id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
Kabatubare/medical | 2023-10-28T03:57:40.000Z | [
"language:en",
"license:other",
"healthcare",
"qna",
"nlp",
"english",
"region:us"
] | Kabatubare | null | null | 1 | 95 | 2023-10-23T18:59:09 | ---
tags:
- healthcare
- qna
- nlp
- english
license: other
language:
- en
pretty_name: Medical QnA Datasets
---
# Dataset Card for "Medical" Healthcare QnA Datasets
## Dataset Details
### Dataset Description
The "Medical" dataset is a specialized subset curated from the larger MedDialog collection, featuring healt... | 1,089 | [
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fake_news_filipino | 2023-01-25T14:30:21.000Z | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
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"language:tl",
"license:unknown",
"region:us"
] | null | Low-Resource Fake News Detection Corpora in Filipino. The first of its kind. Contains 3,206 expertly-labeled news samples, half of which are real and half of which are fake. | @inproceedings{cruz2020localization,
title={Localization of Fake News Detection via Multitask Transfer Learning},
author={Cruz, Jan Christian Blaise and Tan, Julianne Agatha and Cheng, Charibeth},
booktitle={Proceedings of The 12th Language Resources and Evaluation Conference},
pages={2596--... | 0 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- tl
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
paperswithcode_id: fake-news-filipino-dataset
pretty_na... | 4,963 | [
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hover | 2023-01-25T14:32:26.000Z | [
"task_categories:text-retrieval",
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"multilinguality:monolingual",
"size_categories:10K<n<100K",
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"language:en",
"license:cc-by-sa-... | null | HoVer is an open-domain, many-hop fact extraction and claim verification dataset built upon the Wikipedia corpus. The original 2-hop claims are adapted from question-answer pairs from HotpotQA. It is collected by a team of NLP researchers at UNC Chapel Hill and Verisk Analytics. | @inproceedings{jiang2020hover,
title={{HoVer}: A Dataset for Many-Hop Fact Extraction And Claim Verification},
author={Yichen Jiang and Shikha Bordia and Zheng Zhong and Charles Dognin and Maneesh Singh and Mohit Bansal.},
booktitle={Findings of the Conference on Empirical Methods in Natural Language Processing (... | 0 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-retrieval
task_ids:
- fact-checking-retrieval
paperswithcode_id: hover
pretty... | 4,135 | [
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interpress_news_category_tr | 2023-01-25T14:33:03.000Z | [
"task_categories:text-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:tr",
"license:unknown",
"news-category-classification",
"region:us"
] | null | It is a Turkish news data set consisting of 273601 news in 17 categories, compiled from print media and news websites between 2010 and 2017 by the Interpress (https://www.interpress.com/) media monitoring company. | null | 6 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- tr
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
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task_ids: []
pretty_name: Interpress Turkish News Category Dataset (270K)
tags:
- news-category-cl... | 7,699 | [
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sogou_news | 2023-04-05T13:40:25.000Z | [
"arxiv:1509.01626",
"region:us"
] | null | The Sogou News dataset is a mixture of 2,909,551 news articles from the SogouCA and SogouCS news corpora, in 5 categories.
The number of training samples selected for each class is 90,000 and testing 12,000. Note that the Chinese characters have been converted to Pinyin.
classification labels of the news are determined... | @misc{zhang2015characterlevel,
title={Character-level Convolutional Networks for Text Classification},
author={Xiang Zhang and Junbo Zhao and Yann LeCun},
year={2015},
eprint={1509.01626},
archivePrefix={arXiv},
primaryClass={cs.LG}
} | 0 | 94 | 2022-03-02T23:29:22 | ---
pretty_name: Sogou News
dataset_info:
features:
- name: title
dtype: string
- name: content
dtype: string
- name: label
dtype:
class_label:
names:
'0': sports
'1': finance
'2': entertainment
'3': automobile
'4': technology
splits:... | 6,403 | [
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the_pile_stack_exchange | 2023-02-20T15:10:44.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
... | null | This dataset is part of EleutherAI/The Pile dataset and is a dataset for Language Models from processing stackexchange data dump, which is an anonymized dump of all user-contributed content on the Stack Exchange network. | @article{pile,
title={The {P}ile: An 800GB Dataset of Diverse Text for Language Modeling},
author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and Presser, Shawn and Leahy, Connor},
... | 8 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Stack Exchange
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-mo... | 6,445 | [
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turkish_movie_sentiment | 2022-11-03T16:07:48.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:tr",
"license:unknown",
"region:us... | null | This data set is a dataset from kaggle consisting of Turkish movie reviews and scored between 0-5. | null | 3 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- tr
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
- sentiment-scoring
paperswithcode_id: null
pretty_name: 'Tu... | 4,046 | [
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udhr | 2022-11-03T16:16:11.000Z | [
"task_categories:translation",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"language:aa",
"language:ab",
"language:ace",
"language:acu",
"language:ada",
"language:ady",
"language:af",
"... | null | The Universal Declaration of Human Rights (UDHR) is a milestone document in the history of human rights. Drafted by
representatives with different legal and cultural backgrounds from all regions of the world, it set out, for the
first time, fundamental human rights to be universally protected. The Declaration was adopt... | null | 1 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
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- ab
- ace
- acu
- ada
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- agr
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- ajg
- als
- alt
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- ame
- ami
- amr
- ar
- arl
- arn
- ast
- auc
- ay
- az
- ban
- bax
- bba
- bci
- be
- bem
- bfa
- bg
- bho
- bi
- bik
- bin
- blt
- bm
- bn
- bo
- boa
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- b... | 8,673 | [
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0.0... |
AHussain0418/day4data | 2022-01-07T16:26:39.000Z | [
"region:us"
] | AHussain0418 | null | null | 0 | 94 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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AHussain0418/demo_data | 2022-01-06T02:46:54.000Z | [
"region:us"
] | AHussain0418 | null | null | 0 | 94 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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AlexMaclean/wikipedia-deletion-compressions | 2021-12-07T00:27:21.000Z | [
"region:us"
] | AlexMaclean | null | null | 1 | 94 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DDSC/reddit-da | 2022-10-27T11:00:42.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:da",
"license:mit",
"region:us"
] | DDSC | null | null | 2 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- da
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Reddit-da
---
# Dataset Card for SQuAD-da
## Table of ... | 1,770 | [
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GEM/common_gen | 2022-10-24T15:30:11.000Z | [
"task_categories:other",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
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"language:en",
"license:mit",
"reasoning",
"arxiv:1911.03705",
"arxiv:1910.13461",
"arxiv:2009.12677",
"arxiv:2012.00366",
"a... | GEM | CommonGen is a constrained text generation task, associated with a benchmark
