for the dataset card.
🦆🦆🦆
Coin coin | {
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- All tests passed successfully. | {
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https://api.github.com/repos/huggingface/datasets/issues/1071 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1071/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1071/comments | https://api.github.com/repos/huggingface/datasets/issues/1071/events | https://github.com/huggingface/datasets/pull/1071 | 756,447,296 | MDExOlB1bGxSZXF1ZXN0NTMxOTkwNzY1 | 1,071 | add xlrd to test package requirements | {
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https://api.github.com/repos/huggingface/datasets/issues/1070 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1070/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1070/comments | https://api.github.com/repos/huggingface/datasets/issues/1070/events | https://github.com/huggingface/datasets/pull/1070 | 756,442,481 | MDExOlB1bGxSZXF1ZXN0NTMxOTg2Nzcz | 1,070 | add conv_ai | {
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"This one will make @thomwolf reminisce ;)",
"Merging."
] | 1,607,019,920,000 | 1,607,068,715,000 | 1,607,064,274,000 | MEMBER | null | Adding ConvAI dataset https://github.com/DeepPavlov/convai/tree/master/2017 | {
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https://api.github.com/repos/huggingface/datasets/issues/1069 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1069/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1069/comments | https://api.github.com/repos/huggingface/datasets/issues/1069/events | https://github.com/huggingface/datasets/pull/1069 | 756,425,737 | MDExOlB1bGxSZXF1ZXN0NTMxOTcyNjYz | 1,069 | Test | {
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https://api.github.com/repos/huggingface/datasets/issues/1068 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1068/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1068/comments | https://api.github.com/repos/huggingface/datasets/issues/1068/events | https://github.com/huggingface/datasets/pull/1068 | 756,417,337 | MDExOlB1bGxSZXF1ZXN0NTMxOTY1MDk0 | 1,068 | Add Pubmed (citation + abstract) dataset (2020). | {
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"LGTM! ftp addition looks fine but maybe have a look @thomwolf ?",
"It's not finished yet, I need to run the tests on the full dataset (it was running this weekend, there is an error somewhere deep)\r\n",
"@yjernite Ready for review !\r\n@thomwolf \r\n\r\nSo I tried to follow closely the original format that means I still had to drop information (namely tags on elements are simply discarded for now but they don't seem to carry critical information).\r\nSome elements are also discarded they tend to not come up often:\r\n - The most notable is Author affiliation, which seems to be all over the place in terms of what it look meaning it's hard to actually get a consistent format.\r\n - Journal is the same, all the elements in there can be wildly different so I decided to drop it for now instead of trying to figure out a way to have a common presentation. (the DOI and medline ID are present so it can be recovered).\r\n\r\nI think this PR could go as it but we probably should add a way to get easier information to use with a config.\r\nFor instance `{\"title\": \"string\", \"abstract\": \"string\", \"authors\": List[str], \"substances\": List[str]}` maybe ? (substances for instance is a tricky one, some substances only have an international identifier, some have simply a common name, some both)\r\n\r\nIt's relatively easy to do I think it's mostly discarding other fields and renaming some deep structure into a flat one.",
"Look ok to me but @lhoestq is the master on the Download Manager side"
] | 1,607,018,050,000 | 1,608,717,127,000 | 1,608,717,127,000 | CONTRIBUTOR | null | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1067 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1067/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1067/comments | https://api.github.com/repos/huggingface/datasets/issues/1067/events | https://github.com/huggingface/datasets/pull/1067 | 756,414,212 | MDExOlB1bGxSZXF1ZXN0NTMxOTYyNDYx | 1,067 | add xquad-r dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1066 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1066/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1066/comments | https://api.github.com/repos/huggingface/datasets/issues/1066/events | https://github.com/huggingface/datasets/pull/1066 | 756,391,957 | MDExOlB1bGxSZXF1ZXN0NTMxOTQ0MDc0 | 1,066 | Add ChrEn | {
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"I just saw your PR actually ^^",
"> I just saw your PR actually ^^\r\n\r\nSomehow that still doesn't work, lmk if you have any ideas.",
"Did you rebase from master ?"
] | 1,607,015,868,000 | 1,607,032,179,000 | 1,607,032,179,000 | MEMBER | null | Adding the Cherokee English machine translation dataset of https://github.com/ZhangShiyue/ChrEn | {
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https://api.github.com/repos/huggingface/datasets/issues/1065 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1065/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1065/comments | https://api.github.com/repos/huggingface/datasets/issues/1065/events | https://github.com/huggingface/datasets/pull/1065 | 756,383,414 | MDExOlB1bGxSZXF1ZXN0NTMxOTM2OTQ3 | 1,065 | add xquad-r dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1064 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1064/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1064/comments | https://api.github.com/repos/huggingface/datasets/issues/1064/events | https://github.com/huggingface/datasets/issues/1064 | 756,382,186 | MDU6SXNzdWU3NTYzODIxODY= | 1,064 | Not support links with 302 redirect | {
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"Hi !\r\nThis kind of links is now supported by the library since #1316",
"> Hi !\r\n> This kind of links is now supported by the library since #1316\r\n\r\nI updated links in TLC datasets to be the github links in this pull request \r\n https://github.com/huggingface/datasets/pull/1737\r\n\r\nEverything works now. Thank you."
] | 1,607,015,083,000 | 1,610,592,685,000 | 1,610,592,685,000 | CONTRIBUTOR | null | I have an issue adding this download link https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz
it might be because it is not a direct link (it returns 302 and redirects to aws that returns 403 for head requests).
