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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
wmt20_mlqe_task2 | 2023-06-01T14:59:47.000Z | [
"task_categories:translation",
"task_categories:text-classification",
"annotations_creators:expert-generated",
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"language_creators:found",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:extended|wikipedia",
"language:de",
"langu... | null | This shared task (part of WMT20) will build on its previous editions
to further examine automatic methods for estimating the quality
of neural machine translation output at run-time, without relying
on reference translations. As in previous years, we cover estimation
at various levels. Important elements introduced thi... | Not available. | 2 | 135 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
- machine-generated
language_creators:
- found
language:
- de
- en
- zh
license:
- unknown
multilinguality:
- translation
size_categories:
- 1K<n<10K
source_datasets:
- extended|wikipedia
task_categories:
- translation
- text-classification
task_ids: []
pretty_name: WMT20 - ... | 9,278 | [
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NbAiLab/norwegian_parliament | 2022-07-01T19:51:13.000Z | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:no",
"license:cc-by-4.0",
"region:us"
] | NbAiLab | The Norwegian Parliament Speeches is a collection of text passages from
1998 to 2016 and pronounced at the Norwegian Parliament (Storting) by members
of the two major parties: Fremskrittspartiet and Sosialistisk Venstreparti. | @InProceedings{--,
author = {---},
title = {---},
booktitle = {---},
year = 2021,
address = "---"
} | 1 | 135 | 2022-03-02T23:29:22 | ---
annotations_creators:
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- found
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- no
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- cc-by-4.0
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- monolingual
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- 1K<n<10K
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- original
task_categories:
- text-classification
---
# Dataset Card Creation Guide
## Table of Contents
- [Dataset Description](#dat... | 3,184 | [
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0... |
keshan/clean-si-mc4 | 2021-07-14T10:14:11.000Z | [
"region:us"
] | keshan | A colossal, cleaned version of Common Crawl's web crawl corpus.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's mC4 dataset by AllenAI. | @article{2019t5,
author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
journal = {arXiv e-prints},
year = {2... | 0 | 135 | 2022-03-02T23:29:22 | A cleaned version of MC4 dataset for Sinhala, config is a direct adaptation of MC4 original processing script. | 110 | [
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medalpaca/medical_meadow_pubmed_causal | 2023-04-06T17:01:00.000Z | [
"task_categories:question-answering",
"language:en",
"region:us"
] | medalpaca | null | null | 2 | 135 | 2023-04-06T16:59:22 | ---
task_categories:
- question-answering
language:
- en
---
# Dataset Card for Pubmed Causal
## Dataset Description
- **Paper:** https://aclanthology.org/D19-1473/
### Dataset Summary
This is the dataset used in the paper: Detecting Causal Language Use in Science Findings.
### Citation Information
```
@inproceed... | 920 | [
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distil-whisper/tedlium | 2023-09-25T10:30:14.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-nc-nd-3.0",
"region:us"
] | distil-whisper | The TED-LIUM corpus is English-language TED talks, with transcriptions, sampled at 16kHz. It contains about 118 hours of speech. | null | 0 | 135 | 2023-04-10T07:32:45 | ---
license: cc-by-nc-nd-3.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: TEDLIUM
---
# Distil Whisper: TEDLIUM
This is a variant of the [TEDLIUM](https://huggingface.co/datasets/LIUM/tedlium) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions alongside the origi... | 2,011 | [
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distil-whisper/ami-sdm | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,... | @inproceedings{10.1007/11677482_3,
author = {Carletta, Jean and Ashby, Simone and Bourban, Sebastien and Flynn, Mike and Guillemot, Mael and Hain, Thomas and Kadlec, Jaroslav and Karaiskos, Vasilis and Kraaij, Wessel and Kronenthal, Melissa and Lathoud, Guillaume and Lincoln, Mike and Lisowska, Agnes and McCowan, Iain ... | 0 | 135 | 2023-04-11T20:12:21 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: AMI SDM
---
# Distil Whisper: AMI SDM
This is a variant of the [AMI SDM](https://huggingface.co/datasets/edinburghstr/ami) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions alongside the origina... | 1,997 | [
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zeio/baneks | 2023-10-12T18:39:40.000Z | [
"task_categories:text-generation",
"language_creators:crowdsourced",
"language_creators:original",
"size_categories:10K<n<100K",
"language:ru",
"language:en",
"license:apache-2.0",
"not-for-all-audiences",
"art",
"humour",
"jokes",
"region:us"
] | zeio | null | null | 0 | 135 | 2023-10-10T00:49:24 | ---
language:
- ru
- en
license: apache-2.0
tags:
- not-for-all-audiences
- art
- humour
- jokes
annotation_creators:
- crowdsourced
- original
language_creators:
- crowdsourced
- original
pretty_name: baneks
size_categories:
- 10K<n<100K
task_categories:
- text-generation
---
# Dataset card for baneks
## Table of co... | 2,414 | [
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tuanio/book_corpus-input_ids-invalid-random_shuffle-len256 | 2023-10-26T09:02:25.000Z | [
"region:us"
] | tuanio | null | null | 0 | 135 | 2023-10-25T11:51:22 | ---
dataset_info:
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download_size: 3367167037
dataset_size: 6319283552
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "book_co... | 498 | [
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conv_questions | 2023-06-02T12:18:49.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:open-domain-qa",
"task_ids:dialogue-modeling",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source... | null | ConvQuestions is the first realistic benchmark for conversational question answering over knowledge graphs.
