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https://api.github.com/repos/huggingface/datasets/issues/1159 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1159/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1159/comments | https://api.github.com/repos/huggingface/datasets/issues/1159/events | https://github.com/huggingface/datasets/pull/1159 | 757,661,128 | MDExOlB1bGxSZXF1ZXN0NTMzMDAyNzYx | 1,159 | Add Roman Urdu dataset | {
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"Hi @avinsit123 !\r\nDid you manage to rename the dataset and apply the suggestion I mentioned for the data fields ?\r\nFeel free to ping me when you're ready for a review :) ",
"Hi @avinsit123 ! Have you had a chance to take a look at my suggestions ?\r\nLet me know if you have questions or if I can help",
"@lhoestq sorry I completely forgot about this pr. I will complete it ASAP.",
"@lhoestq I have fixed the code to resolve all your comments. Pls do check. I also don't seem to know why the CI tests are failing as I ran all the tests in CONTRIBUTING.md on my local pc and they passed.",
"@lhoestq thanks for ur patient review :) . I also wish to add similar 3 more NLI hindi datasets. Hope to do within this week.",
"@lhoestq would this be merged to master?",
"Yes of course ;)\r\nmerging now !"
] | 1,607,167,534,000 | 1,612,518,511,000 | 1,612,518,511,000 | CONTRIBUTOR | null | # Dataset Card for BBC Hindi NLI Dataset
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- HomePage : https://github.com/midas-research/hindi-nli-data
- Paper : "https://www.aclweb.org/anthology/2020.aacl-main.71"
- Point of Contact : https://github.com/midas-research/hindi-nli-data
### Dataset Summary
- Dataset for Natural Language Inference in Hindi Language. BBC Hindi Dataset consists of textual-entailment pairs.
- Each row of the Datasets if made up of 4 columns - Premise, Hypothesis, Label and Topic.
- Context and Hypothesis is written in Hindi while Entailment_Label is in English.
- Entailment_label is of 2 types - entailed and not-entailed.
- Dataset can be used to train models for Natural Language Inference tasks in Hindi Language.
[More Information Needed]
### Supported Tasks and Leaderboards
- Natural Language Inference for Hindi
### Languages
Dataset is in Hindi
## Dataset Structure
- Data is structured in TSV format.
- Train and Test files are in seperate files
### Dataset Instances
An example of 'train' looks as follows.
```
{'hypothesis': 'यह खबर की सूचना है|', 'label': 'entailed', 'premise': 'गोपनीयता की नीति', 'topic': '1'}
```
### Data Fields
- Each row contatins 4 columns - Premise, Hypothesis, Label and Topic.
### Data Splits
- Train : 15553
- Valid : 2581
- Test : 2593
## Dataset Creation
- We employ a recasting technique from Poliak et al. (2018a,b) to convert publicly available BBC Hindi news text classification datasets in Hindi and pose them as TE problems
- In this recasting process, we build template hypotheses for each class in the label taxonomy
- Then, we pair the original annotated sentence with each of the template hypotheses to create TE samples.
- For more information on the recasting process, refer to paper "https://www.aclweb.org/anthology/2020.aacl-main.71"
### Source Data
Source Dataset for the recasting process is the BBC Hindi Headlines Dataset(https://github.com/NirantK/hindi2vec/releases/tag/bbc-hindi-v0.1)
#### Initial Data Collection and Normalization
- BBC Hindi News Classification Dataset contains 4, 335 Hindi news headlines tagged across 14 categories: India, Pakistan,news, International, entertainment, sport, science, China, learning english, social, southasia, business, institutional, multimedia
- We processed this dataset to combine two sets of relevant but low prevalence classes.
- Namely, we merged the samples from Pakistan, China, international, and southasia as one class called international.
- Likewise, we also merged samples from news, business, social, learning english, and institutional as news.
- Lastly, we also removed the class multimedia because there were very few samples.
#### Who are the source language producers?
Pls refer to this paper: "https://www.aclweb.org/anthology/2020.aacl-main.71"
### Annotations
#### Annotation process
Annotation process has been described in Dataset Creation Section.
#### Who are the annotators?
Annotation is done automatically.
### Personal and Sensitive Information
No Personal and Sensitive Information is mentioned in the Datasets.
## Considerations for Using the Data
Pls refer to this paper: https://www.aclweb.org/anthology/2020.aacl-main.71
### Discussion of Biases
Pls refer to this paper: https://www.aclweb.org/anthology/2020.aacl-main.71
### Other Known Limitations
No other known limitations
## Additional Information
Pls refer to this link: https://github.com/midas-research/hindi-nli-data
### Dataset Curators
It is written in the repo : https://github.com/avinsit123/hindi-nli-data that
- This corpus can be used freely for research purposes.