dataset, to explicitly test machines for the ability of generative commonsense
reasoning. Given a set of common concepts; the task is to generate a coherent
sentence describing an everyday scenario using these concepts. | @inproceedings{lin-etal-2020-commongen,
title = "{C}ommon{G}en: A Constrained Text Generation Challenge for Generative Commonsense Reasoning",
author = "Lin, Bill Yuchen and
Zhou, Wangchunshu and
Shen, Ming and
Zhou, Pei and
Bhagavatula, Chandra and
Choi, Yejin and
Ren,... | 0 | 94 | 2022-03-02T23:29:22 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- mit
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids: []
pretty_name: common_gen
tags:
- reasoning
---
# Dataset Card for GEM/common_gen
## Dataset Description
- ... | 25,320 | [
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allegro/klej-allegro-reviews | 2021-11-29T18:25:32.000Z | [
"region:us"
] | allegro | null | null | 0 | 94 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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texturedesign/td01_natural-ground-textures | 2023-09-02T10:21:04.000Z | [
"task_categories:unconditional-image-generation",
"annotations_creators:expert-generated",
"size_categories:n<1K",
"source_datasets:original",
"license:cc-by-nc-4.0",
"texture-synthesis",
"photography",
"non-infringing",
"region:us"
] | texturedesign | null | null | 3 | 94 | 2022-11-19T17:43:30 | ---
annotations_creators:
- expert-generated
language: []
language_creators: []
license:
- cc-by-nc-4.0
multilinguality: []
pretty_name: 'TD01: Natural Ground Texture Photos'
size_categories:
- n<1K
source_datasets:
- original
tags:
- texture-synthesis
- photography
- non-infringing
task_categories:
- unconditional-ima... | 9,727 | [
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parambharat/tamil_asr_corpus | 2022-12-07T17:32:59.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|common_voice",
"source_datasets:extended|openslr",
"language:ta",
"license:cc-by-4.0",
"region:us"
] | parambharat | The corpus contains roughly 1000 hours of audio and trasncripts in Tamil language. The transcripts have beedn de-duplicated using exact match deduplication. | @misc{mile_1,
doi = {10.48550/ARXIV.2207.13331},
url = {https://arxiv.org/abs/2207.13331},
author = {A, Madhavaraj and Pilar, Bharathi and G, Ramakrishnan A},
title = {Subword Dictionary Learning and Segmentation Techniques for Automatic Speech Recognition in Tamil and Kannada},
publisher = {arXiv},
year = ... | 1 | 94 | 2022-12-07T16:36:05 | ---
annotations_creators:
- found
language:
- ta
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Tamil ASR Corpus
size_categories:
- 100K<n<1M
source_datasets:
- extended|common_voice
- extended|openslr
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---... | 2,795 | [
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0.0... |
pierreguillou/DocLayNet-large | 2023-05-17T08:56:48.000Z | [
"task_categories:object-detection",
"task_categories:image-segmentation",
"task_categories:token-classification",
"task_ids:instance-segmentation",
"annotations_creators:crowdsourced",
"size_categories:10K<n<100K",
"language:en",
"language:de",
"language:fr",
"language:ja",
"license:other",
"D... | pierreguillou | Accurate document layout analysis is a key requirement for high-quality PDF document conversion. With the recent availability of public, large ground-truth datasets such as PubLayNet and DocBank, deep-learning models have proven to be very effective at layout detection and segmentation. While these datasets are of adeq... | @article{doclaynet2022,
title = {DocLayNet: A Large Human-Annotated Dataset for Document-Layout Analysis},
doi = {10.1145/3534678.353904},
url = {https://arxiv.org/abs/2206.01062},
author = {Pfitzmann, Birgit and Auer, Christoph and Dolfi, Michele and Nassar, Ahmed S and Staar, Peter W J},
year = {2022}
} | 3 | 94 | 2023-01-25T15:14:52 | ---
language:
- en
- de
- fr
- ja
annotations_creators:
- crowdsourced
license: other
pretty_name: DocLayNet large
size_categories:
- 10K<n<100K
tags:
- DocLayNet
- COCO
- PDF
- IBM
- Financial-Reports
- Finance
- Manuals
- Scientific-Articles
- Science
- Laws
- Law
- Regulations
- Patents
- Government-Tenders
- object... | 14,455 | [
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liuhaotian/LLaVA-CC3M-Pretrain-595K | 2023-07-06T08:51:35.000Z | [
"language:en",
"license:other",
"region:us"
] | liuhaotian | null | null | 41 | 94 | 2023-04-20T14:28:12 | ---
license: other
language:
- en
pretty_name: LLaVA CC3M Pretrain 595K
---
# LLaVA Visual Instruct CC3M 595K Pretrain Dataset Card
## Dataset details
**Dataset type:**
LLaVA Visual Instruct CC3M Pretrain 595K is a subset of CC-3M dataset, filtered with a more balanced concept coverage distribution.
Captions are al... | 2,773 | [
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Oniichat/bluemoon_roleplay_chat_data_300k_messages | 2023-04-29T16:06:27.000Z | [
"region:us"
] | Oniichat | null | null | 37 | 94 | 2023-04-29T14:44:37 | ---
dataset_info:
features:
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dtype: int64
- name: thread_title
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dtype: string
- name: message
dtype: string
splits:
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FredZhang7/all-scam-spam | 2023-07-18T17:16:16.000Z | [
"task_categories:text-classification",
"task_categories:zero-shot-classification",
"size_categories:10K<n<100K",
"language:no",
"language:es",
"language:so",
"language:ca",
"language:af",
"language:it",
"language:nl",
"language:hi",
"language:cy",
"language:ar",
"language:sv",
"language:... | FredZhang7 | null | null | 4 | 94 | 2023-07-04T22:07:15 | ---
license: apache-2.0
language:
- no
- es
- so
- ca
- af
- it
- nl
- hi
- cy
- ar
- sv
- cs
- pl
- de
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- sq
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- fi
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- bg
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- ja
- bn
- ro
- pt
- fr
- hu
- tr
- zh
- mk
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- sk
- ne
- et
- sw
- ru
- multilingual
task_categories:
- text-classification
- zero-shot-class... | 1,624 | [
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totally-not-an-llm/sharegpt-hyperfiltered-3k | 2023-07-13T02:17:45.000Z | [
"license:apache-2.0",
"region:us"
] | totally-not-an-llm | null | null | 6 | 94 | 2023-07-11T01:54:08 | ---
license: apache-2.0
---
# sharegpt-hyperfiltered-3k
90k sharegpt convos brought down to ~3k (3243) via language filtering, keyword detection, deduping, and regex. Following things were done:
- Deduplication on first message from human
- Remove non-English convos
- Remove censorship, refusals, and alignment
- Rem... | 665 | [
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maxolotl/falcon_w3_en_es_v2 | 2023-09-06T23:53:20.000Z | [
"region:us"
] | maxolotl | null | null | 0 | 94 | 2023-09-06T23:42:58 | Entry not found | 15 | [
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HumanCompatibleAI/ppo-seals-Ant-v1 | 2023-09-27T06:56:10.000Z | [
"region:us"
] | HumanCompatibleAI | null | null | 0 | 94 | 2023-09-26T14:12:32 | ---
dataset_info:
features:
- name: obs
sequence:
sequence: float64
- name: acts
sequence:
sequence: float32
- name: infos
sequence: string
- name: terminal
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sequence: float32
splits:
- name: train
num_bytes: 141011280
num_examples: 104
d... | 543 | [
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semaj83/ioqm | 2023-10-15T16:47:34.000Z | [
"license:mit",
"region:us"
] | semaj83 | null | null | 0 | 94 | 2023-09-26T22:24:44 | ---
license: mit
viewer: false
---
This is a dataset of image generating prompts containing objects and quantifiers such as:
`2 cell phones and 1 oven and 2 remotes`
The objects were a subset of 10 random objects taken from the COCO dataset of 80-1 (79 classes): https://docs.ultralytics.com/datasets/detect/coco/#dat... | 872 | [
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TIGER-Lab/MetricInstruct | 2023-10-22T15:04:12.000Z | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:en",