```
r.head("https://github.com/jitkapat/thailitcorpus/releases/download/v.2.0/tlc_v.2.0.tar.gz", allow_redirects=True)
# <Response [403]>
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1063 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1063/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1063/comments | https://api.github.com/repos/huggingface/datasets/issues/1063/events | https://github.com/huggingface/datasets/pull/1063 | 756,376,374 | MDExOlB1bGxSZXF1ZXN0NTMxOTMxMTMz | 1,063 | Add the Ud treebank | {
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"merging since the CI is fixed on master"
] | 1,607,014,601,000 | 1,607,098,314,000 | 1,607,097,106,000 | CONTRIBUTOR | null | This PR adds the 183 datasets in 104 languages of the UD Treebank. | {
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https://api.github.com/repos/huggingface/datasets/issues/1062 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1062/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1062/comments | https://api.github.com/repos/huggingface/datasets/issues/1062/events | https://github.com/huggingface/datasets/pull/1062 | 756,373,187 | MDExOlB1bGxSZXF1ZXN0NTMxOTI4NDY5 | 1,062 | Add KorNLU dataset | {
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"Nice thank you !\r\nCan you regenerate the dataset_infos.json file ? Since we changed the features we must update it\r\n\r\nThen I think we'll be good to merge :)"
] | 1,607,014,359,000 | 1,607,079,919,000 | 1,607,079,919,000 | CONTRIBUTOR | null | Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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https://api.github.com/repos/huggingface/datasets/issues/1061 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1061/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1061/comments | https://api.github.com/repos/huggingface/datasets/issues/1061/events | https://github.com/huggingface/datasets/pull/1061 | 756,362,661 | MDExOlB1bGxSZXF1ZXN0NTMxOTE5ODA0 | 1,061 | add labr dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1060 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1060/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1060/comments | https://api.github.com/repos/huggingface/datasets/issues/1060/events | https://github.com/huggingface/datasets/pull/1060 | 756,349,001 | MDExOlB1bGxSZXF1ZXN0NTMxOTA4MTgx | 1,060 | Fix squad V2 metric script | {
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"The script with changes is used and tested in [#8924](https://github.com/huggingface/transformers/pull/8924). It gives the same results as the old `evaluate_squad` function when used on the same predictions.",
"merging since the CI is fixed on master"
] | 1,607,012,612,000 | 1,608,649,340,000 | 1,608,649,339,000 | MEMBER | null | The current squad v2 metric doesn't work with the squad (v1 or v2) datasets. The script is copied from `squad_evaluate` in transformers that requires the labels (with multiple answers) to be like this:
```
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
```
while the dataset had references like this:
```
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
```
Using one or the other format fails with the current squad v2 metric:
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers': [
{'text': 'Denver Broncos', 'answer_start': 177},
{'text': 'Denver Broncos', 'answer_start': 177}
]}]
metric.compute(predictions=predictions, references=references)
```
fails as well as
```
from datasets import load_metric
metric = load_metric("squad_v2")
predictions = [{'id': 'a', 'prediction_text': 'Denver Broncos', 'no_answer_probability': 0.0}]
references = [{'id': 'a', 'answers':
{'text': ['Denver Broncos' 'Denver Broncos'], 'answer_start': [177, 177]}
}]
metric.compute(predictions=predictions, references=references)
```
This is because arrow reformats the references behind the scene.
With this PR (tested locally), both the snippets up there work and return proper results. | {
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https://api.github.com/repos/huggingface/datasets/issues/1059 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1059/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1059/comments | https://api.github.com/repos/huggingface/datasets/issues/1059/events | https://github.com/huggingface/datasets/pull/1059 | 756,348,623 | MDExOlB1bGxSZXF1ZXN0NTMxOTA3ODYy | 1,059 | Add TLC | {
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"I have reduced the size of the dummy file and added README sections as you suggested. ",
"I have a little issue to run the test. It seems there is no failed case in my machine. ",
"Thanks !\r\nIt looks like the PR includes changes to many other files than the ones of `tlc`, can you create another branch and another PR ?"
] | 1,607,012,586,000 | 1,607,080,533,000 | 1,607,080,533,000 | CONTRIBUTOR | null | Added TLC dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1058 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1058/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1058/comments | https://api.github.com/repos/huggingface/datasets/issues/1058/events | https://github.com/huggingface/datasets/pull/1058 | 756,332,704 | MDExOlB1bGxSZXF1ZXN0NTMxODk0Mjc0 | 1,058 | added paws-x dataset | {
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} | [] | closed | false | null | [] | null | [] | 1,607,011,561,000 | 1,607,089,565,000 | 1,607,089,565,000 | CONTRIBUTOR | null | Added paws-x dataset. Updating README and tags in the dataset card in a while | {
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https://api.github.com/repos/huggingface/datasets/issues/1057 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1057/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1057/comments | https://api.github.com/repos/huggingface/datasets/issues/1057/events | https://github.com/huggingface/datasets/pull/1057 | 756,331,419 | MDExOlB1bGxSZXF1ZXN0NTMxODkzMjE4 | 1,057 | Adding TamilMixSentiment | {
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"looks like this pr incldues changes about many other files than the ones for tamilMixSentiment, could you create another branch and another PR ?"
] | 1,607,011,465,000 | 1,607,076,574,000 | 1,607,076,552,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1056 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1056/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1056/comments | https://api.github.com/repos/huggingface/datasets/issues/1056/events | https://github.com/huggingface/datasets/pull/1056 | 756,309,828 | MDExOlB1bGxSZXF1ZXN0NTMxODc1MjA2 | 1,056 | Add deal_or_no_dialog | {
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} | [] | closed | false | null | [] | null | [] | 1,607,009,887,000 | 1,607,019,225,000 | 1,607,019,225,000 | CONTRIBUTOR | null | Add deal_or_no_dialog Dataset
github: https://github.com/facebookresearch/end-to-end-negotiator
Paper: [Deal or No Deal? End-to-End Learning for Negotiation Dialogues](https://arxiv.org/abs/1706.05125) | {
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https://api.github.com/repos/huggingface/datasets/issues/1055 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1055/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1055/comments | https://api.github.com/repos/huggingface/datasets/issues/1055/events | https://github.com/huggingface/datasets/pull/1055 | 756,298,372 | MDExOlB1bGxSZXF1ZXN0NTMxODY1NjM4 | 1,055 | Add hebrew-sentiment | {
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"@elronbandel it looks like something went wrong with the renaming, as the old files are still in the PR. Can you `git rm datasets/hebrew-sentiment` ?",
"merging since the CI is fixed on master",
"This is the old version of the data.\r\nHere is the fixed version.\r\nhttps://github.com/OnlpLab/Hebrew-Sentiment-Data\r\n\r\nI hope I would find time to open a PR. I think it supposed to be only to change the data path ",
"Cool ! Sure feel free to open a PR if you have some time :) and feel free to ping me for review or if you have questions"
] | 1,607,009,071,000 | 1,645,457,165,000 | 1,607,081,056,000 | CONTRIBUTOR | null | hebrew-sentiment dataset is ready! (including tests, tags etc) | {
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https://api.github.com/repos/huggingface/datasets/issues/1054 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1054/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1054/comments | https://api.github.com/repos/huggingface/datasets/issues/1054/events | https://github.com/huggingface/datasets/pull/1054 | 756,265,688 | MDExOlB1bGxSZXF1ZXN0NTMxODM3NzQ0 | 1,054 | Add dataset - SemEval 2014 - Task 1 | {
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"Added the dataset card.\r\nRequesting another review."