- The paper listed below provide details of the creation and use of the corpus. If you use the corpus, then please cite the paper.
- If interested in commercial use of the corpus, send email to [email protected].
- If you use the corpus in a product or application, then please credit the authors and Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi appropriately. Also, if you send us an email, we will be thrilled to know about how you have used the corpus.
- Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi, India disclaims any responsibility for the use of the corpus and does not provide technical support. However, the contact listed above will be happy to respond to queries and clarifications.
- Rather than redistributing the corpus, please direct interested parties to this page
- Please feel free to send us an email:
- with feedback regarding the corpus.
- with information on how you have used the corpus.
- if interested in having us analyze your data for natural language inference.
- if interested in a collaborative research project.
### Licensing Information
Copyright (C) 2019 Multimodal Digital Media Analysis Lab - Indraprastha Institute of Information Technology, New Delhi (MIDAS, IIIT-Delhi).
Pls contact authors for any information on the dataset.
### Citation Information
```
@inproceedings{uppal-etal-2020-two,
title = "Two-Step Classification using Recasted Data for Low Resource Settings",
author = "Uppal, Shagun and
Gupta, Vivek and
Swaminathan, Avinash and
Zhang, Haimin and
Mahata, Debanjan and
Gosangi, Rakesh and
Shah, Rajiv Ratn and
Stent, Amanda",
booktitle = "Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing",
month = dec,
year = "2020",
address = "Suzhou, China",
publisher = "Association for Computational Linguistics",
url = "https://www.aclweb.org/anthology/2020.aacl-main.71",
pages = "706--719",
abstract = "An NLP model{'}s ability to reason should be independent of language. Previous works utilize Natural Language Inference (NLI) to understand the reasoning ability of models, mostly focusing on high resource languages like English. To address scarcity of data in low-resource languages such as Hindi, we use data recasting to create NLI datasets for four existing text classification datasets. Through experiments, we show that our recasted dataset is devoid of statistical irregularities and spurious patterns. We further study the consistency in predictions of the textual entailment models and propose a consistency regulariser to remove pairwise-inconsistencies in predictions. We propose a novel two-step classification method which uses textual-entailment predictions for classification task. We further improve the performance by using a joint-objective for classification and textual entailment. We therefore highlight the benefits of data recasting and improvements on classification performance using our approach with supporting experimental results.",
}
```
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More info : http://opus.nlpl.eu/XhosaNavy.php | {
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"Glad to have more Japanese data! Couple of comments:\r\n- the abbreviation might confuse some people as there is also an OPUS BSD corpus, would you mind renaming it as `bsd_ja_en`?\r\n- `flake8` is throwing some errors, you can run it locally (`flake8 datasets`) and fix what it tells you until it's happy :)\r\n- We're not using `os.path.join` for URLs as it's unstable across systems (introduces backslashes on Windows). Can you write the URLs explicitly instead?\r\n\r\nThanks!",
"Fantastic, looks great!",
"> Fantastic, looks great!\r\n\r\nThanks for your help @yjernite, really appreciate it!",
"The RemoteDatasetTest is fixed on master so it's fine",
"merging since the CI is fixed on master"
] | 1,607,165,028,000 | 1,607,333,266,000 | 1,607,333,266,000 | CONTRIBUTOR | null | This PR adds BSD, the Japanese-English business dialogue corpus by
[Rikters et al., 2020](https://www.aclweb.org/anthology/D19-5204.pdf). | {
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for more info : http://opus.nlpl.eu/sardware.php | {
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https://api.github.com/repos/huggingface/datasets/issues/1153 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1153/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1153/comments | https://api.github.com/repos/huggingface/datasets/issues/1153/events | https://github.com/huggingface/datasets/pull/1153 | 757,643,302 | MDExOlB1bGxSZXF1ZXN0NTMyOTkwMTk4 | 1,153 | Adding dataset for proto_qa in huggingface datasets library | {
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Followed all steps for adding a new dataset. | {
