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Opus sardware
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2020-12-05 17:05:45+00:00
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Added Opus sardware dataset for machine translation English to Sardinian. for more info : http://opus.nlpl.eu/sardware.php
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Adding dataset for proto_qa in huggingface datasets library
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2020-12-05 18:53:10+00:00
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Added dataset for ProtoQA: A Question Answering Dataset for Prototypical Common-Sense Reasoning Followed all steps for adding a new dataset.
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hindi discourse analysis dataset commit
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2020-12-14 19:44:48+00:00
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adding psc dataset
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2020-12-09 11:38:41+00:00
2020-12-09 11:38:41+00:00
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2020-12-05 01:25:29+00:00
2020-12-05 16:51:39+00:00
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2020-12-05 01:17:02+00:00
2020-12-05 16:36:04+00:00
2020-12-05 16:36:04+00:00
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Real data tests are failing as this dataset needs to be manually downloaded
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2020-12-05 01:01:09+00:00
2020-12-05 16:35:53+00:00
2020-12-05 16:35:53+00:00
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2020-12-04 23:44:51+00:00
2022-01-13 03:09:20+00:00
2020-12-05 16:35:01+00:00
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Add JFLEG
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2020-12-04 22:36:38+00:00
2020-12-06 18:16:04+00:00
2020-12-06 18:16:04+00:00
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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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Add the Winograd Schema Challenge
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2020-12-04 22:26:59+00:00
2020-12-09 15:11:31+00:00
2020-12-09 09:32:34+00:00
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Adds the Winograd Schema Challenge, including configs for the more canonical wsc273 as well as wsc285 with 12 new examples. - 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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1,142
Fix PerSenT
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2020-12-04 21:21:02+00:00
2020-12-14 13:39:34+00:00
2020-12-14 13:39:34+00:00
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New PR for dataset PerSenT
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1,141
Add GitHub version of ETH Py150 Corpus
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2020-12-04 21:16:08+00:00
2020-12-09 18:32:44+00:00
2020-12-07 10:00:24+00:00
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Add the redistributable version of **ETH Py150 Corpus**
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Add Urdu Sentiment Corpus (USC).
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2020-12-04 20:55:27+00:00
2020-12-07 03:27:23+00:00
2020-12-07 03:27:23+00:00
CONTRIBUTOR
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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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Add ReFreSD dataset
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2020-12-04 20:45:11+00:00
2020-12-16 16:01:18+00:00
2020-12-16 16:01:18+00:00
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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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updated after the class name update
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2020-12-04 20:19:43+00:00
2020-12-05 15:43:32+00:00
2020-12-05 15:43:32+00:00
CONTRIBUTOR
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@lhoestq <---
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add wmt mlqe 2020 shared task
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2020-12-04 19:45:34+00:00
2020-12-06 19:59:44+00:00
2020-12-06 19:53:46+00:00
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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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minor change in description in paws-x.py and updated dataset_infos
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2020-12-06 18:02:57+00:00
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2020-12-09 17:17:13+00:00
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Updating README and tags for dataset card in a while
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2020-12-05 16:50:47+00:00
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Add Urdu Sentiment Corpus (USC).
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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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Adding XQUAD-R Dataset
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757,265,075
MDExOlB1bGxSZXF1ZXN0NTMyNjY5ODY0
1,130
adding discovery
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2020-12-04 17:16:54+00:00
2020-12-14 13:03:14+00:00
2020-12-14 13:03:14+00:00
CONTRIBUTOR
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1,129
Adding initial version of cord-19 dataset
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2020-12-04 17:03:17+00:00
2021-02-09 10:22:35+00:00
2021-02-09 10:18:06+00:00
CONTRIBUTOR
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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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1,128
Add xquad-r dataset
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2020-12-04 16:48:53+00:00
2020-12-04 18:14:30+00:00
2020-12-04 18:14:26+00:00
CONTRIBUTOR
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Add wikiqaar dataset
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2020-12-04 16:26:18+00:00
2020-12-07 16:39:41+00:00
2020-12-07 16:39:41+00:00
CONTRIBUTOR
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Arabic Wiki Question Answering Corpus.
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Adding babi dataset
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2020-12-04 15:42:34+00:00
2021-03-30 09:44:04+00:00
2021-03-30 09:44:04+00:00
MEMBER
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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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Add Urdu fake news dataset.
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2020-12-04 15:38:17+00:00
2020-12-07 03:21:05+00:00
2020-12-07 03:21:05+00:00
CONTRIBUTOR
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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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Clean Xitsonga Ner PR
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Added activation of Conda environment before installing.