] | 1,607,007,179,000 | 1,607,043,164,000 | 1,607,043,164,000 | CONTRIBUTOR | null | Adding the dataset of SemEval 2014 Task 1
Found the dataset under the shared Google Sheet > Recurring Task Datasets
Task Homepage - https://alt.qcri.org/semeval2014/task1
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/1053 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1053/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1053/comments | https://api.github.com/repos/huggingface/datasets/issues/1053/events | https://github.com/huggingface/datasets/pull/1053 | 756,176,061 | MDExOlB1bGxSZXF1ZXN0NTMxNzYyNzg4 | 1,053 | Fix dataset URL and file names, and add column name in "Social Bias Frames" dataset | {
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"Thanks a lot, looks good!"
] | 1,607,000,585,000 | 1,607,002,946,000 | 1,607,002,946,000 | CONTRIBUTOR | null | # Why I did
When I use "social_bias_frames" datasets in this library, I got 404 Errors.
So, I fixed this error and another some problems that I faced to use the dataset.
# What I did
* Modify this dataset URL
* Modify this dataset file names
* Add a "dataSource" column
Thank you! | {
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https://api.github.com/repos/huggingface/datasets/issues/1052 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1052/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1052/comments | https://api.github.com/repos/huggingface/datasets/issues/1052/events | https://github.com/huggingface/datasets/pull/1052 | 756,171,798 | MDExOlB1bGxSZXF1ZXN0NTMxNzU5MjA0 | 1,052 | add sharc dataset | {
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More info:
https://sharc-data.github.io/index.html | {
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https://api.github.com/repos/huggingface/datasets/issues/1051 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1051/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1051/comments | https://api.github.com/repos/huggingface/datasets/issues/1051/events | https://github.com/huggingface/datasets/pull/1051 | 756,169,049 | MDExOlB1bGxSZXF1ZXN0NTMxNzU2OTQy | 1,051 | Add Facebook SimpleQuestionV2 | {
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"I think @thomwolf may also be working on this one as part of the Babi benchmark in #945 "
] | 1,607,000,000,000 | 1,607,016,719,000 | 1,607,016,718,000 | MEMBER | null | Add simple questions v2: https://research.fb.com/downloads/babi/ | {
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https://api.github.com/repos/huggingface/datasets/issues/1050 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1050/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1050/comments | https://api.github.com/repos/huggingface/datasets/issues/1050/events | https://github.com/huggingface/datasets/pull/1050 | 756,166,728 | MDExOlB1bGxSZXF1ZXN0NTMxNzU1MDQ3 | 1,050 | Add GoEmotions | {
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"Whoops, didn't mean for that to be merged yet (my bad). I'm reaching out to the authors since we'd like their feedback on the best way to have the `author` field anonymized or removed. Will send a patch once they get back to me."
] | 1,606,999,793,000 | 1,607,017,065,000 | 1,607,016,608,000 | CONTRIBUTOR | null | Adds the GoEmotions dataset, a nice emotion classification dataset with 27 (multi-)label annotations on reddit comments. Includes both a large raw version and a narrowed version with predefined train/test/val splits, which I've included as separate configs with the latter as a default.
- Webpage/repo: https://github.com/google-research/google-research/tree/master/goemotions
- Paper: https://arxiv.org/abs/2005.00547 | {
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https://api.github.com/repos/huggingface/datasets/issues/1049 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1049/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1049/comments | https://api.github.com/repos/huggingface/datasets/issues/1049/events | https://github.com/huggingface/datasets/pull/1049 | 756,157,602 | MDExOlB1bGxSZXF1ZXN0NTMxNzQ3NDY0 | 1,049 | Add siswati ner corpus | {
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"merging since the CI is fixed on master"
] | 1,606,996,765,000 | 1,607,088,597,000 | 1,607,088,597,000 | CONTRIBUTOR | null | https://repo.sadilar.org/handle/20.500.12185/7/discover?filtertype_0=database&filtertype_1=title&filter_relational_operator_1=contains&filter_relational_operator_0=equals&filter_1=&filter_0=Monolingual+Text+Corpora%3A+Annotated&filtertype=project&filter_relational_operator=equals&filter=NCHLT+Text+II | {
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https://api.github.com/repos/huggingface/datasets/issues/1047 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1047/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1047/comments | https://api.github.com/repos/huggingface/datasets/issues/1047/events | https://github.com/huggingface/datasets/pull/1047 | 756,127,490 | MDExOlB1bGxSZXF1ZXN0NTMxNzIyMjk4 | 1,047 | Add KorNLU | {
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"the CI error about `social_bias_frames` is fixed on master so it's fine",
"created new [PR](https://github.com/huggingface/datasets/pull/1062)",
"looks like this PR includes many changes to other files that the ones related to KorNLU\r\nCould you create another branch and another PR please ?",
"Wow crazy timing",
"hahahaha"
] | 1,606,996,254,000 | 1,607,015,827,000 | 1,607,015,769,000 | CONTRIBUTOR | null | Added Korean NLU datasets. The link to the dataset can be found [here](https://github.com/kakaobrain/KorNLUDatasets) and the paper can be found [here](https://arxiv.org/abs/2004.03289)
**Note**: The MNLI tsv file is broken, so this code currently excludes the file. Please suggest other alternative if any @lhoestq
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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https://api.github.com/repos/huggingface/datasets/issues/1046 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1046/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1046/comments | https://api.github.com/repos/huggingface/datasets/issues/1046/events | https://github.com/huggingface/datasets/issues/1046 | 756,122,709 | MDU6SXNzdWU3NTYxMjI3MDk= | 1,046 | Dataset.map() turns tensors into lists? | {
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"A solution is to have the tokenizer return a list instead of a tensor, and then use `dataset_tok.set_format(type = 'torch')` to convert that list into a tensor. Still not sure if bug.",
"It is expected behavior, you should set the format to `\"torch\"` as you mentioned to get pytorch tensors back.\r\nBy default datasets returns pure python objects."
] | 1,606,995,826,000 | 1,608,731,472,000 | null | NONE | null | I apply `Dataset.map()` to a function that returns a dict of torch tensors (like a tokenizer from the repo transformers). However, in the mapped dataset, these tensors have turned to lists!