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"That's a great dataset to have! We need a couple more things to be good to go:\r\n- you should `make style` and `flake8 datasets` before pushing to make the code quality check happy :) \r\n- the dataset will need some dummy data which you should be able to auto-generate and test locally: https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#automatically-add-code-metadata\r\n- there's some good information in your current README, but we need the format to follow the template [here](https://github.com/huggingface/datasets/blob/master/templates/README.md) and to have YAML tags at the top, as described in the guide: https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card\r\n\r\nLEt us know if you need any help!",
"Hi @yjernite \r\nI was successfully able to generate the dataset_info.json file using the command \r\npython datasets-cli test datasets/<your-dataset-folder> --save_infos --all_configs\r\n\r\nBut unfortunately, could not generate the dummy data\r\n\r\nWhile running the command \r\npython datasets-cli dummy_data datasets/<your-dataset-folder> --auto_generate\r\nI got an error as \r\n\r\nValueError: Couldn't parse columns ['0', '1', '2', '3', '4', ......, '9982']. Maybe specify which json field must be used to read the data with --json_field <my_field>.\r\n\r\nThe thing is the dataset I am trying to upload is of the format \r\n{\r\n '0': {'Story_no': 15, 'Sentence': ' गाँठ से साढ़े तीन रुपये लग गये, जो अब पेट में जाकर खनकते भी नहीं! जो तेरी करनी मालिक! ” “इसमें मालिक की क्या करनी है? ”', 'Discourse Mode': 'Dialogue'},\r\n '1': {'Story_no': story_no, 'Sentence': sentence, 'Discourse Mode': discourse_mode},\r\n .......,\r\n '9982': {'Story_no': story_no, 'Sentence': sentence, 'Discourse Mode': discourse_mode}\r\n}\r\n\r\nCan you please suggest any errors I am making in the _generate_examples method?\r\n\r\nThanks!",
"The dummy data generator doesn't support this kind of json format yet.\r\nCan you create the dummy data manually please ? You can get the instructions by running the \r\n```\r\ndatasets-cli dummy_data ./datasets/dataset_name\r\n```\r\ncommand.",
"Hi, I created the dummy data manually but the tests are still failing it seems.\r\nCan you suggest the format of JSON which is supported by dummy data generator?\r\nI will have to modify my _generate_examples method accordingly.\r\nPlease advice on the same.\r\nThanks much.\r\n",
"Can you run `make style` to format the code for the CI please ?\r\n\r\nAlso about the dummy data, here is how to generate them:\r\n\r\nWe need a dummy_data.zip file in ./datasets/hindiDiscourse/dummy/1.0.0 (or replace hindiDiscourse by hindi_discourse since we have to rename the folder anyway)\r\nTo create the zip file, first go in this directory and create a folder named dummy_data.\r\nThen inside the dummy_data folder create a file `discourse_dataset.json` and fill it with something like 5 examples.\r\nFinally zip the dummy_data folder to end up with the dummy_data.zip file\r\n\r\nOnce it's done you can check if the dummy data test passes with \r\n```\r\nRUN_SLOW=1 pytest tests/test_dataset_common.py::LocalDatasetTest::test_load_dataset_all_configs_hindi_discourse\r\n```\r\n\r\nIf it passes you can then remove the dummy_data folder to keep only the dummy_data.zip file",
"Hi @duttahritwik did you manage to make the dummy data ?\r\nFeel free to ping me if you have questions or if we can help",
"The error `tests/test_file_utils.py::TempSeedTest::test_tensorflow` just appeared because of tensorflow's update.\r\nOnce it's fixed on master we'll be free to merge this one",
"Ci is green on master :) ",
"merging since the CI is fixed on master"
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"thanks @lhoestq ! I probably need to do the same change in the `SplitGenerator`s (lines 107, 110 and 113). I'll open a new PR for that",
"Yes indeed ! Good catch 👍 \r\nFeel free to open a PR and ping me"
] | 1,607,125,491,000 | 1,607,191,730,000 | 1,607,186,101,000 | CONTRIBUTOR | null | {
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"Hi @j-chim ! You're right it does feel redundant: your option works better, but I'd even suggest having the references in a Sequence feature, which you can declare as:\r\n```\r\n\t features=datasets.Features(\r\n {\r\n \"sentence\": datasets.Value(\"string\"),\r\n \"corrections\": datasets.Sequence(datasets.Value(\"string\")),\r\n }\r\n ),\r\n```\r\n\r\nTo create the dummy data, you just need to tell the generator which files it should use, which you can do with:\r\n`python datasets-cli dummy_data datasets/<your-dataset-folder> --auto_generate --match_text_files \"train*,dev*,test*\"`\r\n",
"Many thanks for this @yjernite! I've incorporated your feedback and sorted out the dummy data."