It contains 11,200 conversations which can be evaluated over Wikidata. The questions feature a variety of complex
question phenomena like comparisons, aggregations, compositionality, and temporal reasoning. | @InProceedings{christmann2019look,
title={Look before you hop: Conversational question answering over knowledge graphs using judicious context expansion},
author={Christmann, Philipp and Saha Roy, Rishiraj and Abujabal, Abdalghani and Singh, Jyotsna and Weikum, Gerhard},
booktitle={Proceedings of the 28th ACM Int... | 3 | 134 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
language_bcp47:
- en-US
license:
- cc-by-4.0
multilinguality:
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size_categories:
- 10K<n<100K
source_datasets:
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task_categories:
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- fill-mask
task_ids:
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-... | 7,242 | [
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kilt_wikipedia | 2023-04-05T10:08:59.000Z | [
"region:us"
] | null | KILT-Wikipedia: Wikipedia pre-processed for KILT. | @inproceedings{fb_kilt,
author = {Fabio Petroni and
Aleksandra Piktus and
Angela Fan and
Patrick Lewis and
Majid Yazdani and
Nicola De Cao and
James Thorne and
Yacine Jernite and
... | 10 | 134 | 2022-03-02T23:29:22 | ---
paperswithcode_id: null
pretty_name: KiltWikipedia
dataset_info:
features:
- name: kilt_id
dtype: string
- name: wikipedia_id
dtype: string
- name: wikipedia_title
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- name: text
sequence:
- name: paragraph
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- name: anchors
sequence:
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allenai/peer_read | 2022-11-18T21:37:46.000Z | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown",
"acceptability-classification",
"arxiv:1804.09635",
"region:us"
] | allenai | PearRead is a dataset of scientific peer reviews available to help researchers study this important artifact. The dataset consists of over 14K paper drafts and the corresponding accept/reject decisions in top-tier venues including ACL, NIPS and ICLR, as well as over 10K textual peer reviews written by experts for a sub... | @inproceedings{kang18naacl,
title = {A Dataset of Peer Reviews (PeerRead): Collection, Insights and NLP Applications},
author = {Dongyeop Kang and Waleed Ammar and Bhavana Dalvi and Madeleine van Zuylen and Sebastian Kohlmeier and Eduard Hovy and Roy Schwartz},
booktitle = {Meeting of the North American Chapter o... | 3 | 134 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
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multilinguality:
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source_datasets:
- original
task_categories:
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task_ids: []
paperswithcode_id: peerread
pretty_name: PeerRead
tags:
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taskmaster1 | 2022-11-18T21:50:41.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:crowdsourced",
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"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"arxiv:1... | null | Taskmaster-1 is a goal-oriented conversational dataset. It includes 13,215 task-based dialogs comprising six domains. Two procedures were used to create this collection, each with unique advantages. The first involves a two-person, spoken "Wizard of Oz" (WOz) approach in which trained agents and crowdsourced workers i... | @inproceedings{48484,
title = {Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset},
author = {Bill Byrne and Karthik Krishnamoorthi and Chinnadhurai Sankar and Arvind Neelakantan and Daniel Duckworth and Semih Yavuz and Ben Goodrich and Amit Dubey and Kyu-Young Kim and Andy Cedilnik},
year = {2019}
} | 1 | 134 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
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size_categories:
- 1K<n<10K
source_datasets:
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task_categories:
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paperswithcode_id: taskmaster-1
pretty_name: ... | 8,695 | [
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distil-whisper/ami-ihm | 2023-09-25T10:30:14.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | The AMI Meeting Corpus consists of 100 hours of meeting recordings. The recordings use a range of signals
synchronized to a common timeline. These include close-talking and far-field microphones, individual and
room-view video cameras, and output from a slide projector and an electronic whiteboard. During the meetings,... | @inproceedings{10.1007/11677482_3,
author = {Carletta, Jean and Ashby, Simone and Bourban, Sebastien and Flynn, Mike and Guillemot, Mael and Hain, Thomas and Kadlec, Jaroslav and Karaiskos, Vasilis and Kraaij, Wessel and Kronenthal, Melissa and Lathoud, Guillaume and Lincoln, Mike and Lisowska, Agnes and McCowan, Iain ... | 0 | 134 | 2023-04-10T12:57:58 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: AMI IHM
---
# Distil Whisper: AMI IHM
This is a variant of the [AMI IHM](https://huggingface.co/datasets/edinburghcstr/ami) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions alongside the origin... | 1,999 | [
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ttxy/cn_ner | 2023-05-24T08:56:19.000Z | [
"task_categories:token-classification",
"language:code",
"license:bsd",
"ner",
"region:us"
] | ttxy | null | null | 0 | 134 | 2023-05-24T06:27:30 | ---
language:
- code
pretty_name: "Chinese ner dataseet"
tags:
- ner
license: "bsd"
task_categories:
- token-classification
---
来源 https://github.com/liucongg/NLPDataSet
* 从网上收集数据，将CMeEE数据集、IMCS21_task1数据集、CCKS2017_task2数据集、CCKS2018_task1数据集、CCKS2019_task1数据集、CLUENER2020数据集、MSRA数据集、NLPCC2018_task4数据集、CCFBDCI数据集、MMC... | 4,189 | [
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haitengzhao/molecule_property_instruction | 2023-07-13T10:30:29.000Z | [
"task_categories:question-answering",
"language:en",
"license:afl-3.0",
"chemistry",
"biology",
"region:us"
] | haitengzhao | null | null | 3 | 134 | 2023-07-09T07:36:09 | ---
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HydraLM/biology_dataset_standardized | 2023-07-27T17:14:13.000Z | [
"region:us"
] | HydraLM | null | null | 0 | 134 | 2023-07-27T17:13:47 | Entry not found | 15 | [
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YaHi/english_AAAI_Math | 2023-10-09T21:06:27.000Z | [
"region:us"
] | YaHi | null | null | 0 | 134 | 2023-10-09T21:06:26 | ---
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ar_res_reviews | 2023-01-25T14:26:30.000Z | [
"task_categories:text-classification",
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"source_datasets:original",
"language:ar",
"license:unknown",
"region:us"
] | null | Dataset of 8364 restaurant reviews scrapped from qaym.com in Arabic for sentiment analysis | @InProceedings{10.1007/978-3-319-18117-2_2,
author="ElSahar, Hady
and El-Beltagy, Samhaa R.",
editor="Gelbukh, Alexander",
title="Building Large Arabic Multi-domain Resources for Sentiment Analysis",
booktitle="Computational Linguistics and Intelligent Text Processing",
year="2015",
publisher="Springer International Pu... | 3 | 133 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: ArRestReviews
dataset_info:
features:
- name:... | 4,777 | [
[
-0.04046630859375,
-0.0303955078125,
0.01763916015625,
0.0229339599609375,
-0.030303955078125,
0.011810302734375,
-0.0108795166015625,
-0.0214691162109375,
0.03228759765625,
0.043304443359375,
-0.046234130859375,
-0.08758544921875,
-0.04815673828125,
0.01922... |
code_x_glue_cc_code_completion_token | 2023-06-12T08:13:31.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:code",
"l... | null | Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software developers' productivity. We provide code completion evaluation... | @article{raychev2016probabilistic,
title={Probabilistic Model for Code with Decision Trees},
author={Raychev, Veselin and Bielik, Pavol and Vechev, Martin},
journal={ACM SIGPLAN Notices},
pages={731--747},
year={2016},
publisher={ACM New York, NY, USA}
}
@inproceedings{allamanis2013mining,
t... | 1 | 133 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- code
license:
- c-uda
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
pretty_name: CodeXGlueCcCodeComp... | 14,597 | [
[
-0.0379638671875,
-0.040130615234375,
0.023193359375,
0.032470703125,
-0.008209228515625,
0.036163330078125,
0.007144927978515625,
-0.01474761962890625,
0.035003662109375,
0.0275115966796875,
-0.053070068359375,
-0.0562744140625,
-0.0318603515625,
-0.0079269... |
med_hop | 2022-11-03T16:16:32.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-3.0",
"multi-hop",
"arxiv:1710.06481"... | null | MedHop is based on research paper abstracts from PubMed, and the queries are about interactions between pairs of drugs. The correct answer has to be inferred by combining information from a chain of reactions of drugs and proteins. | @misc{welbl2018constructing,
title={Constructing Datasets for Multi-hop Reading Comprehension Across Documents},
author={Johannes Welbl and Pontus Stenetorp and Sebastian Riedel},
year={2018},
eprint={1710.06481},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 2 | 133 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- en
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: medhop
pretty_name: MedHop
tags:... | 3,980 | [
[
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0.0146484375,
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0.039337158203125,
0.04901123046875,
-0.07269287109375,
-0.06353759765625,
-0.04180908203125,
0.020584... |
style_change_detection | 2023-04-05T13:41:00.000Z | [
"region:us"
] | null | The goal of the style change detection task is to identify text positions within a given multi-author document at which the author switches. Detecting these positions is a crucial part of the authorship identification process, and for multi-author document analysis in general.