```import datasets
import torch
from datasets import load_dataset
print("version datasets", datasets.__version__)
dataset = load_dataset("snli", split='train[0:50]')
def tokenizer_fn(example):
# actually uses a tokenizer which does something like:
return {'input_ids': torch.tensor([[0, 1, 2]])}
print("First item in dataset:\n", dataset[0])
tokenized = tokenizer_fn(dataset[0])
print("Tokenized hyp:\n", tokenized)
dataset_tok = dataset.map(tokenizer_fn, batched=False,
remove_columns=['label', 'premise', 'hypothesis'])
print("Tokenized using map:\n", dataset_tok[0])
print(type(tokenized['input_ids']), type(dataset_tok[0]['input_ids']))
dataset_tok = dataset.map(tokenizer_fn, batched=False,
remove_columns=['label', 'premise', 'hypothesis'])
print("Tokenized using map:\n", dataset_tok[0])
print(type(tokenized['input_ids']), type(dataset_tok[0]['input_ids']))
```
The output is:
```
version datasets 1.1.3
Reusing dataset snli (/home/tom/.cache/huggingface/datasets/snli/plain_text/1.0.0/bb1102591c6230bd78813e229d5dd4c7fbf4fc478cec28f298761eb69e5b537c)
First item in dataset:
{'premise': 'A person on a horse jumps over a broken down airplane.', 'hypothesis': 'A person is training his horse for a competition.', 'label': 1}
Tokenized hyp:
{'input_ids': tensor([[0, 1, 2]])}
Loading cached processed dataset at /home/tom/.cache/huggingface/datasets/snli/plain_text/1.0.0/bb1102591c6230bd78813e229d5dd4c7fbf4fc478cec28f298761eb69e5b537c/cache-fe38f449fe9ac46f.arrow
Tokenized using map:
{'input_ids': [[0, 1, 2]]}
<class 'torch.Tensor'> <class 'list'>
```
Or am I doing something wrong?
| {
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https://api.github.com/repos/huggingface/datasets/issues/1045 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1045/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1045/comments | https://api.github.com/repos/huggingface/datasets/issues/1045/events | https://github.com/huggingface/datasets/pull/1045 | 756,120,760 | MDExOlB1bGxSZXF1ZXN0NTMxNzE2NzIy | 1,045 | Add xitsonga ner corpus | {
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"Look like this PR includes changes to many other files than the ones related to xitsonga NER.\r\nCould you create another branch and another PR please ?"
] | 1,606,995,648,000 | 1,607,016,003,000 | 1,607,015,972,000 | CONTRIBUTOR | null | {
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paper: https://www.aclweb.org/anthology/W17-1307/ | {
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"Looks like this PR include changes about many other files than the ones related to big patent.\r\nCould you create another branch and another PR ?",
"@lhoestq Just created a new PR here: https://github.com/huggingface/datasets/pull/1087"
] | 1,606,993,679,000 | 1,607,056,706,000 | 1,607,056,706,000 | CONTRIBUTOR | null | - More info on the dataset: https://evasharma.github.io/bigpatent/
- There's another raw version of the dataset available from tfds. However, they're quite large so I don't have the resources to fully test all the configs for that version yet. We'll try to add it later.
- ~Currently, there are no dummy data for this dataset yet as I'm facing some problems with generating them. I'm trying to add them later.~ | {
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- UN page: https://www.ohchr.org/EN/UDHR/Pages/UDHRIndex.aspx
- Raw data source: https://unicode.org/udhr/index.html
Each instance of the dataset corresponds to one translation of the document. Since there's only one instance per language (and because there are 500 languages so the dummy data would be messy), I opted to just include them all under the same single config. I wasn't able to find any kind of license so I just copied the copyright notice.
I was pretty careful careful generating the language tags so they _should_ all be correct & consistent BCP-47 codes per the docs. | {
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https://api.github.com/repos/huggingface/datasets/issues/1039 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1039/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1039/comments | https://api.github.com/repos/huggingface/datasets/issues/1039/events | https://github.com/huggingface/datasets/pull/1039 | 756,000,478 | MDExOlB1bGxSZXF1ZXN0NTMxNjE3MDI2 | 1,039 | Update ADD NEW DATASET | {
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https://api.github.com/repos/huggingface/datasets/issues/1038 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1038/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1038/comments | https://api.github.com/repos/huggingface/datasets/issues/1038/events | https://github.com/huggingface/datasets/pull/1038 | 755,987,997 | MDExOlB1bGxSZXF1ZXN0NTMxNjA2Njgw | 1,038 | add med_hop | {
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More info:
http://qangaroo.cs.ucl.ac.uk/index.html | {
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https://api.github.com/repos/huggingface/datasets/issues/1037 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1037/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1037/comments | https://api.github.com/repos/huggingface/datasets/issues/1037/events | https://github.com/huggingface/datasets/pull/1037 | 755,975,586 | MDExOlB1bGxSZXF1ZXN0NTMxNTk2NDkx | 1,037 | Fix docs indentation issues | {
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"is this an issue ?",
"Yes @lhoestq, look at the docs site. For example, in https://huggingface.co/docs/datasets/add_dataset.html, look at the indentation in the code block under the sentence:\r\n> Here are the features of the SQuAD dataset for instance, which is taken from the squad dataset loading script:"
] | 1,606,983,694,000 | 1,608,652,875,000 | 1,608,652,875,000 | MEMBER | null | Replace tabs with spaces. | {
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https://api.github.com/repos/huggingface/datasets/issues/1036 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1036/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1036/comments | https://api.github.com/repos/huggingface/datasets/issues/1036/events | https://github.com/huggingface/datasets/pull/1036 | 755,953,294 | MDExOlB1bGxSZXF1ZXN0NTMxNTc4MjQ4 | 1,036 | Add PerSenT | {
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"looks like this PR contains changes in many other files than the ones for PerSenT\r\ncan you create another branch and another PR ?",
"closing since #1142 was merged"
] | 1,606,981,438,000 | 1,607,953,243,000 | 1,607,953,243,000 | CONTRIBUTOR | null | Added [Person's SentimenT](https://stonybrooknlp.github.io/PerSenT/) dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/1035 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1035/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1035/comments | https://api.github.com/repos/huggingface/datasets/issues/1035/events | https://github.com/huggingface/datasets/pull/1035 | 755,947,097 | MDExOlB1bGxSZXF1ZXN0NTMxNTczMTc3 | 1,035 | add wiki_hop | {
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"Also the dummy data files are quite big (500KB)\r\nIf you could reduce that that would be nice (just look at the files inside and remove unecessary chunks of texts)\r\nin general dummy data are just a few KB and we suggest to not get higher than 50KB\r\n\r\nHaving light dummy data makes the repo faster to clone"
] | 1,606,980,746,000 | 1,607,013,820,000 | 1,607,013,672,000 | MEMBER | null | This PR adds the WikiHop dataset from the QAngaroo multi hop reading comprehension datasets
More info:
http://qangaroo.cs.ucl.ac.uk/index.html
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https://api.github.com/repos/huggingface/datasets/issues/1034 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1034/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1034/comments | https://api.github.com/repos/huggingface/datasets/issues/1034/events | https://github.com/huggingface/datasets/pull/1034 | 755,936,327 | MDExOlB1bGxSZXF1ZXN0NTMxNTY0MjA0 | 1,034 | add scb_mt_enth_2020 | {
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The primary objective of our work is to build a large-scale English-Thai dataset for machine translation.