] | 1,607,121,398,000 | 1,607,278,564,000 | 1,607,278,564,000 | CONTRIBUTOR | null | This PR adds [JFLEG ](https://www.aclweb.org/anthology/E17-2037/), an English grammatical error correction benchmark.
The tests were successful on real data, although it would be great if I can get some guidance on the **dummy data**. Basically, **for each source sentence there are 4 possible gold standard target sentences**. The original dataset comprise files in a flat structure, labelled by split then by source/target (e.g., dev.src, dev.ref0, ..., dev.ref3). Not sure what is the best way of adding this.
I imagine I can treat each distinct source-target pair as its own split? But having so many copies of the source sentence feels redundant, and it would make it less convenient to end-users who might want to access multiple gold standard targets simultaneously. | {
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- https://cs.nyu.edu/faculty/davise/papers/WinogradSchemas/WS.html
The data format was a bit of a nightmare but I think I got it to a workable format. | {
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https://api.github.com/repos/huggingface/datasets/issues/1142 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1142/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1142/comments | https://api.github.com/repos/huggingface/datasets/issues/1142/events | https://github.com/huggingface/datasets/pull/1142 | 757,413,920 | MDExOlB1bGxSZXF1ZXN0NTMyNzk1MjY0 | 1,142 | Fix PerSenT | {
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https://api.github.com/repos/huggingface/datasets/issues/1141 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1141/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1141/comments | https://api.github.com/repos/huggingface/datasets/issues/1141/events | https://github.com/huggingface/datasets/pull/1141 | 757,411,057 | MDExOlB1bGxSZXF1ZXN0NTMyNzkyNzU3 | 1,141 | Add GitHub version of ETH Py150 Corpus | {
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"The `RemoteDatasetTest` is fixed on master so it's fine",
"thanks for rebasing :)\r\n\r\nCI is green now, merging"
] | 1,607,116,568,000 | 1,607,538,764,000 | 1,607,335,224,000 | CONTRIBUTOR | null | Add the redistributable version of **ETH Py150 Corpus** | {
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"@lhoestq have made the suggested changes in the README file.",
"@lhoestq Created a new PR #1231 with only the relevant files.\r\nclosing this one :)"
] | 1,607,115,327,000 | 1,607,311,643,000 | 1,607,311,643,000 | CONTRIBUTOR | null | Added Urdu Sentiment Corpus. More details about the dataset over <a href="https://github.com/MuhammadYaseenKhan/Urdu-Sentiment-Corpus">here</a>. | {
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"Cool dataset! Replying in-line:\r\n\r\n> This PR adds the **ReFreSD dataset**.\r\n> The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data.\r\n> \r\n> Need feedback on:\r\n> \r\n> * I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work.\r\n\r\nyou can use `--match_text_files` in the dummy data generation:\r\n`python datasets-cli dummy_data datasets/refresd --auto_generate --match_text_files \"REFreSD_rationale\"`\r\n\r\n> * The feature names.\r\n> \r\n> * I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit.\r\n\r\nIt would actually be even better to use the `Translation` feature here to replace best:\r\n`\"sentence_pair\": datasets.Translation(languages=['en', 'fr']),`\r\n\r\nThen during `_generate_examples` this filed should look like\"\r\n`{\"sentence_pair\": {\"fr\": french, \"en\": english}}`\r\n\r\n> * There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better.\r\nLooks good!\r\n\r\n> * The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple.\r\n\r\nHaving the feature declared as `\"rationale_en\": datasets.Sequence(datasets.Value(\"int32\"))` should work\r\n\r\n> \r\n> Thanks in advance\r\n\r\nHope that helps you out! Don't forget to `make style`, rebase from master, and run all the tests before pushing again! You will also need to add a `README.md` as described in the guide:\r\nhttps://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md#tag-the-dataset-and-write-the-dataset-card",
"Thanks a lot for the answer, that does help a lot !\r\nI opened a PR for a License in the original repo so I was waiting for that for the model card. If there is no news on Monday, I'll add it without License. ",
"Looks good! It looks like it might need a rebase to pass the tests. Once you do that, should be good to go!"
] | 1,607,114,711,000 | 1,608,134,478,000 | 1,608,134,478,000 | CONTRIBUTOR | null | This PR adds the **ReFreSD dataset**.
The original data is hosted [on this github repo](https://github.com/Elbria/xling-SemDiv) and we use the `REFreSD_rationale` to expose all the data.
Need feedback on:
- I couldn't generate the dummy data. The file we download is a tsv file, but without extension, I suppose this is the problem. I'm sure there is a simple trick to make this work.
- The feature names.