"language:zh",
"language:cs",
"language:ru",
"language:fr",
"license:mit",
"arxiv:2310.00752",
"region:us"
] | TIGER-Lab | null | null | 4 | 94 | 2023-10-04T03:05:36 | ---
configs:
- config_name: train
data_files:
- split: train_real_world
path:
- data/new_real_world_.json
- split: train_synthetic
path:
- data/new_synthetic_.json
- split: train_mix
path:
- data/new_mix_.json
license: mit
task_categories:
- text-generation
language:
- en
- zh
- cs
- ru
... | 6,728 | [
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Fraol/TrainDedupedRefDatasetWMetricFinal2 | 2023-10-08T04:38:56.000Z | [
"region:us"
] | Fraol | null | null | 0 | 94 | 2023-10-08T04:38:50 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
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features:
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lucas-meyer/asr_xh | 2023-10-16T21:54:54.000Z | [
"region:us"
] | lucas-meyer | null | null | 0 | 94 | 2023-10-16T21:07:38 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: audio
dtype: audio
- name: transcription
dtype: string
splits:
- name: train
num_bytes: ... | 715 | [
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hate_speech_pl | 2022-11-03T16:15:27.000Z | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:multi-class-classification",
"task_ids:multi-label-classification",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"task_ids:topic-classification",
"annotations_creators:expert-generated",
"language_creator... | null | HateSpeech corpus in the current version contains over 2000 posts crawled from public Polish web. They represent various types and degrees of offensive language, expressed toward minorities (eg. ethnical, racial). The data were annotated manually. | null | 2 | 93 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pl
license:
- cc-by-nc-sa-3.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
- multi-class-classification
- multi-label-classifica... | 7,339 | [
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laroseda | 2022-11-18T20:18:11.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ro",
"license:cc-by-4.0",
"arxiv:2101.04197",
"arxiv:1901.06543"... | null | LaRoSeDa (A Large Romanian Sentiment Data Set) contains 15,000 reviews written in Romanian, of which 7,500 are positive and 7,500 negative.
Star ratings of 1 and 2 and of 4 and 5 are provided for negative and positive reviews respectively.
The current dataset uses star rating as the label for mu... | @article{
tache2101clustering,
title={Clustering Word Embeddings with Self-Organizing Maps. Application on LaRoSeDa -- A Large Romanian Sentiment Data Set},
author={Anca Maria Tache and Mihaela Gaman and Radu Tudor Ionescu},
journal={ArXiv},
year = {2021}
} | 0 | 93 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ro
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: null
pretty_name: LaRoSeDa
dataset_info... | 6,438 | [
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wrbsc | 2023-01-25T15:02:59.000Z | [
"task_categories:text-classification",
"task_ids:semantic-similarity-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-3.0",
"region:us"
] | null | WUT Relations Between Sentences Corpus contains 2827 pairs of related sentences.
Relationships are derived from Cross-document Structure Theory (CST), which enables multi-document summarization through identification of cross-document rhetorical relationships within a cluster of related documents.
Every relation was ma... | @misc{11321/305,
title = {{WUT} Relations Between Sentences Corpus},
author = {Oleksy, Marcin and Fikus, Dominika and Wolski, Michal and Podbielska, Malgorzata and Turek, Agnieszka and Kędzia, Pawel},
url = {http://hdl.handle.net/11321/305},
note = {{CLARIN}-{PL} digital repository},
copyright = {Attribution-{Shar... | 0 | 93 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pl
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- semantic-similarity-classification
pretty_name: wrbsc
dataset_info:
f... | 5,389 | [
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AlekseyKorshuk/comedy-scripts | 2022-02-11T14:50:39.000Z | [
"region:us"
] | AlekseyKorshuk | This dataset is designed to generate lyrics with HuggingArtists. | @InProceedings{huggingartists:dataset,
title = {Lyrics dataset},
author={Aleksey Korshuk
},
year={2021}
} | 1 | 93 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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HHousen/msrp | 2022-01-01T03:30:43.000Z | [
"region:us"
] | HHousen | null | null | 1 | 93 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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alistvt/coqa | 2022-01-23T02:44:10.000Z | [
"region:us"
] | alistvt | null | null | 0 | 93 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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lgrobol/openminuscule | 2022-10-23T09:28:36.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:100k<n<1M",
"source_datasets:original",
"language:en",
"language:fr",
"license:cc-by-4.0",
"region:us"
] | lgrobol | null | null | 0 | 93 | 2022-03-02T23:29:22 | ---
language_creators:
- crowdsourced
language:
- en
- fr
license:
- cc-by-4.0
multilinguality:
- multilingual
size_categories:
- 100k<n<1M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_name: Open Minuscule
language_bcp47:
- en-GB
- fr-FR
---
Open Minuscule
=======... | 1,770 | [
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persiannlp/parsinlu_entailment | 2022-10-22T15:13:00.000Z | [
"task_ids:natural-language-inference",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|translated|mnli",
"language:fa",
"license:cc-by-nc-sa-4.0",
"arxiv:2012.06154",
"region:us"
] | persiannlp | A Persian textual entailment task (deciding `sent1` entails `sent2`). | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | 0 | 93 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|translated|mnli
task_categories:
- textual-entailment
- natural-language-inference
task_ids:
- textual-entai... | 4,677 | [
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Murple/ksponspeech | 2022-11-14T02:41:37.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ko",
"region:us"
] | Murple | This paper introduces a large-scale spontaneous speech corpus of Korean, named KsponSpeech. This corpus contains 969 h of general open-domain dialog utterances, spoken by about 2000 native Korean speakers in a clean environment. All data were constructed by recording the dialogue of two people freely conversing on a va... | @Article{app10196936,
AUTHOR = {Bang, Jeong-Uk and Yun, Seung and Kim, Seung-Hi and Choi, Mu-Yeol and Lee, Min-Kyu and Kim, Yeo-Jeong and Kim, Dong-Hyun and Park, Jun and Lee, Young-Jik and Kim, Sang-Hun},
TITLE = {KsponSpeech: Korean Spontaneous Speech Corpus for Automatic Speech Recognition},
JOURNAL = {Applied Scien... | 4 | 93 | 2022-11-14T01:58:12 | ---
annotations_creators:
- expert-generated
language:
- ko
language_creators:
- crowdsourced
license: []
multilinguality:
- monolingual
pretty_name: KsponSpeech
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---
# Dataset Card for KsponS... | 6,237 | [
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Norod78/microsoft-fluentui-emoji-768 | 2023-07-16T12:13:07.000Z | [
"task_categories:text-to-image",
"size_categories:n<10K",
"language:en",
"license:mit",
"emoji",
"fluentui",
"region:us"
] | Norod78 | null | null | 6 | 93 | 2023-01-01T09:35:07 | ---
language: en
license: mit
size_categories:
- n<10K
task_categories:
- text-to-image
pretty_name: Microsoft FluentUI Emoji 768x768
dataset_info:
features:
- name: text
dtype: string
- name: image
dtype: image
splits:
- name: train
num_bytes: 679617796.94
num_examples: 7564
download_size: ... | 581 | [
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jordyvl/DUDE_loader | 2023-10-03T10:54:36.000Z | [
"task_categories:question-answering",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-4.0",
"region:us"
] | jordyvl | DUDE requires models to reason and understand about document layouts in multi-page images/PDFs to answer questions about them.