We construct an English-Thai machine translation dataset with over 1 million segment pairs, curated from various sources,
namely news, Wikipedia articles, SMS messages, task-based dialogs, web-crawled data and government documents.
Methodology for gathering data, building parallel texts and removing noisy sentence pairs are presented in a reproducible manner.
We train machine translation models based on this dataset. Our models' performance are comparable to that of
Google Translation API (as of May 2020) for Thai-English and outperform Google when the Open Parallel Corpus (OPUS) is
included in the training data for both Thai-English and English-Thai translation.
The dataset, pre-trained models, and source code to reproduce our work are available for public use. | {
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https://api.github.com/repos/huggingface/datasets/issues/1033 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1033/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1033/comments | https://api.github.com/repos/huggingface/datasets/issues/1033/events | https://github.com/huggingface/datasets/pull/1033 | 755,921,927 | MDExOlB1bGxSZXF1ZXN0NTMxNTUxNzYw | 1,033 | Add support for ".txm" format | {
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"Neat! Looks like you need a rebase and then should be good to go :) ",
"Done, @yjernite, @lhoestq.",
"If you agree, we could merge this.",
"Hi ! yes sure :) can you just merge master into this branch before we merge ?",
"Done @lhoestq "
] | 1,606,978,328,000 | 1,613,936,831,000 | 1,613,936,831,000 | MEMBER | null | In dummy data generation, add support for XML-like ".txm" file format.
Also support filenames with additional compression extension: ".txm.gz". | {
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https://api.github.com/repos/huggingface/datasets/issues/1032 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1032/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1032/comments | https://api.github.com/repos/huggingface/datasets/issues/1032/events | https://github.com/huggingface/datasets/pull/1032 | 755,858,785 | MDExOlB1bGxSZXF1ZXN0NTMxNDk2MTU2 | 1,032 | IIT B English to Hindi machine translation dataset | {
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"Please note that this dataset is actually behind a form that one needs to fill. However, the link is direct. I'm not sure what should the approach be in this case.",
"also pinging @thomwolf \r\nThe dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).\r\nHowever the url we get with the form can be used for the dataset script.\r\nShould we ask the authors or use the urls this way ?",
"> also pinging @thomwolf\r\n> The dataset webpage returns a form when trying to download the dataset (form here : http://www.cfilt.iitb.ac.in/iitb_parallel/dataset.html).\r\n> However the url we get with the form can be used for the dataset script.\r\n> Should we ask the authors or use the urls this way ?\r\n\r\nI had discussion on this with @thomwolf . We have already sent email to author of this dataset.",
"Hi @spatil6 !\r\nAny news from the authors ?",
"IIT B folks will add this dataset to repo."
] | 1,606,972,725,000 | 1,610,268,291,000 | 1,610,268,255,000 | CONTRIBUTOR | null | Adding IIT Bombay English-Hindi Corpus dataset
more info : http://www.cfilt.iitb.ac.in/iitb_parallel/ | {
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https://api.github.com/repos/huggingface/datasets/issues/1031 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1031/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1031/comments | https://api.github.com/repos/huggingface/datasets/issues/1031/events | https://github.com/huggingface/datasets/pull/1031 | 755,844,004 | MDExOlB1bGxSZXF1ZXN0NTMxNDgyMzEy | 1,031 | add crows_pairs | {
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"looks good now :) wdyt @yjernite ?",
"Looks good to merge for me, can edit the dataset card later if required. Merging"
] | 1,606,971,911,000 | 1,607,020,192,000 | 1,607,020,179,000 | MEMBER | null | This PR adds CrowS-Pairs datasets.
More info:
https://github.com/nyu-mll/crows-pairs/
https://arxiv.org/pdf/2010.00133.pdf | {
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https://api.github.com/repos/huggingface/datasets/issues/1030 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1030/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1030/comments | https://api.github.com/repos/huggingface/datasets/issues/1030/events | https://github.com/huggingface/datasets/pull/1030 | 755,777,438 | MDExOlB1bGxSZXF1ZXN0NTMxNDI0MDM3 | 1,030 | allegro_reviews dataset | {
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- **Description:** *Allegro Reviews is a sentiment analysis dataset, consisting of 11,588 product reviews written in Polish and extracted from Allegro.pl - a popular e-commerce marketplace. Each review contains at least 50 words and has a rating on a scale from one (negative review) to five (positive review).*
- **Data:** *https://github.com/allegro/klejbenchmark-allegroreviews*
- **Motivation:** *The KLEJ benchmark (Kompleksowa Lista Ewaluacji Językowych) is a set of nine evaluation tasks for the Polish language understanding.* | {
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https://api.github.com/repos/huggingface/datasets/issues/1029 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1029/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1029/comments | https://api.github.com/repos/huggingface/datasets/issues/1029/events | https://github.com/huggingface/datasets/pull/1029 | 755,767,616 | MDExOlB1bGxSZXF1ZXN0NTMxNDE2NzE4 | 1,029 | Add PEC | {
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"I'm a bit frustrated now to get this right.",
"Hey @zhongpeixiang!\r\nReally nice addition here!\r\n\r\nDid you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?\r\nI can't seem to find you there! Should I add you directly with your gmail address?",
"> Hey @zhongpeixiang!\r\n> Really nice addition here!\r\n> \r\n> Did you officially joined the sprint by posting [on the forum thread](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176) and joining our slack?\r\n> I can't seem to find you there! Should I add you directly with your gmail address?\r\n\r\nThank you for the invitation. This initiative is awesome. Sadly I’m occupied by my thesis writing this month. Good luck 🤗",
"As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do)",
"> As you want @zhongpeixiang (I was maybe not clear but that just mean that by posting on the forum thread that you participated in the current event you will get a special gift (a tee-shirt) for the contribution that you have already done here :-) Nothing more to do)\r\n\r\nOh, I misunderstood the post. I'm glad to join."