- I don't know if it's better to stick to the classic `sentence1`, `sentence2` or to `sentence_en`, `sentence_fr` to be more explicit.
- There is a binary label (called `label`, no problem here), and a 3-class label called `#3_labels` in the original tsv. I changed it to `all_labels` but I'm sure there is better.
- The rationales are lists of integers, extracted as a string at first. I wonder what's the best way to treat them, any idea? Also, I couldn't manage to make a `Sequence` of `int8` but I'm sure I've missed something simple.
Thanks in advance | {
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https://api.github.com/repos/huggingface/datasets/issues/1137 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1137/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1137/comments | https://api.github.com/repos/huggingface/datasets/issues/1137/events | https://github.com/huggingface/datasets/pull/1137 | 757,358,145 | MDExOlB1bGxSZXF1ZXN0NTMyNzQ4NDAx | 1,137 | add wmt mlqe 2020 shared task | {
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"re-created in #1218 because this was too messy"
] | 1,607,111,134,000 | 1,607,284,784,000 | 1,607,284,426,000 | MEMBER | null | First commit for Shared task 1 (wmt_mlqw_task1) of WMT20 MLQE (quality estimation of machine translation)
Note that I copied the tags in the README for only one (of the 7 configurations): `en-de`.
There is one configuration for each pair of languages. | {
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https://api.github.com/repos/huggingface/datasets/issues/1130 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1130/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1130/comments | https://api.github.com/repos/huggingface/datasets/issues/1130/events | https://github.com/huggingface/datasets/pull/1130 | 757,265,075 | MDExOlB1bGxSZXF1ZXN0NTMyNjY5ODY0 | 1,130 | adding discovery | {
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"merging since the CI is fixed on master"
] | 1,607,102,214,000 | 1,607,950,994,000 | 1,607,950,994,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1129 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1129/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1129/comments | https://api.github.com/repos/huggingface/datasets/issues/1129/events | https://github.com/huggingface/datasets/pull/1129 | 757,255,492 | MDExOlB1bGxSZXF1ZXN0NTMyNjYxNzM2 | 1,129 | Adding initial version of cord-19 dataset | {
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"Hi @ggdupont !\r\nHave you had a chance to take a look at my suggestions ?\r\nFeel free to ping me if you have questions or when you're ready for a review",
"> Hi @ggdupont !\r\n> Have you had a chance to take a look at my suggestions ?\r\n> Feel free to ping me if you have questions or when you're ready for a review\r\n\r\nYes I did, just busy period (and no time on weekend right now ;-) )",
"With some delay, reduced the dummy data and had t rebase",
"Thanks !\r\n\r\nIt looks like the rebase messed up the github diff for this PR (2.000+ files changed)\r\nCould you create another branch and another PR please ?",
"Cleaned PR: https://github.com/huggingface/datasets/pull/1850"
] | 1,607,101,397,000 | 1,612,866,155,000 | 1,612,865,886,000 | CONTRIBUTOR | null | Initial version only reading the metadata in CSV.
### Checklist:
- [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.
### TODO:
- [x] add more metadata
- [x] add full text
- [x] add pre-computed document embedding | {
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https://api.github.com/repos/huggingface/datasets/issues/1127 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1127/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1127/comments | https://api.github.com/repos/huggingface/datasets/issues/1127/events | https://github.com/huggingface/datasets/pull/1127 | 757,229,684 | MDExOlB1bGxSZXF1ZXN0NTMyNjQwMjMx | 1,127 | Add wikiqaar dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1126 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1126/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1126/comments | https://api.github.com/repos/huggingface/datasets/issues/1126/events | https://github.com/huggingface/datasets/pull/1126 | 757,197,735 | MDExOlB1bGxSZXF1ZXN0NTMyNjEzNzcw | 1,126 | Adding babi dataset | {
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"This is ok now @lhoestq\r\n\r\nI've included the tweak to `dummy_data` to only use the data transmitted to `_generate_examples` by default (it only do that if it can find at least one path to an existing file in the `gen_kwargs` and this can be unactivated with a flag).\r\n\r\nShould I extract it in another PR or is it ok like this?",
"Nice !\r\nCould you add the dummy data generation trick in another PR ?\r\nI think we can also extend it to make it work not only with data files paths but also with data directories (sometimes it's one of the parent directory that is passed to gen_kwargs, not the actual path to the file).\r\nThis will help a lot to make the dummy data lighter !",
"This PR can be closed due to #2053 @lhoestq\r\n\r\n"
] | 1,607,096,554,000 | 1,617,097,444,000 | 1,617,097,444,000 | MEMBER | null | Adding the English version of bAbI.