Access to the dataset needs to be request... | @inproceedings{bevendorff2020shared,
title={Shared Tasks on Authorship Analysis at PAN 2020},
author={Bevendorff, Janek and Ghanem, Bilal and Giachanou, Anastasia and Kestemont, Mike and Manjavacas, Enrique and Potthast, Martin and Rangel, Francisco and Rosso, Paolo and Specht, G{\"u}nther and Stamatatos, Efstathio... | 0 | 133 | 2022-03-02T23:29:22 | ---
paperswithcode_id: null
pretty_name: StyleChangeDetection
dataset_info:
- config_name: narrow
features:
- name: id
dtype: string
- name: text
dtype: string
- name: authors
dtype: int32
- name: structure
sequence: string
- name: site
dtype: string
- name: multi-author
dtype: boo... | 7,812 | [
[
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0.04345703125,
0.03582763671875,
-0.059234619140625,
-0.06494140625,
-0.04803466796875,
0.01930236... |
thai_toxicity_tweet | 2023-01-25T14:45:38.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:th",
"license:cc-by-nc-3.0",
"region:us"
] | null | Thai Toxicity Tweet Corpus contains 3,300 tweets annotated by humans with guidelines including a 44-word dictionary.
The author obtained 2,027 and 1,273 toxic and non-toxic tweets, respectively; these were labeled by three annotators. The result of corpus
analysis indicates that tweets that include toxic words are not ... | @article{sirihattasak2019annotation,
title={Annotation and Classification of Toxicity for Thai Twitter},
author={Sirihattasak, Sugan and Komachi, Mamoru and Ishikawa, Hiroshi},
year={2019}
} | 2 | 133 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- th
license:
- cc-by-nc-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: ThaiToxicityTweet
dataset_info:
... | 8,620 | [
[
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0.02459716796875,
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-0.077880859375,
-0.055419921875,
0.0257415771... |
SetFit/toxic_conversations | 2022-02-11T13:45:54.000Z | [
"region:us"
] | SetFit | null | null | 4 | 133 | 2022-03-02T23:29:22 | # Toxic Conversation
This is a version of the [Jigsaw Unintended Bias in Toxicity Classification dataset](https://www.kaggle.com/c/jigsaw-unintended-bias-in-toxicity-classification/overview). It contains comments from the Civil Comments platform together with annotations if the comment is toxic or not.
10 annotato... | 507 | [
[
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0.051849365234375,
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-0.0335693359375,
-0.052520751953125,
-0... |
M-CLIP/ImageCaptions-7M-Translations | 2022-05-16T21:03:28.000Z | [
"region:us"
] | M-CLIP | null | null | 2 | 133 | 2022-05-16T21:02:40 | Found. Redirecting to https://cdn-lfs.huggingface.co/repos/fd/a8/fda8d7c968a6d27e1390ab6e21a82ccb5e772b75d39fc21bbf9337f5f876a9bf/835f3f7d88a86e05a882c6a6b6333da6ab874776385f85473798769d767c2fca?response-content-disposition=attachment%3B+filename*%3DUTF-8%27%27README.md%3B+filename%3D%22README.md%22%3B&response-content... | 1,183 | [
[
-0.03924560546875,
-0.057159423828125,
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0.0198211669921875,
-0.036865234375,
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0.0142364501953125,
-0.01470947265625,
0.06195068359375,
0.0513916015625,
-0.08050537109375,
-0.057830810546875,
-0.03521728515625,
0.037719726... |
hadiqa123/en_timit_asr | 2022-09-20T15:52:36.000Z | [
"region:us"
] | hadiqa123 | null | null | 0 | 133 | 2022-09-16T21:12:57 | Entry not found | 15 | [
[
-0.021392822265625,
-0.01494598388671875,
0.05718994140625,
0.028839111328125,
-0.0350341796875,
0.046539306640625,
0.052490234375,
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0.01702880859375,
-0.052093505859375,
-0.01494598388671875,
-0.06036376953125,
0.03790... |
bigbio/mirna | 2022-12-22T15:45:38.000Z | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-nc-3.0",
"region:us"
] | bigbio | The corpus consists of 301 Medline citations. The documents were screened for
mentions of miRNA in the abstract text. Gene, disease and miRNA entities were manually
annotated. The corpus comprises of two separate files, a train and a test set, coming
from 201 and 100 documents respectively. | @Article{Bagewadi2014,
author={Bagewadi, Shweta
and Bobi{\'{c}}, Tamara
and Hofmann-Apitius, Martin
and Fluck, Juliane
and Klinger, Roman},
title={Detecting miRNA Mentions and Relations in Biomedical Literature},
journal={F1000Research},
year={2014},
month={Aug},
day={28},
publisher={F1000Research},
volume={3},
pages={... | 1 | 133 | 2022-11-13T22:10:00 |
---
language:
- en
bigbio_language:
- English
license: cc-by-nc-3.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_NC_3p0
pretty_name: miRNA
homepage: https://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads/download-mirna-test-corpus.html
bigbio_pubmed: True
bigbio_public: Tr... | 4,113 | [
[
-0.0302886962890625,
-0.045654296875,
0.0400390625,
-0.0003304481506347656,
-0.030120849609375,
-0.005832672119140625,
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0.06671142578125,
0.0186614990234375,
-0.023956298828125,
-0.04541015625,
-0.0457763671875,
0.02087... |
bigbio/tmvar_v1 | 2022-12-22T15:47:01.000Z | [
"multilinguality:monolingual",
"language:en",
"license:unknown",
"region:us"
] | bigbio | This dataset contains 500 PubMed articles manually annotated with mutation mentions of various kinds. It can be used for NER tasks only.