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2020-12-06 17:33:14+00:00
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MDExOlB1bGxSZXF1ZXN0NTMyNTY3ODMw
1,118
Add Tashkeela dataset
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2020-12-04 14:26:18+00:00
2020-12-04 15:47:01+00:00
2020-12-04 15:46:51+00:00
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Arabic Vocalized Words Dataset.
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757,133,789
MDExOlB1bGxSZXF1ZXN0NTMyNTYwNzM4
1,117
Fix incorrect MRQA train+SQuAD URL
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2020-12-04 14:14:26+00:00
2020-12-06 17:14:11+00:00
2020-12-06 17:14:10+00:00
CONTRIBUTOR
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Fix issue #1115
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1,116
add dbpedia_14 dataset
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2020-12-04 14:13:59+00:00
2020-12-07 10:06:54+00:00
2020-12-05 15:36:23+00:00
CONTRIBUTOR
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This dataset corresponds to the DBpedia dataset requested in https://github.com/huggingface/datasets/issues/353.
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757,127,527
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1,115
Incorrect URL for MRQA SQuAD train subset
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2020-12-04 14:05:24+00:00
2020-12-06 17:14:22+00:00
2020-12-06 17:14:22+00:00
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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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1,114
Add sesotho ner corpus
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2020-12-04 13:59:41+00:00
2020-12-04 15:02:07+00:00
2020-12-04 15:02:07+00:00
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Clean Sesotho PR
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add qed
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2020-12-04 13:47:57+00:00
2020-12-05 15:46:21+00:00
2020-12-05 15:41:57+00:00
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adding QED: Dataset for Explanations in Question Answering https://github.com/google-research-datasets/QED https://arxiv.org/abs/2009.06354
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Initial version of cord-19 dataset from AllenAI with only the abstract
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2020-12-04 13:36:39+00:00
2020-12-04 16:16:40+00:00
2020-12-04 16:16:24+00:00
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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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Add Siswati Ner corpus
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2020-12-04 12:57:31+00:00
2020-12-04 14:43:01+00:00
2020-12-04 14:43:00+00:00
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Clean Siswati PR
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Using a feature named "_type" fails with certain operations
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2020-12-04 12:56:33+00:00
2022-01-14 18:07:00+00:00
2022-01-14 18:07:00+00:00
CONTRIBUTOR
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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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add woz_dialogue
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2020-12-04 12:13:07+00:00
2020-12-05 15:41:23+00:00
2020-12-05 15:40:18+00:00
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Adding Wizard-of-Oz task oriented dialogue dataset https://github.com/nmrksic/neural-belief-tracker/tree/master/data/woz https://arxiv.org/abs/1604.04562
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Add Sepedi NER corpus
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2020-12-04 12:11:24+00:00
2020-12-04 14:39:00+00:00
2020-12-04 14:39:00+00:00
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Finally a clean PR for Sepedi
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Add arsentd_lev dataset
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2020-12-04 11:31:04+00:00
2020-12-05 15:38:09+00:00
2020-12-05 15:38:09+00:00
CONTRIBUTOR
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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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757,027,158
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1,106
Add Urdu fake news
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2020-12-04 11:24:14+00:00
2020-12-04 14:21:12+00:00
2020-12-04 14:21:12+00:00
CONTRIBUTOR
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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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757,024,162
MDExOlB1bGxSZXF1ZXN0NTMyNDY4NDIw
1,105
add xquad_r dataset
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2020-12-04 11:19:35+00:00
2020-12-04 16:37:00+00:00
2020-12-04 16:37:00+00:00
CONTRIBUTOR
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add TLC
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2020-12-04 11:14:58+00:00
2020-12-04 14:29:23+00:00
2020-12-04 14:29:23+00:00
CONTRIBUTOR
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Added TLC dataset
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Add support to download kaggle datasets
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closed
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2020-12-04 11:08:37+00:00
2023-07-20 15:22:24+00:00
2023-07-20 15:22:23+00:00
CONTRIBUTOR
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We can use API key
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Add retries to download manager
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2020-12-04 11:08:11+00:00
2020-12-22 15:34:06+00:00
2020-12-22 15:34:06+00:00
CONTRIBUTOR
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Add Wikicorpus dataset
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2020-12-04 10:57:26+00:00
2020-12-09 18:13:10+00:00
2020-12-09 18:13:09+00:00
MEMBER
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Add dataset.