Specifically, models need to incorporate a new modality of layout present in the images/PDFs and reason
over it to answer DUDE questions. | @inproceedings{dude2023icdar,
title={ICDAR 2023 Challenge on Document UnderstanDing of Everything (DUDE)},
author={Van Landeghem, Jordy et . al.},
booktitle={Proceedings of the ICDAR},
year={2023}
} | 8 | 93 | 2023-01-24T15:20:01 | ---
license: cc-by-4.0
task_categories:
- question-answering
language:
- en
pretty_name: DUDE
size_categories:
- 10K<n<100K
---
## Loading the dataset with a specific configuration
There are 3 different OCR versions to choose from with their original format or standardized DUE format, as well as the option to load t... | 1,989 | [
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Multimodal-Fatima/COCO_captions_validation | 2023-03-17T21:22:46.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 93 | 2023-03-17T21:22:06 | ---
dataset_info:
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Francesco/bone-fracture-7fylg | 2023-03-30T09:14:59.000Z | [
"task_categories:object-detection",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc",
"rf100",
"region:us"
] | Francesco | null | null | 1 | 93 | 2023-03-30T09:14:40 | ---
dataset_info:
features:
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lengt... | 3,483 | [
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HANSEN-REPO/HANSEN | 2023-11-01T18:35:34.000Z | [
"license:apache-2.0",
"region:us"
] | HANSEN-REPO | This benchmark environment contains a dataset comprised of human-spoken text and Large Language Models (LLM) generated spoken text.
We also have three benchmark tasks - AA (multi-class classification problem on human datasets), AV (binary classification problem on whether two spoken texts are from same human),
and TT (... | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2023}
} | 1 | 93 | 2023-06-23T20:11:04 | ---
license: apache-2.0
---
# HANSEN
Human and AI Spoken Text Benchmark for Authorship Analysis.
**We are updating the HANSEN to the following specific format **
The various portions of the
(1) open-source data/existing datasets that we are free to re-distribute (All AA and AV datasets except for FTN and CEO)
(2) ... | 4,198 | [
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Stevross/mmlu | 2023-07-11T12:04:33.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"arxiv:2009.03300",
"arxiv:2005.... | Stevross | This is a massive multitask test consisting of multiple-choice questions from various branches of knowledge, covering 57 tasks including elementary mathematics, US history, computer science, law, and more. | @article{hendryckstest2021,
title={Measuring Massive Multitask Language Understanding},
author={Dan Hendrycks and Collin Burns and Steven Basart and Andy Zou and Mantas Mazeika and Dawn Song and Jacob Steinhardt},
journal={Proceedings of the International Conference on Learning Representations (ICLR)}... | 3 | 93 | 2023-07-11T11:58:20 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: mmlu
pretty_name: Measuring Massi... | 39,677 | [
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iamtarun/code_instructions_120k_alpaca | 2023-07-27T15:49:10.000Z | [
"task_categories:text-generation",
"task_categories:question-answering",
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
"code",
"region:us"
] | iamtarun | null | null | 3 | 93 | 2023-07-23T17:34:03 | ---
dataset_info:
features:
- name: instruction
dtype: string
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dtype: string
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dtype: string
splits:
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num_bytes: 154022159
num_examples: 121959
download_size: 72306808
dataset_size: 154022159
task_categories:
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yzhuang/autotree_automl_10000_covertype_sgosdt_l256_dim10_d3_sd0 | 2023-09-07T03:42:01.000Z | [
"region:us"
] | yzhuang | null | null | 0 | 93 | 2023-09-07T03:41:54 | ---
dataset_info:
features:
- name: id
dtype: int64
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sequence:
sequence: float32
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sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
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TrainingDataPro/ripe-strawberries-detection | 2023-09-26T08:38:14.000Z | [
"task_categories:image-classification",
"task_categories:image-to-image",
"task_categories:object-detection",
"language:en",
"license:cc-by-nc-nd-4.0",
"code",
"biology",
"region:us"
] | TrainingDataPro | The dataset consists of photos of strawberries for the identification and recognition of
ripe berries.
The images are annotated with **bounding boxes** that accurately demarcate the location
of the ripe strawberries within the image.
Each image in the dataset showcases a strawberry plantation, and includes a diverse
r... | @InProceedings{huggingface:dataset,
title = {ripe-strawberries-detection},
author = {TrainingDataPro},
year = {2023}
} | 2 | 93 | 2023-09-08T09:29:07 | ---
language:
- en
license: cc-by-nc-nd-4.0
task_categories:
- image-classification
- image-to-image
- object-detection
tags:
- code
- biology
dataset_info:
features:
- name: id
dtype: int32
- name: name
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- name: image
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- name: mask
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dty... | 3,349 | [
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SpeedOfMagic/trivia_qa_tiny | 2023-09-08T16:39:19.000Z | [
"size_categories:n<1K",
"language:en",
"region:us"
] | SpeedOfMagic | null | null | 0 | 93 | 2023-09-08T14:32:44 | ---
language:
- en
size_categories:
- n<1K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
This dataset contains 100 samples from [trivia_qa](https://huggingface.co/datasets/trivia_qa) data... | 666 | [
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vlsp-2023-vllm/truthful_qa | 2023-09-30T05:13:12.000Z | [
"region:us"
] | vlsp-2023-vllm | null | null | 0 | 93 | 2023-09-29T19:37:14 | ---
dataset_info:
features:
- name: question
dtype: string
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struct:
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sequence: string
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sequence: int64
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struct:
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sequence: string
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splits:
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aazer/weathergov | 2023-10-25T17:29:05.000Z | [
"region:us"
] | aazer | null | null | 0 | 93 | 2023-10-25T17:27:46 | Entry not found | 15 | [
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yuvalkirstain/task_prediction_train3 | 2023-10-31T19:33:36.000Z | [
"region:us"
] | yuvalkirstain | null | null | 0 | 93 | 2023-10-31T19:33:13 | ---
configs:
- config_name: default
data_files:
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path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
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cawac | 2022-11-03T16:15:53.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
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"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:ca"... | null | caWaC is a 780-million-token web corpus of Catalan built from the .cat top-level-domain in late 2013. | @inproceedings{DBLP:conf/lrec/LjubesicT14,
author = {Nikola Ljubesic and
Antonio Toral},
editor = {Nicoletta Calzolari and
Khalid Choukri and
Thierry Declerck and
Hrafn Loftsson and
Bente Maegaard and
Joseph Mariani and
... | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: ... | 4,436 | [
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farsi_news | 2022-11-03T16:15:15.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
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"language_creators:found",
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"language:fa",
"licen... | null | Contains Farsi (Persian) datasets for Machine Learning tasks, particularly NLP.