] | 1,606,963,568,000 | 1,607,079,499,000 | 1,607,012,106,000 | CONTRIBUTOR | null | A persona-based empathetic conversation dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/1028 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1028/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1028/comments | https://api.github.com/repos/huggingface/datasets/issues/1028/events | https://github.com/huggingface/datasets/pull/1028 | 755,712,854 | MDExOlB1bGxSZXF1ZXN0NTMxMzc0MTYw | 1,028 | Add ASSET dataset for text simplification evaluation | {
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"Nice, thanks @yjernite !!"
] | 1,606,955,309,000 | 1,608,199,386,000 | 1,607,013,277,000 | MEMBER | null | Adding the ASSET dataset from https://github.com/facebookresearch/asset
One config for the simplification data, one for the human ratings of quality.
The README.md borrows from that written by @juand-r | {
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https://api.github.com/repos/huggingface/datasets/issues/1027 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1027/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1027/comments | https://api.github.com/repos/huggingface/datasets/issues/1027/events | https://github.com/huggingface/datasets/issues/1027 | 755,695,420 | MDU6SXNzdWU3NTU2OTU0MjA= | 1,027 | Hi | {
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} | [] | closed | false | null | [] | null | [] | 1,606,952,834,000 | 1,607,013,761,000 | 1,607,013,761,000 | NONE | null | ## Adding a Dataset
- **Name:** *name of the dataset*
- **Description:** *short description of the dataset (or link to social media or blog post)*
- **Paper:** *link to the dataset paper if available*
- **Data:** *link to the Github repository or current dataset location*
- **Motivation:** *what are some good reasons to have this dataset*
Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md). | {
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https://api.github.com/repos/huggingface/datasets/issues/1026 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1026/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1026/comments | https://api.github.com/repos/huggingface/datasets/issues/1026/events | https://github.com/huggingface/datasets/issues/1026 | 755,689,195 | MDU6SXNzdWU3NTU2ODkxOTU= | 1,026 | Lío o | {
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```
O
```
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Ño
```
````
``` | {
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https://api.github.com/repos/huggingface/datasets/issues/1025 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1025/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1025/comments | https://api.github.com/repos/huggingface/datasets/issues/1025/events | https://github.com/huggingface/datasets/pull/1025 | 755,673,371 | MDExOlB1bGxSZXF1ZXN0NTMxMzQxNjE5 | 1,025 | Add Sesotho Ner | {
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"looks like this PR include changes to other files (sepedi)\r\ncould you try to only include the files related to the addition of sesotho ner ?",
"I think i need to clean up my local repo. I am committing everything a fresh after sepedi",
"Feel free to ping me when yuo have a clean PR and it's ready to review :)",
"closing in favor of #1114 "
] | 1,606,950,015,000 | 1,608,136,023,000 | 1,608,136,022,000 | CONTRIBUTOR | null | {
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"Looks good to me, we can ping the authors for more info later. And yes apply `other-task` labels liberally, we can sort them out later :) \r\n\r\nLooks ready to merge when you're ready @joeddav "
] | 1,606,948,880,000 | 1,607,023,260,000 | 1,607,011,755,000 | CONTRIBUTOR | null | Adds the ZEST dataset on zero-shot learning from task descriptions from AI2.
- Webpage: https://allenai.org/data/zest
- Paper: https://arxiv.org/abs/2011.08115
The nature of this dataset made the supported task tags tricky if you wouldn't mind giving any feedback @yjernite. Also let me know if you think we should have a `other-task-generalization` or something like that... | {
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- https://github.com/google-research-datasets/dstc8-schema-guided-dialogue
A bit simpler than MultiWOZ, the only tricky thing is the sequence of dictionaries that had to be linearized. There is a config for the data proper, and a config for the schemas. | {
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"THanks!\r\nDone!"
] | 1,606,947,476,000 | 1,607,042,066,000 | 1,607,042,065,000 | MEMBER | null | MRQA (shared task 2019)
out of distribution generalization
Framed as extractive question answering
Dataset is the concatenation (of subsets) of existing QA datasets processed to match the SQuAD format | {
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"Description: \"A clean data resource containing all explicit time references in a dataset of 52,183 novels whose full text is available via Project Gutenberg and the Hathi Trust Digital Library 2.\" > This is just the Gutenberg part.\r\n\r\nAlso, the paragraph at the top of the file would make a good Dataset Summary in the README :) "
] | 1,606,946,726,000 | 1,606,991,619,000 | 1,606,991,618,000 | MEMBER | null | This PR adds the gutenberg_time dataset: https://arxiv.org/abs/2011.04124 | {
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"Sorry for this. I deleted sepedi_ner_corpus as per your earlier advise. Let me check. "
] | 1,606,939,265,000 | 1,607,032,023,000 | 1,607,031,998,000 | CONTRIBUTOR | null | This is a new branch created for this dataset | {
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"Thanks!"