The dataset is split into train(334) and test(166) splits | @article{wei2013tmvar,
title={tmVar: a text mining approach for extracting sequence variants in biomedical literature},
author={Wei, Chih-Hsuan and Harris, Bethany R and Kao, Hung-Yu and Lu, Zhiyong},
journal={Bioinformatics},
volume={29},
number={11},
pages={1433--1439},
year={2013},
publisher={Oxford ... | 0 | 133 | 2022-11-13T22:12:28 |
---
language:
- en
bigbio_language:
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: tmVar v1
homepage: https://www.ncbi.nlm.nih.gov/research/bionlp/Tools/tmvar/
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
---
# Dataset Car... | 1,062 | [
[
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0.02813720703125,
0.002056121826171875,
-0.03656005859375,
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0.01216888427734375,
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0.0241241455078125,
0.0533447265625,
-0.050933837890625,
-0.07061767578125,
-0.058319091796875... |
vocabtrimmer/mc4_validation | 2023-03-02T13:33:54.000Z | [
"region:us"
] | vocabtrimmer | A colossal, cleaned version of Common Crawl's web crawl corpus.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's mC4 dataset by AllenAI. | @article{2019t5,
author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
journal = {arXiv e-prints},
year = {2... | 0 | 133 | 2023-03-02T09:20:16 | # MC4: only validation split
This contains the validation set of [mc4](https://huggingface.co/datasets/mc4), to reduce the amount of the files at downloading the validation split of the mc4 data.
| 196 | [
[
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0.033050537109375,
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0.02911376953125,
0.06988525390625,
-0.08154296875,
-0.034698486328125,
-0.017669677734375,
0.0250701... |
metaeval/race-c | 2023-05-31T08:39:38.000Z | [
"task_categories:question-answering",
"task_categories:multiple-choice",
"language:en",
"region:us"
] | metaeval | null | null | 0 | 133 | 2023-04-06T07:49:42 | ---
task_categories:
- question-answering
- multiple-choice
language:
- en
---
Race-C : additional data for race (high school/middle school) but for college level
https://github.com/mrcdata/race-c
```bib
@InProceedings{pmlr-v101-liang19a,
title={A New Multi-choice Reading Comprehension Dataset for Curriculum Learning... | 499 | [
[
-0.023895263671875,
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0.0240631103515625,
0.005352020263671875,
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0.035736083984375,
0.006534576416015625,
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0.019317626953125,
0.0180511474609375,
-0.052154541015625,
-0.050048828125,
-0.03369140625,
0.0... |
distil-whisper/voxpopuli | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc0-1.0",
"region:us"
] | distil-whisper | A large-scale multilingual speech corpus for representation learning, semi-supervised learning and interpretation. | @inproceedings{wang-etal-2021-voxpopuli,
title = "{V}ox{P}opuli: A Large-Scale Multilingual Speech Corpus for Representation Learning,
Semi-Supervised Learning and Interpretation",
author = "Wang, Changhan and
Riviere, Morgane and
Lee, Ann and
Wu, Anne and
Talnikar, Chaitanya a... | 0 | 133 | 2023-04-07T17:10:56 | ---
license: cc0-1.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: VoxPopuli
---
# Distil Whisper: VoxPopuli
This is a variant of the [VoxPopuli](https://huggingface.co/datasets/facebook/voxpopuli) dataset, augmented to return the pseudo-labelled Whisper
Transcriptions alongside the o... | 2,005 | [
[
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0.0273590087890625,
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0.0... |
distil-whisper/spgispeech | 2023-09-25T10:28:52.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:other",
"region:us"
] | distil-whisper | The SPGISpeech corpus is derived from company earnings calls manually transcribed by S&P Global, Inc. according to a pro- fessional style guide detailing conventions for capitalization, punctuation, denormalization of non-standard words and tran- scription of disfluencies in spontaneous speech. The basic unit of SPGISp... | @ARTICLE{2021arXiv210402014O,
author = {{O'Neill}, Patrick K. and {Lavrukhin}, Vitaly and {Majumdar}, Somshubra and {Noroozi}, Vahid and {Zhang}, Yuekai and {Kuchaiev}, Oleksii and {Balam}, Jagadeesh and {Dovzhenko}, Yuliya and {Freyberg}, Keenan and {Shulman}, Michael D. and {Ginsburg}, Boris and {Watanabe}, Sh... | 0 | 133 | 2023-04-07T21:11:05 | ---
license: other
task_categories:
- automatic-speech-recognition
language:
- en
extra_gated_prompt: |-
Your access to and use of the information in the Kensho Transcript Dataset (the “Content”), which is provided by Kensho Technologies, LLC, a subsidiary of S&P Global, Inc., (“Kensho”), shall be governed by the f... | 17,467 | [
[
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0.042205810546875,
0.0276336669921875,
-0.06463623046875,
-0.032501220703125,
-0.055572509765625,
0... |
hltcoe/megawika | 2023-10-03T17:24:24.000Z | [
"task_categories:summarization",
"task_categories:question-answering",
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10M<n<100M",
"language:af",
"language:ar",
"language:az",
"language:bn",
"language:cs",
"language:de",
"language:en",
"language:e... | hltcoe | MegaWika is a multi- and crosslingual text dataset containing 30 million
Wikipedia passages with their scraped and cleaned web citations. The
passages span 50 Wikipedias in 50 languages, and the articles in which
the passages were originally embedded are included for convenience. Where
a Wikipedia passage is in a non-E... | @article{barham2023megawika,
title={MegaWika: Millions of reports and their sources across 50 diverse languages},
author={Barham, Samuel and Weller, Orion and
Yuan, Michelle and Murray, Kenton and
Yarmohammadi, Mahsa and Jiang, Zhengping and
Vashishtha, Siddharth and Martin, Alexander ... | 22 | 133 | 2023-05-17T02:07:50 | ---
license: cc-by-sa-4.0
task_categories:
- summarization
- question-answering
- text-generation
- text2text-generation
language:
- af
- ar
- az
- bn
- cs
- de
- en
- es
- et
- fa
- fi
- fr
- ga
- gl
- gu
- he
- hi
- hr
- id
- it
- ja
- ka
- kk
- km
- ko
- lt
- lv
- mk
- ml
- mn
- mr
- my
- ne
- nl
- pl
- ps
- pt
- ro... | 10,431 | [
[
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0.033203125,
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0.047... |
bbz662bbz/databricks-dolly-15k-ja-gozaru | 2023-05-29T12:58:37.000Z | [
"license:cc-by-sa-3.0",
"region:us"
] | bbz662bbz | null | null | 1 | 133 | 2023-05-28T00:51:18 | ---
license: cc-by-sa-3.0
---
This dataset was using "kunishou/databricks-dolly-15k-ja"
This dataset is licensed under CC BY SA 3.0