Samples are taken from ParlAI for consistency with the main users at the moment.
Supersede #945 (problem with the rebase) and adresses the issues mentioned in the review (dummy data are smaller now and code comments are fixed). | {
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https://api.github.com/repos/huggingface/datasets/issues/1125 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1125/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1125/comments | https://api.github.com/repos/huggingface/datasets/issues/1125/events | https://github.com/huggingface/datasets/pull/1125 | 757,194,531 | MDExOlB1bGxSZXF1ZXN0NTMyNjExMDU5 | 1,125 | Add Urdu fake news dataset. | {
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"@lhoestq looks like a lot of files were updated... shall I create a new PR?",
"Hi @chaitnayabasava ! you can try rebasing and see if that fixes the number of files changed, otherwise please do open a new PR with only the relevant files and close this one :) ",
"Created a new PR #1230.\r\nclosing this one :)"
] | 1,607,096,297,000 | 1,607,311,265,000 | 1,607,311,265,000 | CONTRIBUTOR | null | Added Urdu fake news dataset. More information about the dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>. | {
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https://api.github.com/repos/huggingface/datasets/issues/1124 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1124/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1124/comments | https://api.github.com/repos/huggingface/datasets/issues/1124/events | https://github.com/huggingface/datasets/pull/1124 | 757,186,983 | MDExOlB1bGxSZXF1ZXN0NTMyNjA0NzY3 | 1,124 | Add Xitsonga Ner | {
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"looks like this PR includes changes about many files other than the ones related to xitsonga NER\r\n\r\ncould you create another branch and another PR please ?"
] | 1,607,095,664,000 | 1,607,279,495,000 | 1,607,279,495,000 | CONTRIBUTOR | null | Clean Xitsonga Ner PR | {
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https://api.github.com/repos/huggingface/datasets/issues/1123 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1123/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1123/comments | https://api.github.com/repos/huggingface/datasets/issues/1123/events | https://github.com/huggingface/datasets/pull/1123 | 757,181,014 | MDExOlB1bGxSZXF1ZXN0NTMyNTk5ODQ3 | 1,123 | adding cdt dataset | {
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"the `ms_terms` formatting CI fails is fixed on master",
"merging since the CI is fixed on master"
] | 1,607,095,176,000 | 1,607,101,556,000 | 1,607,101,556,000 | CONTRIBUTOR | null | {
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https://api.github.com/repos/huggingface/datasets/issues/1122 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1122/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1122/comments | https://api.github.com/repos/huggingface/datasets/issues/1122/events | https://github.com/huggingface/datasets/pull/1122 | 757,176,172 | MDExOlB1bGxSZXF1ZXN0NTMyNTk1ODE5 | 1,122 | Add Urdu fake news. | {
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https://api.github.com/repos/huggingface/datasets/issues/1120 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1120/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1120/comments | https://api.github.com/repos/huggingface/datasets/issues/1120/events | https://github.com/huggingface/datasets/pull/1120 | 757,166,342 | MDExOlB1bGxSZXF1ZXN0NTMyNTg3Njk1 | 1,120 | Add conda environment activation | {
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https://api.github.com/repos/huggingface/datasets/issues/1119 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1119/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1119/comments | https://api.github.com/repos/huggingface/datasets/issues/1119/events | https://github.com/huggingface/datasets/pull/1119 | 757,156,781 | MDExOlB1bGxSZXF1ZXN0NTMyNTc5ODA5 | 1,119 | Add Google Great Code Dataset | {
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https://api.github.com/repos/huggingface/datasets/issues/1118 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1118/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1118/comments | https://api.github.com/repos/huggingface/datasets/issues/1118/events | https://github.com/huggingface/datasets/pull/1118 | 757,142,350 | MDExOlB1bGxSZXF1ZXN0NTMyNTY3ODMw | 1,118 | Add Tashkeela dataset | {
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"Sorry @lhoestq for the trouble, sometime I forget to change the names :/",
"> Sorry @lhoestq for the trouble, sometime I forget to change the names :/\r\n\r\nhaha it's ok ;)"
] | 1,607,091,978,000 | 1,607,096,821,000 | 1,607,096,811,000 | CONTRIBUTOR | null | Arabic Vocalized Words Dataset. | {
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https://api.github.com/repos/huggingface/datasets/issues/1117 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1117/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1117/comments | https://api.github.com/repos/huggingface/datasets/issues/1117/events | https://github.com/huggingface/datasets/pull/1117 | 757,133,789 | MDExOlB1bGxSZXF1ZXN0NTMyNTYwNzM4 | 1,117 | Fix incorrect MRQA train+SQuAD URL | {
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"Thanks ! could you regenerate the dataset_infos.json file ?\r\n\r\n```\r\ndatasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications\r\n```\r\n\r\nalso cc @VictorSanh ",
"Oooops, good catch @jimmycode ",
"> Thanks ! could you regenerate the dataset_infos.json file ?\r\n> \r\n> ```\r\n> datasets-cli test ./datasets/mrqa --save_infos --all_configs --ignore_verifications\r\n> ```\r\n> \r\n> also cc @VictorSanh\r\n\r\nUpdated the `dataset_infos.json` file."