These datasets have been extracted from the RSS feed of two Farsi news agency websites:
- Hamshahri
- RadioFarda | \ | 2 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- fa
license:
- unknown
multilinguality:
- monolingual
size_categories:
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source_datasets:
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task_categories:
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task_ids:
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paperswithcode_id: null
pretty_nam... | 3,487 | [
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glucose | 2022-11-18T20:04:16.000Z | [
"task_categories:fill-mask",
"task_categories:text-generation",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-ROC-stories",
"language:en",
"license:cc-by-4.0",
"commonsense-inferen... | null | When humans read or listen, they make implicit commonsense inferences that frame their understanding of what happened and why. As a step toward AI systems that can build similar mental models, we introduce GLUCOSE, a large-scale dataset of implicit commonsense causal knowledge, encoded as causal mini-theories about the... | @inproceedings{mostafazadeh2020glucose,
title={GLUCOSE: GeneraLized and COntextualized Story Explanations},
author={Nasrin Mostafazadeh and Aditya Kalyanpur and Lori Moon and David Buchanan and Lauren Berkowitz and Or Biran and Jennifer Chu-Carroll},
year={2020},
booktitle={The Conference on Emp... | 2 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-ROC-stories
task_categories:
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paperswithcode_id: glucose
pretty_name: GLUCOSE
tags:
-... | 13,832 | [
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hebrew_this_world | 2022-11-03T16:08:08.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
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"multilinguality:monolingual",
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"language:he... | null | HebrewThisWorld is a data set consists of 2028 issues of the newspaper 'This World' edited by Uri Avnery and were published between 1950 and 1989. Released under the AGPLv3 license. | null | 1 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- he
license:
- agpl-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: nul... | 5,280 | [
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id_puisi | 2022-11-03T16:08:09.000Z | [
"task_categories:text2text-generation",
"task_categories:text-generation",
"task_categories:fill-mask",
"annotations_creators:no-annotation",
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"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:id",
"license:mit",
"poem-gene... | null | Puisi (poem) is an Indonesian poetic form. The dataset contains 7223 Indonesian puisi with its title and author. | null | 2 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- id
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text2text-generation
- text-generation
- fill-mask
task_ids: []
paperswithcode_id: null
pretty_name: Indonesian Pui... | 5,045 | [
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labr | 2023-01-25T14:34:10.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ar",
"license:unknown",
"region:us"
] | null | This dataset contains over 63,000 book reviews in Arabic.It is the largest sentiment analysis dataset for Arabic to-date.The book reviews were harvested from the website Goodreads during the month or March 2013.Each book review comes with the goodreads review id, the user id, the book id, the rating (1 to 5) and the te... | @inproceedings{aly2013labr,
title={Labr: A large scale arabic book reviews dataset},
author={Aly, Mohamed and Atiya, Amir},
booktitle={Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)},
pages={494--498},
year={2013}
} | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
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- ar
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- unknown
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paperswithcode_id: labr
pretty_name: LABR
dataset_info:
... | 4,864 | [
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reclor | 2022-11-18T21:41:37.000Z | [
"region:us"
] | null | Logical reasoning is an important ability to examine, analyze, and critically evaluate arguments as they occur in ordinary
language as the definition from LSAC. ReClor is a dataset extracted from logical reasoning questions of standardized graduate
admission examinations. Empirical results show that the state-of-the-ar... | @inproceedings{yu2020reclor,
author = {Yu, Weihao and Jiang, Zihang and Dong, Yanfei and Feng, Jiashi},
title = {ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning},
booktitle = {International Conference on Learning Representations (ICLR)},
month = {April},
year ... | 1 | 92 | 2022-03-02T23:29:22 | ---
paperswithcode_id: reclor
pretty_name: ReClor
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swedish_reviews | 2023-01-25T14:45:25.000Z | [
"task_categories:text-classification",
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"annotations_creators:found",
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"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:sv",
"license:unknown",
"region:us"
] | null | null | null | 3 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
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- sv
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- unknown
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pretty_name: Swedish Reviews
dataset_info:
features:
- na... | 4,307 | [
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tashkeela | 2022-11-03T16:07:53.000Z | [
"task_categories:text-generation",
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"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:ar",
"l... | null | Arabic vocalized texts.
it contains 75 million of fully vocalized words mainly97 books from classical and modern Arabic language. | @article{zerrouki2017tashkeela,
title={Tashkeela: Novel corpus of Arabic vocalized texts, data for auto-diacritization systems},
author={Zerrouki, Taha and Balla, Amar},
journal={Data in brief},
volume={11},
pages={147},
year={2017},
publisher={Elsevier}
} | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
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- found
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- gpl-2.0
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paperswithcode_id: null
pretty... | 10,280 | [
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tep_en_fa_para | 2022-11-03T16:08:03.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:translation",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"language:fa",
"license:unknown",
"region:us"
] | null | TEP: Tehran English-Persian parallel corpus. The first free Eng-Per corpus, provided by the Natural Language and Text Processing Laboratory, University of Tehran. | @InProceedings{“TEP: Tehran English-Persian Parallel Corpus”,
title = {TEP: Tehran English-Persian Parallel Corpus”, in proceedings of 12th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing-2011)},
authors={M. T. Pilevar, H. Faili, and A. H. Pilevar, },
year={2011}
} | 1 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
- fa
license:
- unknown
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- translation
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- 100K<n<1M
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- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: TepEnFaPara
dataset_info:
features:
- name: tra... | 3,422 | [
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twi_text_c3 | 2022-11-03T16:15:20.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
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"task_ids:masked-language-modeling",
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"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:t... | null | Twi Text C3 is the largest Twi texts collected and used to train FastText embeddings in the
YorubaTwi Embedding paper: https://www.aclweb.org/anthology/2020.lrec-1.335/ | @inproceedings{alabi-etal-2020-massive,
title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of Yoruba and {T}wi",
author = "Alabi, Jesujoba and
Amponsah-Kaakyire, Kwabena and
Adelani, David and
Espa{\\~n}a-Bonet, Cristina",
booktitle = "Proceedings of the 12th ... | 1 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- tw
license:
- cc-by-nc-4.0
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- monolingual
size_categories:
- 100K<n<1M
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- original
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- text-generation
- fill-mask
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- language-modeling
- masked-language-modeling
paperswithcode_id... | 6,735 | [
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wiki_source | 2022-11-03T16:07:54.000Z | [
"task_categories:translation",
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"language_creators:found",
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"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"language:sv",
"license:unknown",
"region:us"
] | null | 2 languages, total number of files: 132
total number of tokens: 1.80M
total number of sentence fragments: 78.36k | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
- sv
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: WikiSource
dataset_info:
features:
- name: id... | 3,230 | [
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wikitext_tl39 | 2022-11-03T16:15:46.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
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"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:fil",... | null | Large scale, unlabeled text dataset with 39 Million tokens in the training set. Inspired by the original WikiText Long Term Dependency dataset (Merity et al., 2016). TL means "Tagalog." Originally published in Cruz & Cheng (2019). | @article{cruz2019evaluating,
title={Evaluating Language Model Finetuning Techniques for Low-resource Languages},
author={Cruz, Jan Christian Blaise and Cheng, Charibeth},
journal={arXiv preprint arXiv:1907.00409},
year={2019}
} | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- fil
- tl
license:
- gpl-3.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: w... | 3,869 | [
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wisesight1000 | 2023-06-14T08:20:50.000Z | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:extended|wisesight_sentiment",
"language:th",
"license:cc0-1.0",
"word-tokenization",
"region:us"
] | null | `wisesight1000` contains Thai social media texts randomly drawn from the full `wisesight-sentiment`, tokenized by human annotators.