Last Update : 2023-05-28
databricks-dolly-15k-ja-gozaru
kunishou/databricks-dolly-15k-ja
https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja
| 290 | [
[
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0.0119781494140625,
0.05682373046875,
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0.021392822265625,
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0.036407470703125,
0.05572509765625,
-0.0721435546875,
-0.0243377685546875,
-0.0277252197265625,
0.01335... |
gonced8/multi-session_chat | 2023-08-25T10:59:38.000Z | [
"task_categories:conversational",
"size_categories:100K<n<1M",
"language:en",
"license:gpl-3.0",
"region:us"
] | gonced8 | null | null | 1 | 133 | 2023-08-25T10:56:33 | ---
license: gpl-3.0
task_categories:
- conversational
language:
- en
pretty_name: Multi-Session Chat
size_categories:
- 100K<n<1M
---
Not my dataset, I only cleaned the dataset from [ParlAI - Msc](https://parl.ai/projects/msc/). | 230 | [
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0.01194000244140625,
0.0191497802734375,
0.038299560546875,
0.06298828125,
-0.04364013671875,
-0.0535888671875,
-0.022491455078125,
0.006... |
BrunoHays/multilingual-TEDX-fr | 2023-10-23T09:41:59.000Z | [
"task_categories:automatic-speech-recognition",
"size_categories:100K<n<1M",
"language:fr",
"license:cc-by-nc-nd-4.0",
"region:us"
] | BrunoHays | French subpart of the multilingual TEDX dataset | @inproceedings{salesky2021mtedx,
title={Multilingual TEDx Corpus for Speech Recognition and Translation},
author={Elizabeth Salesky and Matthew Wiesner and Jacob Bremerman and Roldano Cattoni and Matteo Negri and Marco Turchi and Douglas W. Oard and Matt Post},
booktitle={Proceedings of Interspeech},
... | 0 | 133 | 2023-10-02T09:39:41 | ---
license: cc-by-nc-nd-4.0
task_categories:
- automatic-speech-recognition
language:
- fr
size_categories:
- 100K<n<1M
---
The french subset of the dataset [Multilingual TEDx](https://www.openslr.org/100). The data uploaded to HF corresponds to the directory fr-fr. The audio files are automatically resampled to 16 kH... | 1,789 | [
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0.0259399414... |
euclaise/gsm8k_self_correct | 2023-10-19T20:46:04.000Z | [
"size_categories:1K<n<10K",
"license:mit",
"cot",
"self-correct",
"region:us"
] | euclaise | null | null | 1 | 133 | 2023-10-05T20:15:09 | ---
license: mit
size_categories:
- 1K<n<10K
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: mistake
dtype: string
- name: correct_end
dtype: string
splits:
- name: train
num_bytes: 4561402
num_examples: 4676
download_size: 2528831
da... | 629 | [
[
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open-phi/rag-textbook-instruct-full | 2023-10-11T04:57:32.000Z | [
"region:us"
] | open-phi | null | null | 5 | 133 | 2023-10-10T18:53:45 | ---
dataset_info:
features:
- name: formatted_prompt
dtype: string
- name: completion
dtype: string
splits:
- name: train
num_bytes: 117082216
num_examples: 8340
download_size: 44011549
dataset_size: 117082216
configs:
- config_name: default
data_files:
- split: train
path: data/tr... | 510 | [
[
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0.047271728515625,
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haseong8012/child-50k | 2023-10-19T12:27:12.000Z | [
"region:us"
] | haseong8012 | null | null | 0 | 133 | 2023-10-19T11:27:30 | ---
dataset_info:
features:
- name: text
dtype: string
- name: audio
sequence: float32
splits:
- name: train
num_bytes: 9937227708
num_examples: 50000
download_size: 8732585023
dataset_size: 9937227708
---
# Dataset Card for "korean-child-command-voice_train-0-50000_smaplingRate-160002"
[... | 450 | [
[
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newsph | 2022-11-03T16:07:51.000Z | [
"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:fil",... | null | Large-scale dataset of Filipino news articles. Sourced for the NewsPH-NLI Project (Cruz et al., 2020). | @article{cruz2020investigating,
title={Investigating the True Performance of Transformers in Low-Resource Languages: A Case Study in Automatic Corpus Creation},
author={Jan Christian Blaise Cruz and Jose Kristian Resabal and James Lin and Dan John Velasco and Charibeth Cheng},
journal={arXiv preprint arXiv:2010.1... | 2 | 132 | 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: n... | 3,463 | [
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0.0247... |
offcombr | 2023-01-25T14:41:55.000Z | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pt",
"license:unknown",
"hate-speech-detection",
"region:us"
] | null | OffComBR: an annotated dataset containing for hate speech detection in Portuguese composed of news comments on the Brazilian Web. | @article{Pelle2017,
title={Offensive Comments in the Brazilian Web: a dataset and baseline results},
author={Rogers P. de Pelle and Viviane P. Moreira},
booktitle={6th Brazilian Workshop on Social Network Analysis and Mining (BraSNAM)},
year={2017},
} | 4 | 132 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
paperswithcode_id: offcombr
pretty_name: Offensive Comments in the Brazilia... | 3,642 | [
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ollie | 2023-06-01T14:59:47.000Z | [
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:other",
"relation-extraction",
"text-to-structured",
"region:us"
] | null | The Ollie dataset includes two configs for the data
used to train the Ollie informatation extraction algorithm, for 18M
sentences and 3M sentences respectively.
This data is for academic use only. From the authors:
Ollie is a program that automatically identifies and extracts binary
relationships from English sentenc... | @inproceedings{ollie-emnlp12,
author = {Mausam and Michael Schmitz and Robert Bart and Stephen Soderland and Oren Etzioni},
title = {Open Language Learning for Information Extraction},
booktitle = {Proceedings of Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Lea... | 0 | 132 | 2022-03-02T23:29:22 | ---
annotations_creators:
- machine-generated
language_creators:
- crowdsourced
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 10M<n<100M
- 1M<n<10M
source_datasets:
- original
task_categories: []
task_ids: []
pretty_name: Ollie
tags:
- relation-extraction
- text-to-structured
dataset... | 8,399 | [
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poleval2019_cyberbullying | 2023-01-25T14:42:46.000Z | [
"task_categories:text-classification",
"task_ids:intent-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:unknown",
"region:us"
] | null | In Task 6-1, the participants are to distinguish between normal/non-harmful tweets (class: 0) and tweets
that contain any kind of harmful information (class: 1). This includes cyberbullying, hate speech and
related phenomena.