] | 1,607,091,266,000 | 1,607,274,851,000 | 1,607,274,850,000 | CONTRIBUTOR | null | Fix issue #1115
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https://api.github.com/repos/huggingface/datasets/issues/1116 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1116/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1116/comments | https://api.github.com/repos/huggingface/datasets/issues/1116/events | https://github.com/huggingface/datasets/pull/1116 | 757,133,502 | MDExOlB1bGxSZXF1ZXN0NTMyNTYwNDk4 | 1,116 | add dbpedia_14 dataset | {
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"Thanks for the review. \r\nCheers!",
"Hi @hfawaz, this week we are doing the 🤗 `datasets` sprint (see some details [here](https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)).\r\n\r\nNothing more to do on your side but it means that if you register on the thread I linked above, you can have some goodies for the present dataset that you have already added (and a special goodie if you want to spend more time and add 2 other datasets as well).\r\n\r\nIf you want to join, just tell me (or post on the thread on the HuggingFace forum: https://discuss.huggingface.co/t/open-to-the-community-one-week-team-effort-to-reach-v2-0-of-hf-datasets-library/2176)",
"Hello @thomwolf \r\nThanks for the feedback and for this invitation, indeed I would be glad to join you guys (you can add me). \r\nI will see if I have the time to implement a couple of datasets. \r\nCheers! ",
"@hfawaz invited you to the slack with your uha email.\r\n\r\nCheck your spam folder if you can't find the invitation :)",
"Oh thanks, but can you invite me on my gmail: [email protected] \r\nUHA is my old organization, I haven't had the time to update my online profiles yet.\r\nThank you "
] | 1,607,091,239,000 | 1,607,335,614,000 | 1,607,182,583,000 | CONTRIBUTOR | null | This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353. | {
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"good catch !"
] | 1,607,090,724,000 | 1,607,274,862,000 | 1,607,274,862,000 | CONTRIBUTOR | null | https://github.com/huggingface/datasets/blob/4ef4c8f8b7a60e35c6fa21115fca9faae91c9f74/datasets/mrqa/mrqa.py#L53
The URL for `train+SQuAD` subset of MRQA points to the dev set instead of train set. It should be `https://s3.us-east-2.amazonaws.com/mrqa/release/v2/train/SQuAD.jsonl.gz`. | {
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https://api.github.com/repos/huggingface/datasets/issues/1114 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1114/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1114/comments | https://api.github.com/repos/huggingface/datasets/issues/1114/events | https://github.com/huggingface/datasets/pull/1114 | 757,123,638 | MDExOlB1bGxSZXF1ZXN0NTMyNTUyMjE1 | 1,114 | Add sesotho ner corpus | {
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https://api.github.com/repos/huggingface/datasets/issues/1113 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1113/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1113/comments | https://api.github.com/repos/huggingface/datasets/issues/1113/events | https://github.com/huggingface/datasets/pull/1113 | 757,115,557 | MDExOlB1bGxSZXF1ZXN0NTMyNTQ1Mzg2 | 1,113 | add qed | {
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https://github.com/google-research-datasets/QED
https://arxiv.org/abs/2009.06354 | {
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https://api.github.com/repos/huggingface/datasets/issues/1112 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1112/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1112/comments | https://api.github.com/repos/huggingface/datasets/issues/1112/events | https://github.com/huggingface/datasets/pull/1112 | 757,108,151 | MDExOlB1bGxSZXF1ZXN0NTMyNTM5MjE2 | 1,112 | Initial version of cord-19 dataset from AllenAI with only the abstract | {
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"too ugly, I'll make a clean one"
] | 1,607,088,999,000 | 1,607,098,600,000 | 1,607,098,584,000 | CONTRIBUTOR | null | Initial version only reading the metadata in CSV.
### Checklist:
- [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
- [ ] Both tests for the real data and the dummy data pass.