] | 1,606,938,045,000 | 1,606,956,265,000 | 1,606,956,265,000 | MEMBER | null | If not specified, Python uses system default, which for Windows is not "utf-8". | {
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- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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"Thanks @sumanthd17 that fixed it. "
] | 1,606,933,656,000 | 1,607,007,834,000 | 1,607,007,834,000 | CONTRIBUTOR | null | Hotel Reviews in Arabic language. | {
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"@lhoestq please review this PR when you get free",
"If the CI fails just because of `RemoteDatasetTest` errors it's fine, they're fixed on master",
"> If the CI fails just because of `RemoteDatasetTest` errors it's fine, they're fixed on master\r\n\r\nThe same 3 tests are failing again :(\r\n```\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_class_norwegian_ner\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_builder_configs_norwegian_ner\r\nFAILED tests/test_dataset_common.py::RemoteDatasetTest::test_load_dataset_norwegian_ner\r\n```",
"One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors",
"> One trick if you want to add more datasets to avoid these errors : you can just rebase the master branch of your fork from the master branch of the repo. Then each time you make a new branch from master on your fork, it will include the fix for these errors\r\n\r\nYes, I almost always do that, but somehow seems even this branch got old 😓 \r\nI also do the following if I directly create a new branch locally: `git checkout -b <branchname> upstream/master` so it stays up-to date irrespective of my fork, still don't know how this crept in again",
"Merging this one since the CI is fixed on master"
] | 1,606,933,370,000 | 1,606,935,310,000 | 1,606,934,278,000 | CONTRIBUTOR | null | Adds the SciTLDR Dataset by AI2
Added the `README.md` card with tags to the best of my knowledge
Multi-target summaries or TLDRs of Scientific Documents
Continued from #986 | {
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https://arxiv.org/pdf/2005.04177.pdf | {
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"IMO, the problem with this dataset is that it is not really a text/nlp dataset. These are just collections of tweet ids. So, ultimately, one needs to crawl twitter to get the actual text.",
"That's true.\r\n\r\n",
"at least it's clear in the description that one needs to collect the tweets : \r\n```\r\nThis resource is a result of a generic method for collecting parallel tweets.\r\n```",
"Looks like this is failing for other datasets. Should I rebase it and push again?\r\nAlso rebasing and pushing is reflecting changes in many other files (ultimately forcing me to open a new branch and a new PR) any way to avoid this?",
"No let me merge this one directly, it's fine",
"merging since the CI is fixed on master"
] | 1,606,929,602,000 | 1,607,093,110,000 | 1,607,093,073,000 | CONTRIBUTOR | null | Added Bilingual Corpus of Arabic-English Parallel Tweets. The link to the dataset can be found [here](https://alt.qcri.org/wp-content/uploads/2020/08/Bilingual-Corpus-of-Arabic-English-Parallel-Tweets.zip) and the paper can be found [here](https://www.aclweb.org/anthology/2020.bucc-1.3.pdf)
- [x] Followed the instructions in CONTRIBUTING.md
- [x] Ran the tests successfully
- [x] Created the dummy data | {
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"Dupe of #1009 "
] | 1,606,922,885,000 | 1,606,923,655,000 | 1,606,923,655,000 | CONTRIBUTOR | null | null | {
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"feel free to merge/ping me to merge if there're no more changes to do"
] | 1,606,922,173,000 | 1,607,013,878,000 | 1,606,932,092,000 | MEMBER | null | This PR adds yahoo answers topic classification dataset.
More info:
https://github.com/LC-John/Yahoo-Answers-Topic-Classification-Dataset
cc @joeddav, @yjernite | {
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"This library uses Apache Arrow under the hood to store datasets on disk.\r\nThe advantage of Apache Arrow is that it allows to memory map the dataset. This allows to load datasets bigger than memory and with almost no RAM usage. It also offers excellent I/O speed.\r\n\r\nFor example when you access one element or one batch\r\n```python\r\nfrom datasets import load_dataset\r\n\r\nsquad = load_dataset(\"squad\", split=\"train\")\r\nfirst_element = squad[0]\r\none_batch = squad[:8]\r\n```\r\n\r\nthen only this element/batch is loaded in memory, while the rest of the dataset is memory mapped.",
"How can we change how much data is loaded to memory with Arrow? I think that I am having some performance issue with it. When Arrow loads the data from disk it does it in multiprocess? It's almost twice slower training with arrow than in memory.\r\n\r\nEDIT:\r\nMy fault! I had not seen the `dataloader_num_workers` in `TrainingArguments` ! Now I can parallelize and go fast! Sorry, and thanks.",
"> How can we change how much data is loaded to memory with Arrow? I think that I am having some performance issue with it. When Arrow loads the data from disk it does it in multiprocess? It's almost twice slower training with arrow than in memory.\r\n\r\nLoading arrow data from disk is done with memory-mapping. This allows to load huge datasets without filling your RAM.\r\nMemory mapping is almost instantaneous and is done within one process.\r\n\r\nThen, the speed of querying examples from the dataset is I/O bounded depending on your disk. If it's an SSD then fetching examples from the dataset will be very fast.\r\nBut since the I/O speed of an SSD is lower than the one of RAM it's expected to be slower to fetch data from disk than from memory.\r\nStill, if you load the dataset in different processes then it can be faster but there will still be the I/O bottleneck of the disk.\r\n\r\n> EDIT:\r\n> My fault! I had not seen the `dataloader_num_workers` in `TrainingArguments` ! Now I can parallelize and go fast! Sorry, and thanks.\r\n\r\nOk let me know if that helps !\r\n"
] | 1,606,919,560,000 | 1,612,175,031,000 | null | NONE | null | Hi
I want to use multiple large datasets with a mapping style dataloader, where they cannot fit into memory, could you tell me how you handled the datasets under the hood? is this you bring all in memory in case of mapping style ones? or is this some sharding under the hood and you bring in memory when necessary, thanks | {
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github repo: https://github.com/yaolu/Multi-XScience
paper: [Multi-XScience: A Large-scale Dataset for Extreme Multi-document Summarization of Scientific Articles](https://arxiv.org/abs/2010.14235) | {
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"Could you fix the dummy data before we merge ?\r\nLooks like the dummy `train.csv` is missing",
"Thanks @Narsil @lhoestq for adding MeDAL :)"
] | 1,606,918,397,000 | 1,607,360,283,000 | 1,607,001,273,000 | CONTRIBUTOR | null | null | {
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More info:
https://ciir.cs.umass.edu/downloads/nfL6/ | {
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"#978 is working on adding code refinement\r\n\r\nmaybe we should keep the CodeXGlue benchmark (as glue) and don't merge the code_refinement dataset proposed in #978 ?\r\n\r\ncc @reshinthadithyan",
"Hi @madlag and @lhoestq , I am extremely interested in getting this dataset into HF's library as I research in this area a lot. I see that it hasn't been updated in a while, but it is very close to being finished. If no one is currently working on this, I'd be happy to do any final touches that might be needed to get this merged.",
"Hi @ncoop57 ! Thanks for your interest and sorry for the inactivity on this PR.\r\nSure feel free to create another PR to continue this one ! This one was really close to being merged so I think it won't require that much changes. In addition to my previous comments, there should also be a \"Contributions\" subsection (see the template of the README [here](https://github.com/huggingface/datasets/blob/master/templates/README.md))",
"Superseded by https://github.com/huggingface/datasets/pull/2357 ."