In Task 6-2, the participants shall distinguish between three classes of twee... | @proceedings{ogr:kob:19:poleval,
editor = {Maciej Ogrodniczuk and Łukasz Kobyliński},
title = {{Proceedings of the PolEval 2019 Workshop}},
year = {2019},
address = {Warsaw, Poland},
publisher = {Institute of Computer Science, Polish Academy of Sciences},
url = {http://2019.poleval.pl/fi... | 1 | 132 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- pl
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- intent-classification
pretty_name: Poleval 2019 cyberbullying
dataset_info:
- config_... | 5,046 | [
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-0.00008... |
BeIR/beir-corpus | 2022-10-21T15:30:07.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | 3 | 132 | 2022-03-02T23:29:22 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... | 13,988 | [
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mbazaNLP/kinyarwanda-tts-dataset | 2023-06-27T08:09:28.000Z | [
"language_creators:Digital Umuganda",
"size_categories:3K<n<4K",
"size_categories:~6hours",
"language:rw",
"license:cc-by-4.0",
"region:us"
] | mbazaNLP | null | null | 1 | 132 | 2022-05-27T08:20:36 | ---
language:
- rw
language_creators:
- "Digital Umuganda"
license:
- cc-by-4.0
size_categories:
- 3K<n<4K
- ~6hours
---
# Kinyarwanda TTS dataset
The dataset consists of 3992 clips of Kinyarwanda TTS corpus recorded in a studio using a voice actress, it was collected in the mbaza project
## Data struct... | 890 | [
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asapp/slue | 2022-09-26T23:08:10.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"task_categories:text-classification",
"task_categories:token-classification",
"task_ids:sentiment-analysis",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",... | asapp | Spoken Language Understanding Evaluation (SLUE) benchmark. There are two subsets: (i) SLUE-VoxPopuli which has ASR and NER tasks and (ii) SLUE-VoxCeleb which has ASR and SA tasks. | @inproceedings{shon2022slue,
title={Slue: New benchmark tasks for spoken language understanding evaluation on natural speech},
author={Shon, Suwon and Pasad, Ankita and Wu, Felix and Brusco, Pablo and Artzi, Yoav and Livescu, Karen and Han, Kyu J},
booktitle={ICASSP 2022-2022 IEEE International Conference on Acou... | 3 | 132 | 2022-09-19T18:07:59 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- cc0-1.0
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: slue
pretty_name: SLUE (Spoken Language Understanding Evaluation benchmark)
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_cate... | 15,334 | [
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0.0... |
JosephusCheung/GuanacoDataset | 2023-05-29T12:50:05.000Z | [
"task_categories:text-generation",
"task_categories:question-answering",
"task_categories:conversational",
"language:zh",
"language:en",
"language:ja",
"language:de",
"license:gpl-3.0",
"alpaca",
"llama",
"guanaco",
"doi:10.57967/hf/0570",
"region:us"
] | JosephusCheung | null | null | 448 | 132 | 2023-03-16T06:30:22 | ---
license: gpl-3.0
task_categories:
- text-generation
- question-answering
- conversational
language:
- zh
- en
- ja
- de
tags:
- alpaca
- llama
- guanaco
---
# GuanacoDataset
**News: We're heading towards multimodal VQA, with blip2-flan-t5-xxl Alignment to Guannaco 7B LLM.**
Still under construction: [GuanacoVQA w... | 8,212 | [
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mstz/mushroom | 2023-04-16T17:34:40.000Z | [
"task_categories:tabular-classification",
"size_categories:1K<n<10K",
"language:en",
"license:cc",
"mushroom",
"tabular_classification",
"binary_classification",
"UCI",
"region:us"
] | mstz | null | @misc{misc_mushroom_73,
title = {{Mushroom}},
year = {1987},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: \\url{10.24432/C5959T}}
} | 0 | 132 | 2023-04-06T17:42:03 | ---
language:
- en
tags:
- mushroom
- tabular_classification
- binary_classification
- UCI
pretty_name: Mushroom
size_categories:
- 1K<n<10K
task_categories:
- tabular-classification
configs:
- mushroom
license: cc
---
# Mushroom
The [Mushroom dataset](https://archive.ics.uci.edu/ml/datasets/Mushroom) from the [UCI ML ... | 742 | [
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mattymchen/celeba-hq | 2023-04-26T05:56:53.000Z | [
"region:us"
] | mattymchen | null | null | 0 | 132 | 2023-04-26T05:15:42 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': female
'1': male
splits:
- name: train
num_bytes: 2731627350.0
num_examples: 28000
- name: validation
num_bytes: 197550788.0
num_examples: 2000
dow... | 539 | [
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kz-transformers/multidomain-kazakh-dataset | 2023-05-02T07:19:37.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"source_datasets:original",
"language:kk",
"language:ru",
"license:apache-2.0",
"region:us"
] | kz-transformers | null | null | 9 | 132 | 2023-04-28T13:35:01 | ---
license:
- apache-2.0
annotations_creators:
- no-annotation
language_creators:
- found
language:
- kk
- ru
multilinguality:
- multilingual
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
pretty_name: MDBKD | Multi-Domain Bilingual Kazakh Dataset
---
# Dataset Description
**Point of Cont... | 4,605 | [
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zuzannad1/pixelsum_wiki | 2023-09-13T11:42:49.000Z | [
"region:us"
] | zuzannad1 | null | null | 0 | 132 | 2023-05-16T13:39:49 | ---
dataset_info:
features:
- name: example
dtype: string
- name: summary
dtype: string
splits:
- name: train
num_bytes: 7401808572
num_examples: 6458670
download_size: 4591048930
dataset_size: 7401808572
---
# Dataset Card for "pixelsum_wiki"
[More Information needed](https://github.com/... | 406 | [
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hippocrates/DDI_RE | 2023-10-04T19:08:58.000Z | [
"region:us"
] | hippocrates | null | null | 0 | 132 | 2023-10-04T19:07:43 | Entry not found | 15 | [
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liyucheng/mmlu_test | 2023-10-16T23:28:37.000Z | [
"region:us"
] | liyucheng | null | null | 0 | 132 | 2023-10-16T23:28:24 | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: A
dtype: string
- name: B
dtype: string
- name: C
dtype: string
- name: D
dtype: string
- name: id
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- name: in-context examples
dtype: string
- name: testing i... | 707 | [
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-0.0090484619140625,
0.03057861328125,
0.001895904541015625,
0.06488037109375,
0.01499176025390625,
-0.063232421875,
-0.04669189453125,
-0.037933349609375,
-0.... |
jxu124/OpenX-Embodiment | 2023-11-01T11:46:34.000Z | [
"task_categories:robotics",
"task_categories:reinforcement-learning",
"size_categories:1M<n<10M",
"language:en",
"license:cc-by-4.0",
"Robotics",
"region:us"
] | jxu124 | null | null | 3 | 132 | 2023-10-23T11:24:16 | ---
license: cc-by-4.0
task_categories:
- robotics
- reinforcement-learning
language:
- en
tags:
- Robotics
pretty_name: Open X-Embodiment Dataset
size_categories:
- 1M<n<10M
---
# Open X-Embodiment Dataset (unofficial)
This is an unofficial Dataset Repo. This Repo is set up to make **Open X-Embodiment Dataset (55 in ... | 4,770 | [