### TODO:
- [ ] add more metadata
- [ ] add full text
- [ ] add pre-computed document embedding | {
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"Thanks for reporting !\r\n\r\nIndeed this is a keyword in the library that is used to encode/decode features to a python dictionary that we can save/load to json.\r\nWe can probably change `_type` to something that is less likely to collide with user feature names.\r\nIn this case we would want something backward compatible though.\r\n\r\nFeel free to try a fix and open a PR, and to ping me if I can help :) "
] | 1,607,086,593,000 | 1,610,535,208,000 | null | CONTRIBUTOR | null | A column named `_type` leads to a `TypeError: unhashable type: 'dict'` for certain operations:
```python
from datasets import Dataset, concatenate_datasets
ds = Dataset.from_dict({"_type": ["whatever"]}).map()
concatenate_datasets([ds])
# or simply
Dataset(ds._data)
```
Context: We are using datasets to persist data coming from elasticsearch to feed to our pipeline, and elasticsearch has a `_type` field, hence the strange name of the column.
Not sure if you wish to support this specific column name, but if you do i would be happy to try a fix and provide a PR. I already had a look into it and i think the culprit is the `datasets.features.generate_from_dict` function. It uses the hard coded `_type` string to figure out if it reached the end of the nested feature object from a serialized dict.
Best wishes and keep up the awesome work! | {
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https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz
https://arxiv.org/abs/1604.04562 | {
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"thanks ! can you also regenerate the dataset_infos.json file please ?"
] | 1,607,081,464,000 | 1,607,182,689,000 | 1,607,182,689,000 | CONTRIBUTOR | null | Add The Arabic Sentiment Twitter Dataset for Levantine dialect (ArSenTD-LEV)
Paper: [ArSentD-LEV: A Multi-Topic Corpus for Target-based Sentiment Analysis in Arabic Levantine Tweets](https://arxiv.org/abs/1906.01830)
Homepage: http://oma-project.com/ | {
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"looks like this PR includes changes in many files than the ones for xquad_r, could you create a new branch and a new PR ?",
"Sure, I will close this then.\r\n"
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"Hey, I think this is great idea. Any plan to integrate kaggle private datasets loading to `datasets`?"
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"@lhoestq done! ;)"
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"hope this works.."
] | 1,607,063,154,000 | 1,607,276,583,000 | 1,607,276,582,000 | CONTRIBUTOR | null | This pull request will add Google wellformed_query dataset. Link of dataset is https://github.com/google-research-datasets/query-wellformedness | {
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https://api.github.com/repos/huggingface/datasets/issues/1088 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1088/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1088/comments | https://api.github.com/repos/huggingface/datasets/issues/1088/events | https://github.com/huggingface/datasets/pull/1088 | 756,822,017 | MDExOlB1bGxSZXF1ZXN0NTMyMzAyNjIz | 1,088 | add xquad_r 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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https://api.github.com/repos/huggingface/datasets/issues/1086 | https://api.github.com/repos/huggingface/datasets | https://api.github.com/repos/huggingface/datasets/issues/1086/labels{/name} | https://api.github.com/repos/huggingface/datasets/issues/1086/comments | https://api.github.com/repos/huggingface/datasets/issues/1086/events | https://github.com/huggingface/datasets/pull/1086 | 756,720,643 | MDExOlB1bGxSZXF1ZXN0NTMyMjIzNDEy | 1,086 | adding cdt dataset | {
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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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} | [] | closed | false | null | [] | null | [] | 1,607,040,605,000 | 1,607,078,486,000 | 1,607,078,486,000 | CONTRIBUTOR | null | - **Name**: *cdsc (domains: cdsc-e & cdsc-r)*
- **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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} | [] | closed | false | null | [] | null | [] | 1,607,035,646,000 | 1,607,074,926,000 | 1,607,074,926,000 | CONTRIBUTOR | null | - **Name:** *nkjp-ner*
- **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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} | [] | closed | false | null | [] | null | [] | 1,607,032,141,000 | 1,607,075,753,000 | 1,607,075,752,000 | MEMBER | null | This PR adds the [Glucose](https://github.com/ElementalCognition/glucose) dataset. | {
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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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"This one will make @thomwolf reminisce ;)",
"Merging."
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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"
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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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}
] | closed | false | null | [] | null | [
"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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} | [] | closed | false | null | [] | null | [] | 1,607,013,537,000 | 1,607,019,944,000 | 1,607,019,944,000 | CONTRIBUTOR | null | Arabic Book Reviews 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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