] | 1,606,908,078,000 | 1,623,159,745,000 | 1,623,159,744,000 | CONTRIBUTOR | null | Datasets from https://github.com/microsoft/CodeXGLUE
This contains 13 datasets:
code_x_glue_cc_clone_detection_big_clone_bench
code_x_glue_cc_clone_detection_poj_104
code_x_glue_cc_cloze_testing_all
code_x_glue_cc_cloze_testing_maxmin
code_x_glue_cc_code_completion_line
code_x_glue_cc_code_completion_token
code_x_glue_cc_code_refinement
code_x_glue_cc_code_to_code_trans
code_x_glue_cc_defect_detection
code_x_glue_ct_code_to_text
code_x_glue_tc_nl_code_search_adv
code_x_glue_tc_text_to_code
code_x_glue_tt_text_to_text
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"Looks like the google drive download failed.\r\nI'm getting a `Google Drive - Quota exceeded` error while looking at the downloaded file.\r\n\r\nWe should consider finding a better host than google drive for this dataset imo\r\nrelated : #873 #864 ",
"It is working now, thank you. \r\n\r\nShould I leave this issue open to address the Quota-exceeded error?",
"Yes please. It's been happening several times, we definitely need to address it",
"Any updates on this one? I'm facing a similar issue trying to add CelebA.",
"I've looked into it and couldn't find a solution. This looks like a Google Drive limitation..\r\nPlease try to use other hosts when possible",
"The original links are google drive links. Would it be feasible for HF to maintain their own servers for this? Also, I think the same issue must also exist with TFDS.",
"It's possible to host data on our side but we should ask the authors. TFDS has the same issue and doesn't have a solution either afaik.\r\nOtherwise you can use the google drive link, but it it's not that convenient because of this quota issue.",
"Okay. I imagine asking every author who shares their dataset on Google Drive will also be cumbersome.",
"I am getting this error as well. Is there a fix?",
"Not as long as the data is stored on GG drive unfortunately.\r\nMaybe we can ask if there's a mirror ?\r\n\r\nHi @JafferWilson is there a download link to get cnn dailymail from another host than GG drive ?\r\n\r\nTo give you some context, this library provides tools to download and process datasets. For CNN DailyMail the data are downloaded from the link you provide on your github repository. Unfortunately because of GG drive quotas, many users are not able to load this dataset.",
"The following copy of CNN/DM dataset, fixed the problem for me:\r\nhttps://huggingface.co/datasets/ccdv/cnn_dailymail",
"Thanks for the link @mrazizi !\r\n\r\nApparently the original authors don't host the dataset themselves (\"for legal reasons\", source [here](https://github.com/abisee/cnn-dailymail/issues/9))."
] | 1,606,907,276,000 | 1,645,107,219,000 | 1,645,107,219,000 | NONE | null |
Downloading and preparing dataset cnn_dailymail/3.0.0 (download: 558.32 MiB, generated: 1.28 GiB, post-processed: Unknown size, total: 1.82 GiB) to /root/.cache/huggingface/datasets/cnn_dailymail/3.0.0/3.0.0/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602...
---------------------------------------------------------------------------
NotADirectoryError Traceback (most recent call last)
<ipython-input-9-cd4bf8bea840> in <module>()
22
23
---> 24 train = load_dataset('cnn_dailymail', '3.0.0', split='train')
25 validation = load_dataset('cnn_dailymail', '3.0.0', split='validation')
26 test = load_dataset('cnn_dailymail', '3.0.0', split='test')
5 frames
/root/.cache/huggingface/modules/datasets_modules/datasets/cnn_dailymail/0128610a44e10f25b4af6689441c72af86205282d26399642f7db38fa7535602/cnn_dailymail.py in _find_files(dl_paths, publisher, url_dict)
132 else:
133 logging.fatal("Unsupported publisher: %s", publisher)
--> 134 files = sorted(os.listdir(top_dir))
135
136 ret_files = []
NotADirectoryError: [Errno 20] Not a directory: '/root/.cache/huggingface/datasets/downloads/1bc05d24fa6dda2468e83a73cf6dc207226e01e3c48a507ea716dc0421da583b/cnn/stories' | {
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"Blocked @k125-ak ;) Bye-bye"
] | 1,606,907,199,000 | 1,607,079,496,000 | 1,606,988,377,000 | CONTRIBUTOR | null | Dataset Circa added. Only README.md and dataset card left | {
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"Looks like the PR includes commits about many other files.\r\nCould you create a clean branch from master, and create another PR ?",
"Sorry, will do that. "
] | 1,606,905,007,000 | 1,606,990,754,000 | 1,606,933,208,000 | CONTRIBUTOR | null | {
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"Hi @hfawaz ! This is working fine for me. Is it a repeated occurence? Have you tried from the latest verion?",
"Hi, it seems a connection problem. \r\nNow it says: \r\n`ConnectionError: Couldn't reach https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/train/dataset_ja_train.json`"
] | 1,606,904,157,000 | 1,607,074,693,000 | null | CONTRIBUTOR | null | Thanks for adding the dataset.
After trying to load the dataset, I am getting the following error:
`ConnectionError: Couldn't reach https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/train/dataset_fr_train.json
`
I used the following code to load the dataset:
`load_dataset(
dataset_name,
"all_languages",
cache_dir=".data"
)`
I am using version 1.1.3 of `datasets`
Note that I can perform a successfull `wget https://amazon-reviews-ml.s3-us-west-2.amazonaws.com/json/train/dataset_fr_train.json` | {
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More info here : http://www.macs.hw.ac.uk/InteractionLab/E2E/
### 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 and at least fill the tags
- [x] Both tests for the real data and the dummy data pass.
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"my implementation of sharding per TPU core: https://github.com/google-research/ruse/blob/d4dd58a2d8efe0ffb1a9e9e77e3228d6824d3c3c/seq2seq/trainers/t5_trainer.py#L316 \r\nmy implementation of dataloader for this case https://github.com/google-research/ruse/blob/d4dd58a2d8efe0ffb1a9e9e77e3228d6824d3c3c/seq2seq/tasks/tasks.py#L496 "
] | 1,606,898,715,000 | 1,606,899,034,000 | null | CONTRIBUTOR | null | Hi
I am dealing with large-scale datasets which I need to train distributedly, I used the shard function to divide the dataset across the cores, without any sampler, this does not work for distributed training and does not become any faster than 1 TPU core. 1) how I can make sure data is not loaded in memory 2) in case of distributed training with iterative datasets which measures needs to be taken? Is this all sharding the data only. I was wondering if there can be possibility for me to discuss this with someone with distributed training with iterative datasets using dataset library. thanks | {
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