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0.0048065185... |
rusheeliyer/german-courts | 2023-11-01T10:50:44.000Z | [
"region:us"
] | rusheeliyer | null | null | 0 | 132 | 2023-11-01T10:46:49 | ---
# For reference on dataset card metadata, see the spec: https://github.com/huggingface/hub-docs/blob/main/datasetcard.md?plain=1
# Doc / guide: https://huggingface.co/docs/hub/datasets-cards
configs:
- config_name: bundesfinanzhof
data_files:
- split: train
path: data/Bundesfinanzhof_train.csv
- split: t... | 5,969 | [
[
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0.043212890625,
0.059478759765625,
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-0.06951904296875,
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0.009... |
senti_ws | 2023-01-25T14:44:03.000Z | [
"task_categories:token-classification",
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:sentiment-scoring",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual"... | null | SentimentWortschatz, or SentiWS for short, is a publicly available German-language resource for sentiment analysis, and pos-tagging. The POS tags are ["NN", "VVINF", "ADJX", "ADV"] -> ["noun", "verb", "adjective", "adverb"], and positive and negative polarity bearing words are weighted within the interval of [-1, 1]. | @INPROCEEDINGS{remquahey2010,
title = {SentiWS -- a Publicly Available German-language Resource for Sentiment Analysis},
booktitle = {Proceedings of the 7th International Language Resources and Evaluation (LREC'10)},
author = {Remus, R. and Quasthoff, U. and Heyer, G.},
year = {2010}
} | 1 | 131 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
- machine-generated
language_creators:
- found
language:
- de
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
- text-classification
task_ids:
- text-scoring
- sentiment-sco... | 5,009 | [
[
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0.0257568359375,
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-0.0694580078125,
-0.053863525390625,
0.009605407... |
GroNLP/ik-nlp-22_slp | 2023-02-01T18:25:21.000Z | [
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:text-retrieval",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unk... | GroNLP | Paragraphs from the Speech and Language Processing book (3ed) by Jurafsky and Martin extracted semi-automatically
from Chapters 2 to 11 of the original book draft. | @book{slp3ed-iknlp2022,
author = {Jurafsky, Daniel and Martin, James},
year = {2021},
month = {12},
pages = {1--235, 1--19},
title = {Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition},
volume = {3}
} | 0 | 131 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
- summarization
- text-retrieval
pretty_name: slp3ed-iknlp2022
tags:
- questio... | 6,964 | [
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... |
SetFit/rte | 2022-02-28T12:46:43.000Z | [
"region:us"
] | SetFit | null | null | 0 | 131 | 2022-03-02T23:29:22 | # Glue RTE
This dataset is a port of the official [`rte` dataset](https://huggingface.co/datasets/glue/viewer/rte/train) on the Hub.
Note that the sentence1 and sentence2 columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
| 313 | [
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codeparrot/codeparrot-clean-valid | 2022-10-10T15:28:51.000Z | [
"region:us"
] | codeparrot | null | null | 5 | 131 | 2022-03-02T23:29:22 | # CodeParrot 🦜 Dataset Cleaned (valid)
Train split of [CodeParrot 🦜 Dataset Cleaned](https://huggingface.co/datasets/lvwerra/codeparrot-clean).
## Dataset structure
```python
DatasetDict({
train: Dataset({
features: ['repo_name', 'path', 'copies', 'size', 'content', 'license', 'hash', 'line_mean', 'lin... | 395 | [
[
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0.039642333984375,
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-0.030914306640625,
-0.02886962890625,
0.019... |
BeIR/quora | 2022-10-23T06:03:40.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | 1 | 131 | 2022-06-05T16:53:54 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... | 13,988 | [
[
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-0.02639770507812... |
juancavallotti/multilingual-gec | 2023-01-06T18:59:59.000Z | [
"task_categories:translation",
"size_categories:100K<n<1M",
"language:en",
"language:es",
"language:fr",
"language:de",
"license:apache-2.0",
"grammar",
"gec",
"multi language",
"language detection",
"region:us"
] | juancavallotti | null | null | 2 | 131 | 2023-01-06T16:07:20 | ---
author: Juan Alberto López Cavallotti
date: Jan 6, 2023
license: apache-2.0
task_categories:
- translation
language:
- en
- es
- fr
- de
tags:
- grammar
- gec
- multi language
- language detection
pretty_name: Multi Lingual Grammar Error Correction Dataset
size_categories:
- 100K<n<1M
---
# Dataset Card for Multil... | 2,976 | [
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EleutherAI/pythia-memorized-evals | 2023-03-14T15:12:36.000Z | [
"region:us"
] | EleutherAI | null | null | 2 | 131 | 2023-03-14T15:11:02 | ---
dataset_info:
features:
- name: index
dtype: int64
- name: tokens
sequence: int64
- name: __index_level_0__
dtype: int64
splits:
- name: duped.1.4b
num_bytes: 730820104
num_examples: 1373722
- name: deduped.1.4b
num_bytes: 557587604
num_examples: 1048097
- name: duped.160... | 1,547 | [
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biu-nlp/abstract-sim-pubmed | 2023-05-13T17:49:55.000Z | [
"region:us"
] | biu-nlp | null | null | 2 | 131 | 2023-05-13T17:42:50 | Entry not found | 15 | [
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0.0379... |
saattrupdan/womens-clothing-ecommerce-reviews | 2023-05-25T20:18:53.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"multimodal",
"region:us"
] | saattrupdan | null | null | 0 | 131 | 2023-05-25T20:04:03 | ---
dataset_info:
features:
- name: review_text
dtype: string
- name: age
dtype: int64
- name: rating
dtype: int64
- name: positive_feedback_count
dtype: int64
- name: division_name
dtype: string
- name: department_name
dtype: string
- name: class_name
dtype: string
- name:... | 1,007 | [
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-0.01035308837890625,
0.00251007080... |
veezbo/akkadian_english_corpus | 2023-09-30T21:32:28.000Z | [
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:en",
"license:mit",
"region:us"
] | veezbo | null | null | 1 | 131 | 2023-09-29T07:22:07 | ---
license: mit
task_categories:
- text-generation
language:
- en
pretty_name: English-translated Akkadian Corpus
size_categories:
- 1K<n<10K
---
# Akkadian English Corpus
This dataset is a cleaned English-translated Akkadian language dataset. This dataset can and has been used for text generation tasks, for example ... | 2,067 | [
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peterbeamish/hack-cnn | 2023-10-13T01:10:44.000Z | [
"source_datasets:github",
"language:en",
"license:other",
"region:us"
] | peterbeamish | null | null | 0 | 131 | 2023-10-12T22:15:54 | ---
language:
- en
license: other
license_name: notouch
license_details: notouch
source_datasets:
- github
configs:
- config_name: default
splits:
- name: train
num_bytes: 725
num_examples: 2
- name: test
num_bytes: 725
num_examples: 2
dataset_info:
- config_name: default
features:
- name: hig... | 566 | [