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Urdu fake news
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2020-12-04 10:41:20+00:00
2020-12-04 11:19:00+00:00
2020-12-04 11:19:00+00:00
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Added Bend the Truth urdu fake news dataset. More inforation <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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Add tamilmixsentiment data
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2020-12-04 10:34:07+00:00
2020-12-06 06:32:22+00:00
2020-12-05 16:48:33+00:00
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Add ToTTo Dataset
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2020-12-04 10:07:25+00:00
2020-12-04 13:38:20+00:00
2020-12-04 13:38:19+00:00
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Adds a brand new table to text dataset: https://github.com/google-research-datasets/ToTTo
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Add MSRA NER labels
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2020-12-04 09:38:16+00:00
2020-12-04 13:31:59+00:00
2020-12-04 13:31:58+00:00
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Fixes #940
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FIX matinf link in ADD_NEW_DATASET.md
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2020-12-04 09:33:25+00:00
2020-12-04 14:25:35+00:00
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1,095
Add TupleInf Open IE Dataset
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2020-12-04 09:08:07+00:00
2020-12-04 15:40:54+00:00
2020-12-04 15:40:54+00:00
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For more information: https://allenai.org/data/tuple-ie
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1,094
add urdu fake news dataset
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2020-12-04 08:57:38+00:00
2020-12-04 09:20:56+00:00
2020-12-04 09:20:56+00:00
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Added Urdu fake news dataset. The dataset can be found <a href="https://github.com/MaazAmjad/Datasets-for-Urdu-news">here</a>.
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756,916,565
MDExOlB1bGxSZXF1ZXN0NTMyMzgxNjkw
1,093
Add NCBI Disease Corpus dataset
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2020-12-04 08:42:32+00:00
2020-12-04 11:15:12+00:00
2020-12-04 11:15:12+00:00
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756,913,134
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1,092
Add Coached Conversation Preference Dataset
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2020-12-04 08:36:49+00:00
2020-12-20 13:34:00+00:00
2020-12-04 13:49:50+00:00
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Adding [Coached Conversation Preference Dataset](https://research.google/tools/datasets/coached-conversational-preference-elicitation/)
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Add Google wellformed query dataset
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2020-12-04 06:25:54+00:00
2020-12-06 17:43:03+00:00
2020-12-06 17:43:02+00:00
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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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add thaisum
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2020-12-04 05:54:48+00:00
2020-12-04 11:16:06+00:00
2020-12-04 11:16:06+00:00
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ThaiSum, a large-scale corpus for Thai text summarization obtained from several online news websites namely Thairath, ThaiPBS, Prachathai, and The Standard. This dataset consists of over 350,000 article and summary pairs written by journalists. We evaluate the performance of various existing summarization models on ThaiSum dataset and analyse the characteristic of the dataset to present its difficulties.
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1,089
add sharc_modified
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2020-12-04 05:49:49+00:00
2020-12-04 10:41:30+00:00
2020-12-04 10:31:44+00:00
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Adding modified ShARC dataset https://github.com/nikhilweee/neural-conv-qa
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1,088
add xquad_r dataset
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2020-12-04 05:45:55+00:00
2020-12-04 10:58:13+00:00
2020-12-04 10:47:01+00:00
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Add Big Patent dataset
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2020-12-04 04:37:30+00:00
2020-12-06 17:21:00+00:00
2020-12-06 17:20:59+00:00
CONTRIBUTOR
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* 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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adding cdt dataset
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2020-12-04 01:28:11+00:00
2020-12-04 15:04:02+00:00
2020-12-04 15:04:02+00:00
CONTRIBUTOR
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- **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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add mutual friends conversational dataset
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2020-12-04 00:48:21+00:00
2020-12-16 15:58:31+00:00
2020-12-16 15:58:30+00:00
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Mutual friends dataset WIP TODO: - scenario_kbs (bug with pyarrow conversion) - download from codalab checksums bug
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adding cdsc dataset
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2020-12-04 00:10:05+00:00
2020-12-04 10:41:26+00:00
2020-12-04 10:41:26+00:00
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- **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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Add the multilingual Exams dataset
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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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Myanmar news dataset
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2020-12-04 10:13:38+00:00
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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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Add Knowledge-Enhanced Language Model Pre-training (KELM)
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Adds the KELM dataset. - Webpage/repo: https://github.com/google-research-datasets/KELM-corpus - Paper: https://arxiv.org/pdf/2010.12688.pdf
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Add WikiANN NER dataset
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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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2020-12-04 09:42:06+00:00
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- **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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add AJGT dataset
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Arabic Jordanian General Tweets.