Out of the labels `neg` (negative), `neu` (neutral), `pos` (positive), `q` (question), 250 samples each. Some texts are removed because
they look like spam.Because these samples are repres... | @software{bact_2019_3457447,
author = {Suriyawongkul, Arthit and
Chuangsuwanich, Ekapol and
Chormai, Pattarawat and
Polpanumas, Charin},
title = {PyThaiNLP/wisesight-sentiment: First release},
month = sep,
year = 2019,
publisher... | 0 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- th
license:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- extended|wisesight_sentiment
task_categories:
- token-classification
task_ids: []
pretty_name: wisesight1000
tags:
- word-tokenization
datas... | 9,666 | [
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AHussain0418/day2_data | 2022-01-05T18:16:53.000Z | [
"region:us"
] | AHussain0418 | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Alvenir/nst-da-16khz | 2021-11-29T08:58:25.000Z | [
"region:us"
] | Alvenir | null | null | 1 | 92 | 2022-03-02T23:29:22 | # NST Danish 16kHz dataset from Sprakbanken
Data is from sprakbanken and can be accessed using following [link](https://www.nb.no/sprakbanken/en/resource-catalogue/oai-nb-no-sbr-19/).
| 185 | [
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CodedotAI/code-clippy-tfrecords | 2021-12-07T21:40:32.000Z | [
"region:us"
] | CodedotAI | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DDSC/europarl | 2022-07-01T15:42:03.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:da",
"license:cc-by-4.0",
"region:us"
] | DDSC | null | null | 2 | 92 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
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- found
language:
- da
license:
- cc-by-4.0
multilinguality:
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pretty_name: TwitterSent
size_categories:
- n<1K
source_datasets:
- original
task_categories:
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task_ids:
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---
# Dataset Card for DKHa... | 2,538 | [
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Daniele/dante-corpus | 2021-11-12T11:44:16.000Z | [
"region:us"
] | Daniele | null | null | 1 | 92 | 2022-03-02T23:29:22 | ---
YAML tags:
- copy-paste the tags obtained with the online tagging app: https://huggingface.co/spaces/huggingface/datasets-tagging
---
# Dataset Card for [Dataset Name]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summar... | 893 | [
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Nexdata/chinese_dialect | 2023-08-31T03:09:33.000Z | [
"region:us"
] | Nexdata | null | null | 5 | 92 | 2022-03-02T23:29:22 | ---
YAML tags:
- copy-paste the tags obtained with the tagging app: https://github.com/huggingface/datasets-tagging
---
# Dataset Card for chinese_dialect
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported... | 3,298 | [
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HHousen/ParaSCI | 2021-11-24T03:38:25.000Z | [
"arxiv:2101.08382",
"region:us"
] | HHousen | null | null | 1 | 92 | 2022-03-02T23:29:22 | Reformatted version of the ParaSCI dataset from [ParaSCI: A Large Scientific Paraphrase Dataset for Longer Paraphrase Generation](https://arxiv.org/abs/2101.08382). Data retrieved from [dqxiu/ParaSCI](https://github.com/dqxiu/ParaSCI). | 235 | [
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alistvt/coqa-flat | 2022-01-23T01:21:14.000Z | [
"region:us"
] | alistvt | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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anukaver/EstQA | 2021-04-29T15:34:29.000Z | [
"language:et",
"region:us"
] | anukaver | null | null | 0 | 92 | 2022-03-02T23:29:22 | ---
language: et
---
# Estonian Question Answering dataset
* Dataset for extractive question answering in Estonian. It is based on Wikipedia articles, pre-filtered via PageRank. Annotation was done by one person.
* Train set includes 776 context-question-answer triplets. There are several possible answers per questio... | 887 | [
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anuragshas/lv_opus100_processed | 2022-02-01T09:33:15.000Z | [
"region:us"
] | anuragshas | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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anuragshas/pa_cc100_processed | 2022-02-04T10:50:24.000Z | [
"region:us"
] | anuragshas | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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anushakamath/sv_corpora_parliament_processed_v0 | 2022-02-05T11:39:24.000Z | [
"region:us"
] | anushakamath | null | null | 0 | 92 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
anzorq/kbd-ru-1.67M-temp | 2022-01-14T12:00:11.000Z | [
"region:us"
] | anzorq | null | null | 0 | 92 | 2022-03-02T23:29:22 | kbd: web sites dump deduplicated latin script – 835K sentences
ru: wiki dump deduplicated – 835K sentences | 107 | [
[
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s-nlp/paradetox | 2023-09-08T08:59:53.000Z | [
"task_categories:text-generation",
"language:en",
"license:openrail++",
"region:us"
] | s-nlp | null | null | 7 | 92 | 2022-05-19T17:12:06 | ---
license: openrail++
task_categories:
- text-generation
language:
- en
---
# ParaDetox: Detoxification with Parallel Data (English)
This repository contains information about Paradetox dataset -- the first parallel corpus for the detoxification task -- as well as models and evaluation methodology for the detoxific... | 5,021 | [
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0.04931640625,
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... |
bigbio/seth_corpus | 2022-12-22T15:46:51.000Z | [
"multilinguality:monolingual",
"language:en",
"license:apache-2.0",
"region:us"
] | bigbio | null | @Article{SETH2016,
Title = {SETH detects and normalizes genetic variants in text.},
Author = {Thomas, Philippe and Rockt{"{a}}schel, Tim and Hakenberg, J{"{o}}rg and Lichtblau, Yvonne and Leser, Ulf},
Journal = {Bioinformatics},
Year = {2016},
Month = {Jun},
Doi ... | 1 | 92 | 2022-11-13T22:12:17 |
---
language:
- en
bigbio_language:
- English
license: apache-2.0
multilinguality: monolingual
bigbio_license_shortname: APACHE_2p0
pretty_name: SETH Corpus
homepage: https://github.com/rockt/SETH
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- RELATION_EXTRACTION
---
# Dataset ... | 1,096 | [
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0... |
keremberke/aerial-sheep-object-detection | 2023-01-05T08:02:23.000Z | [
"task_categories:object-detection",
"roboflow",
"region:us"
] | keremberke | null | @misc{ aerial-sheep_dataset,
title = { Aerial Sheep Dataset },
type = { Open Source Dataset },
author = { Riis },
howpublished = { \\url{ https://universe.roboflow.com/riis/aerial-sheep } },
url = { https://universe.roboflow.com/riis/aerial-sheep },
journal = { Roboflow Universe },
publisher... | 4 | 92 | 2023-01-02T20:17:28 | ---
task_categories:
- object-detection
tags:
- roboflow
---
### Roboflow Dataset Page
[https://universe.roboflow.com/riis/aerial-sheep/dataset/1](https://universe.roboflow.com/riis/aerial-sheep/dataset/1?ref=roboflow2huggingface)
### Dataset Labels
```
['sheep']
```
### Citation
```
@misc{ aerial-sheep_dataset,
... | 1,717 | [
[
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0.04052734375,
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-0.041168212890625,
-0.031890869140625,
-0.00... |
HuggingFaceH4/hhh_alignment | 2023-03-02T10:13:04.000Z | [
"task_categories:multiple-choice",
"language:en",
"license:apache-2.0",
"human-feedback",
"arxiv:2112.00861",
"region:us"
] | HuggingFaceH4 | This task evaluates language models on alignment, broken down into categories of helpfulness, honesty/accuracy, harmlessness, and other. The evaluations imagine a conversation between a person and a language model assistant. The goal with these evaluations is that on careful reflection, the vast majority of people wo... | @article{DBLP:journals/corr/abs-2112-00861,