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Added glucose dataset
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2020-12-03 21:49:01+00:00
2020-12-04 09:55:53+00:00
2020-12-04 09:55:52+00:00
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This PR adds the [Glucose](https://github.com/ElementalCognition/glucose) dataset.
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quac quac / coin coin
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2020-12-04 16:36:39+00:00
2020-12-04 09:15:20+00:00
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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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adding cleaned verion of E2E NLG
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Found at: https://github.com/tuetschek/e2e-cleaning
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Swedish MT STS-B
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2020-12-03 19:06:25+00:00
2020-12-04 20:22:27+00:00
2020-12-03 20:44:28+00:00
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Added a Swedish machine translated version of the well known STS-B Corpus
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Add DialogRE dataset
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2020-12-03 18:56:40+00:00
2020-12-20 13:34:48+00:00
2020-12-04 13:41:51+00:00
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Adding the [DialogRE](https://github.com/nlpdata/dialogre) dataset Version 2. - All tests passed successfully.
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actually uses the previously declared VERSION on the configs in the template
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add xlrd to test package requirements
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2020-12-03 18:47:16+00:00
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Adds `xlrd` package to the test requirements to handle scripts that use `pandas` to load excel files
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add conv_ai
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2020-12-03 18:25:20+00:00
2020-12-04 07:58:35+00:00
2020-12-04 06:44:34+00:00
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Adding ConvAI dataset https://github.com/DeepPavlov/convai/tree/master/2017
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Test
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2020-12-03 18:01:45+00:00
2020-12-04 04:24:18+00:00
2020-12-04 04:24:11+00:00
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Add Pubmed (citation + abstract) dataset (2020).
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2020-12-03 17:54:10+00:00
2020-12-23 09:52:07+00:00
2020-12-23 09:52:07+00:00
CONTRIBUTOR
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add xquad-r dataset
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2020-12-03 17:53:21+00:00
2020-12-03 17:53:15+00:00
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Add ChrEn
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2020-12-03 17:17:48+00:00
2020-12-03 21:49:39+00:00
2020-12-03 21:49:39+00:00
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Adding the Cherokee English machine translation dataset of https://github.com/ZhangShiyue/ChrEn
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add xquad-r dataset
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2020-12-03 17:06:23+00:00
2020-12-03 17:42:21+00:00
2020-12-03 17:42:03+00:00
CONTRIBUTOR
null
null
0
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1,064
Not support links with 302 redirect
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2
2020-12-03 17:04:43+00:00
2021-01-14 02:51:25+00:00
2021-01-14 02:51:25+00:00
CONTRIBUTOR
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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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756,376,374
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1,063
Add the Ud treebank
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2020-12-03 16:56:41+00:00
2020-12-04 16:11:54+00:00
2020-12-04 15:51:46+00:00
CONTRIBUTOR
null
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This PR adds the 183 datasets in 104 languages of the UD Treebank.
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Add KorNLU dataset
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2020-12-03 16:52:39+00:00
2020-12-04 11:05:19+00:00
2020-12-04 11:05:19+00:00
CONTRIBUTOR
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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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add labr dataset
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2020-12-03 16:38:57+00:00
2020-12-03 18:25:44+00:00
2020-12-03 18:25:44+00:00
CONTRIBUTOR
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Arabic Book Reviews dataset.
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Fix squad V2 metric script
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2020-12-03 16:23:32+00:00
2020-12-22 15:02:20+00:00
2020-12-22 15:02:19+00:00
CONTRIBUTOR
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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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1,059
Add TLC
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2020-12-03 16:23:06+00:00
2020-12-04 11:15:33+00:00
2020-12-04 11:15:33+00:00
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Added TLC dataset
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1,058
added paws-x dataset
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2020-12-03 16:06:01+00:00
2020-12-04 13:46:05+00:00
2020-12-04 13:46:05+00:00
CONTRIBUTOR
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Added paws-x dataset. Updating README and tags in the dataset card in a while
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1,057
Adding TamilMixSentiment
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2020-12-03 16:04:25+00:00
2020-12-04 10:09:34+00:00
2020-12-04 10:09:12+00:00
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756,309,828
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1,056
Add deal_or_no_dialog
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2020-12-03 15:38:07+00:00
2020-12-03 18:13:45+00:00
2020-12-03 18:13:45+00:00
CONTRIBUTOR
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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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Add hebrew-sentiment
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2020-12-03 15:24:31+00:00
2022-02-21 15:26:05+00:00
2020-12-04 11:24:16+00:00
CONTRIBUTOR
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hebrew-sentiment dataset is ready! (including tests, tags etc)
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