author = {Amanda Askell and
Yuntao Bai and
Anna Chen and
Dawn Drain and
Deep Ganguli and
Tom Henighan and
Andy Jones and
Nicholas Joseph and
Benjamin M... | 6 | 92 | 2023-03-01T15:31:15 | ---
license: apache-2.0
task_categories:
- multiple-choice
language:
- en
tags:
- human-feedback
pretty_name: HHH Alignment
dataset_info:
- config_name: harmless
features:
- name: input
dtype: string
- name: targets
struct:
- name: choices
sequence: string
- name: labels
sequence: int3... | 5,445 | [
[
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0.0216064453125,
-0.0282745361328125,
-0.044830322265625,
-0.046783447265625... |
LinhDuong/chatdoctor-5k | 2023-03-28T07:32:21.000Z | [
"license:apache-2.0",
"arxiv:2303.14070",
"region:us"
] | LinhDuong | null | null | 0 | 92 | 2023-03-28T07:23:57 | ---
license: apache-2.0
---
This ChatDoctor-5K dataset is collected from this paper https://arxiv.org/pdf/2303.14070.pdf
Alternatively, you can download the original dataset from this link https://drive.google.com/file/d/1nDTKZ3wZbZWTkFMBkxlamrzbNz0frugg/view?usp=sharing | 271 | [
[
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camel-ai/math | 2023-06-22T21:59:52.000Z | [
"task_categories:text-generation",
"language:en",
"license:cc-by-nc-4.0",
"instruction-finetuning",
"arxiv:2303.17760",
"region:us"
] | camel-ai | null | null | 49 | 92 | 2023-04-10T22:00:46 | ---
license: cc-by-nc-4.0
language:
- en
tags:
- instruction-finetuning
pretty_name: CAMEL Math
task_categories:
- text-generation
arxiv: 2303.17760
extra_gated_prompt: "By using this data, you acknowledge and agree to utilize it solely for research purposes, recognizing that the dataset may contain inaccuracies due to... | 2,185 | [
[
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-0.047637939453125,
-0.0297393798828125,
-0.04574584960937... |
pvduy/sharegpt_alpaca_oa_vicuna_format | 2023-04-29T18:37:21.000Z | [
"region:us"
] | pvduy | null | null | 6 | 92 | 2023-04-29T18:36:44 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 494337138
num_examples: 324160
- name: test
num_bytes: 5944776
num_examples: 1499
download_size: 263071058
dataset_size: 500281914
---
# Dataset Card for "sharegp... | 479 | [
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-0.0... |
Thaweewat/databricks-dolly-15k-th | 2023-05-09T16:15:52.000Z | [
"task_categories:question-answering",
"task_categories:summarization",
"size_categories:10K<n<100K",
"language:th",
"license:cc-by-sa-3.0",
"instruction-finetuning",
"region:us"
] | Thaweewat | null | null | 1 | 92 | 2023-05-09T15:13:01 | ---
license: cc-by-sa-3.0
task_categories:
- question-answering
- summarization
tags:
- instruction-finetuning
language:
- th
size_categories:
- 10K<n<100K
---
# Summary
This is a Thai 🇹🇭-instructed dataset translated from `databricks-dolly-15k` using Google Cloud Translation.
`databricks-dolly-15k` is an open-sourc... | 934 | [
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0.00390625,
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0.0504150390625,
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... |
pranjali97/Bias-detection-combined | 2023-06-11T23:48:39.000Z | [
"region:us"
] | pranjali97 | null | null | 0 | 92 | 2023-06-10T20:28:51 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: __index_level_0__
dtype: int64
splits:
- name: train
num_bytes: 3698636
num_examples: 38213
- name: validation
num_bytes: 414977
num_examples: 4246
download_size: 0
dataset_size: 41136... | 504 | [
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svjack/cmmlu_ed | 2023-07-24T06:56:54.000Z | [
"task_categories:multiple-choice",
"task_categories:question-answering",
"size_categories:10K<n<100K",
"language:zh",
"license:cc-by-nc-4.0",
"chinese",
"llm",
"evaluation",
"arxiv:2306.09212",
"region:us"
] | svjack | CMMLU is a comprehensive Chinese assessment suite specifically designed to evaluate the advanced knowledge and reasoning abilities of LLMs within the Chinese language and cultural context. | @misc{li2023cmmlu,
title={CMMLU: Measuring massive multitask language understanding in Chinese},
author={Haonan Li and Yixuan Zhang and Fajri Koto and Yifei Yang and Hai Zhao and Yeyun Gong and Nan Duan and Timothy Baldwin},
year={2023},
eprint={2306.09212},
archivePrefix={arXiv},
pr... | 0 | 92 | 2023-07-24T06:30:20 | ---
license: cc-by-nc-4.0
task_categories:
- multiple-choice
- question-answering
language:
- zh
tags:
- chinese
- llm
- evaluation
pretty_name: CMMLU
size_categories:
- 10K<n<100K
---
# CMMLU: Measuring massive multitask language understanding in Chinese
- **Homepage:** [https://github.com/haonan-li/CMMLU](https://g... | 4,449 | [
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0.00... |
nampdn-ai/tiny-lessons | 2023-08-29T05:58:57.000Z | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"source_datasets:nampdn-ai/tiny-en",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | nampdn-ai | null | null | 11 | 92 | 2023-08-25T08:11:13 | ---
license: cc-by-sa-4.0
task_categories:
- text-generation
language:
- en
pretty_name: Tiny Lessons
size_categories:
- 10K<n<100K
source_datasets:
- nampdn-ai/tiny-en
---
# Tiny Lessons
The dataset is designed to help causal language models learn more effectively from raw web text. It is augmented from public web ... | 957 | [
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... |
gmongaras/reddit_political_2019_Feb | 2023-09-15T02:29:18.000Z | [
"license:openrail",
"region:us"
] | gmongaras | null | null | 0 | 92 | 2023-09-15T02:18:03 | ---
license: openrail
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 1360555778
num_examples: 5808978
download_size: 832828536
dataset_size: 1360555778
---
Data from https://zenodo.org/record/5851729, dataset comments_2017-02.bz2
In format of: score: {scor... | 338 | [
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0.0... |
ouvic215/Soldering-Data-pix2pix | 2023-09-19T11:20:22.000Z | [
"region:us"
] | ouvic215 | null | null | 0 | 92 | 2023-09-17T09:35:34 | ---
dataset_info:
features:
- name: mask_image
dtype: image
- name: text
dtype: string
- name: image
dtype: image
splits:
- name: train
num_bytes: 108567615.5
num_examples: 1338
download_size: 108539509
dataset_size: 108567615.5
---
# Dataset Card for "Soldering-Data-pix2pix"
[More ... | 445 | [
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ShashiVish/cover-letter-dataset | 2023-10-15T15:20:47.000Z | [
"region:us"
] | ShashiVish | null | null | 0 | 92 | 2023-10-14T14:37:08 | ---
dataset_info:
features:
- name: Job Title
dtype: string
- name: Preferred Qualifications
dtype: string
- name: Hiring Company
dtype: string
- name: Applicant Name
dtype: string
- name: Past Working Experience
dtype: string
- name: Current Working Experience
dtype: string
- na... | 816 | [
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jin05102518/KO_EN_QA_MERGE_SHUFFLE | 2023-10-20T01:30:45.000Z | [
"region:us"
] | jin05102518 | null | null | 0 | 92 | 2023-10-20T01:28:07 | Entry not found | 15 | [
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0.0379028... |
coached_conv_pref | 2023-01-25T14:28:17.000Z | [
"task_categories:other",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:token-classification",
"task_ids:dialogue-modeling",
"task_ids:parsing",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1... | null | A dataset consisting of 502 English dialogs with 12,000 annotated utterances between a user and an assistant discussing
movie preferences in natural language. It was collected using a Wizard-of-Oz methodology between two paid crowd-workers,
where one worker plays the role of an 'assistant', while the other plays the ro... | @inproceedings{48414,
title = {Coached Conversational Preference Elicitation: A Case Study in Understanding Movie Preferences},
author = {Filip Radlinski and Krisztian Balog and Bill Byrne and Karthik Krishnamoorthi},
year = {2019},
booktitle = {Proceedings of the Annual SIGdial Meeting on Discourse and Dialogue}
} | 2 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- other
- text-generation
- fill-mask
- token-classification
task_ids:
- dialogue-modeling
- parsing
paperswi... | 12,757 | [
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0.00722... |
eduge | 2023-01-25T14:29:42.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:mn",
"license:unknown",
"region:us"
] | null | Eduge news classification dataset is provided by Bolorsoft LLC. It is used for training the Eduge.mn production news classifier
75K news articles in 9 categories: урлаг соёл, эдийн засаг, эрүүл мэнд, хууль, улс төр, спорт, технологи, боловсрол and байгал орчин | null | 3 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- mn
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
pretty_name: Eduge
dataset_info:
f... | 4,434 | [
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eth_py150_open | 2022-11-18T20:01:17.000Z | [
"task_categories:other",
"annotations_creators:no-annotation",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"contextual-embeddings",
"region:us"
] | null | A redistributable subset of the ETH Py150 corpus, introduced in the ICML 2020 paper 'Learning and Evaluating Contextual Embedding of Source Code' | @inproceedings{kanade2020learning,
title={Learning and Evaluating Contextual Embedding of Source Code},
author={Kanade, Aditya and Maniatis, Petros and Balakrishnan, Gogul and Shi, Kensen},
booktitle={International Conference on Machine Learning},
pages={5110--5121},
year={2020},
organization={PMLR}
} | 0 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- machine-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- other
task_ids: []
paperswithcode_id: eth-py150-open
pretty_name: ethpy150open
tags:
- contextu... | 4,611 | [
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hard | 2023-01-25T14:31:26.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
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"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar",
"license:unknown",
"region:us"
] | null | This dataset contains 93700 hotel reviews in Arabic language.The hotel reviews were collected from Booking.com website during June/July 2016.The reviews are expressed in Modern Standard Arabic as well as dialectal Arabic.The following table summarize some tatistics on the HARD Dataset. | @incollection{elnagar2018hotel,
title={Hotel Arabic-reviews dataset construction for sentiment analysis applications},
author={Elnagar, Ashraf and Khalifa, Yasmin S and Einea, Anas},
booktitle={Intelligent Natural Language Processing: Trends and Applications},
pages={35--52},
year={2018},
publisher={Springe... | 0 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
paperswithcode_id: hard
pretty_name: Hotel Arabic-Reviews D... | 3,676 | [
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ilist | 2023-01-25T14:32:46.000Z | [
"task_categories:text-classification",
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"language_creators:found",
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"language:awa",
"language:bho",
"language:bra",
"language:hi",
"language:mag",
"license:cc-by-4.0",
... | null | This dataset is introduced in a task which aimed at identifying 5 closely-related languages of Indo-Aryan language family –
Hindi (also known as Khari Boli), Braj Bhasha, Awadhi, Bhojpuri, and Magahi. | null | 1 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
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language_creators:
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- awa
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- hi
- mag
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task_ids: []
pretty_name: ilist
tags:
- language-identificatio... | 6,294 | [
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isizulu_ner_corpus | 2023-01-25T14:33:13.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
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"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:zu",
"license:other",
"region:us"
] | null | Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags. | @inproceedings{isizulu_ner_corpus,
author = {A.N. Manzini and
Roald Eiselen},
title = {NCHLT isiZulu Named Entity Annotated Corpus},
booktitle = {Eiselen, R. 2016. Government domain named entity recognition for South African languages. Proceedings of the 10th Language Resource and Evalua... | 0 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- zu
license:
- other
multilinguality:
- monolingual
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- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: Isizulu Ner Corpus
license... | 5,486 | [
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makhzan | 2022-11-03T16:07:47.000Z | [
"task_categories:text-generation",
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"... | null | An Urdu text corpus for machine learning, natural language processing and linguistic analysis. | null | 0 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ur
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paperswithcode... | 16,550 | [
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msr_zhen_translation_parity | 2022-11-03T16:08:10.000Z | [
"task_categories:translation",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
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"multilinguality:monolingual",
"multilinguality:translation",
"size_categories:1K<n<10K",
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"language:en",
... | null | Translator Human Parity Data
Human evaluation results and translation output for the Translator Human Parity Data release,
as described in https://blogs.microsoft.com/ai/machine-translation-news-test-set-human-parity/.
The Translator Human Parity Data release contains all human evaluation results and translations
rela... | @misc{hassan2018achieving,
title={Achieving Human Parity on Automatic Chinese to English News Translation},
author={ Hany Hassan and Anthony Aue and Chang Chen and Vishal Chowdhary and Jonathan Clark
and Christian Federmann and Xuedong Huang and Marcin Junczys-Dowmunt and William Lewis
... | 0 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
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language:
- en
license:
- ms-pl
multilinguality:
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size_categories:
- 1K<n<10K
source_datasets:
- extended|other-newstest2017
task_categories:
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paperswithcode_id: null
... | 5,522 | [
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sharc | 2022-11-03T16:16:40.000Z | [
"task_categories:question-answering",
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"language:en",
"license:cc-by-sa-3.0... | null | ShARC is a Conversational Question Answering dataset focussing on question answering from texts containing rules. The goal is to answer questions by possibly asking follow-up questions first. It is assumed assume that the question is often underspecified, in the sense that the question does not provide enough informati... | @misc{saeidi2018interpretation,
title={Interpretation of Natural Language Rules in Conversational Machine Reading},
author={Marzieh Saeidi and Max Bartolo and Patrick Lewis and Sameer Singh and Tim Rocktäschel and Mike Sheldon and Guillaume Bouchard and Sebastian Riedel},
year={2018},
eprint={18... | 1 | 91 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
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language:
- en
license:
- cc-by-sa-3.0
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- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
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paperswithcode_id: sharc
pretty_na... | 4,228 | [
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