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0.014419... |
ncslgr | 2022-11-03T16:16:28.000Z | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:n<1K",
"source_datasets:original",
"language:ase",
"language:en",
"license:mit",
"region:us"
] | null | A small corpus of American Sign Language (ASL) video data from native signers, annotated with non-manual features. | @misc{dataset:databases2007volumes,
title={Volumes 2--7},
author={Databases, NCSLGR},
year={2007},
publisher={American Sign Language Linguistic Research Project (Distributed on CD-ROM~…}
} | 4 | 130 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ase
- en
license:
- mit
multilinguality:
- translation
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: NCSLGR
dataset_info:
- config_name: e... | 3,891 | [
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xor_tydi_qa | 2023-01-25T15:03:13.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"source_datasets:extended|tydiqa",
"langu... | null | XOR-TyDi QA brings together for the first time information-seeking questions,
open-retrieval QA, and multilingual QA to create a multilingual open-retrieval
QA dataset that enables cross-lingual answer retrieval. It consists of questions
written by information-seeking native speakers in 7 typologically ... | @misc{asai2020xor,
title={XOR QA: Cross-lingual Open-Retrieval Question Answering},
author={Akari Asai and Jungo Kasai and Jonathan H. Clark and Kenton Lee and Eunsol Choi and Hannaneh Hajishirzi},
year={2020},
eprint={2010.11856},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 1 | 130 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
- found
language:
- ar
- bn
- fi
- ja
- ko
- ru
- te
license:
- mit
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
- extended|tydiqa
task_categories:
- question-answering
task_ids:
- open-domain-qa
... | 9,054 | [
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0.023... |
Kira-Asimov/gender_clinical_trial | 2022-02-10T10:16:03.000Z | [
"region:us"
] | Kira-Asimov | null | null | 2 | 130 | 2022-03-02T23:29:22 | # Gender classification from Clinical Trial Public Data
| 58 | [
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SocialGrep/the-reddit-covid-dataset | 2022-07-01T18:40:57.000Z | [
"annotations_creators:lexyr",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | SocialGrep | This dataset attempts to capture the full extent of COVID-19 discussion across the entire site of Reddit. All posts and comments found to mention the term 'COVID' as of 2021-10-25 have been gathered from the site. | null | 1 | 130 | 2022-03-02T23:29:22 | ---
annotations_creators:
- lexyr
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
paperswithcode_id: null
---
# Dataset Card for the-reddit-covid-dataset
## Table of Contents
- [Dataset Description](#dataset-d... | 4,297 | [
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classla/FRENK-hate-en | 2022-10-21T07:52:06.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"license:other",
"hate-speech-detection",
"offensive-language",
"arxiv:1906.02045",
"region:us"
] | classla | The FRENK Datasets of Socially Unacceptable Discourse in English. | @misc{ljubešić2019frenk,
title={The FRENK Datasets of Socially Unacceptable Discourse in Slovene and English},
author={Nikola Ljubešić and Darja Fišer and Tomaž Erjavec},
year={2019},
eprint={1906.02045},
archivePrefix={arXiv},
primaryClass={cs.CL},
url={https://arxiv.org/abs/... | 1 | 130 | 2022-03-02T23:29:22 | ---
language:
- en
license:
- other
size_categories:
- 1K<n<10K
task_categories:
- text-classification
task_ids: []
tags:
- hate-speech-detection
- offensive-language
---
# Offensive language dataset of Croatian comments FRENK 1.0
English subset of the [FRENK dataset](http://hdl.handle.net/11356/1433). Also available... | 4,822 | [
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changpt/ko-lima-vicuna | 2023-06-14T07:47:51.000Z | [
"task_categories:text-generation",
"size_categories:n<1K",
"language:ko",
"license:cc-by-2.0",
"KoLima",
"region:us"
] | changpt | null | null | 16 | 130 | 2023-06-14T03:58:58 | ---
license: cc-by-2.0
task_categories:
- text-generation
language:
- ko
size_categories:
- n<1K
pretty_name: KoLima(vicuna)
tags:
- KoLima
---
# Ko Lima Vicuna Dataset
GPT4 API를 사용하여 [lima_vicuna_format 데이터](https://huggingface.co/datasets/64bits/lima_vicuna_format)를 한국어로 재생성한 데이터셋입니다.
GPT4 사용시 프롬프트는 "단순 번역이 아닌, 원... | 2,749 | [
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bloyal/oas-paired-sequence-data | 2023-10-26T17:14:13.000Z | [
"task_categories:fill-mask",
"language:en",
"license:cc-by-4.0",
"region:us"
] | bloyal | null | null | 0 | 130 | 2023-09-09T16:24:46 | ---
pretty_name: OAS paired sequences
language: en
task_categories:
- fill-mask
license: cc-by-4.0
configs:
- config_name: human
data_files: "human/*.parquet"
- config_name: rat_SD
data_files: "rat_SD/*.parquet"
- config_name: mouse_BALB_c
data_files: "mouse_BALB_c/*.parquet"
- config_name: mouse_C57BL_6
data_f... | 651 | [
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ai4bharat/IN22-Gen | 2023-09-12T11:13:23.000Z | [
"task_categories:translation",
"language_creators:expert-generated",
"multilinguality:multilingual",
"multilinguality:translation",
"size_categories:1K<n<10K",
"language:as",
"language:bn",
"language:brx",
"language:doi",
"language:en",
"language:gom",
"language:gu",
"language:hi",
"langua... | ai4bharat | IN-22 is a newly created comprehensive benchmark for evaluating machine translation performance in multi-domain, n-way parallel contexts across 22 Indic languages.
IN22-Gen is a general-purpose multi-domain evaluation subset of IN22. It has been created from two sources: Wikipedia and Web Sources offering diverse cont... | @article{ai4bharat2023indictrans2,
title = {IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
author = {AI4Bharat and Jay Gala and Pranjal A. Chitale and Raghavan AK and Sumanth Doddapaneni and Varun Gumma and Aswanth Kumar and Janki Nawale and An... | 1 | 130 | 2023-09-09T17:16:09 | ---
language:
- as
- bn
- brx
- doi
- en
- gom
- gu
- hi
- kn
- ks
- mai
- ml
- mr
- mni
- ne
- or
- pa
- sa
- sat
- sd
- ta
- te
- ur
language_details: >-
asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr,
hin_Deva, kan_Knda, kas_Arab, mai_Deva, mal_Mlym, mar_Deva, mni_Mtei,
npi_Deva, ory_Ory... | 7,349 | [
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0.04150390625,... |
igbo_ner | 2022-11-03T16:16:30.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ig",
"license:unknown",
"arxiv:2004.00648",
"region:us"
] | null | Igbo Named Entity Recognition Dataset | @misc{ezeani2020igboenglish,
title={Igbo-English Machine Translation: An Evaluation Benchmark},
author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},
year={2020},
eprint={2004.00648},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 0 | 129 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ig
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: null
pretty_name: Igbo NER dataset
datas... | 3,923 | [
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multi_booked | 2023-06-01T14:59:47.000Z | [
"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:ca",
"language:eu",
"license:cc-by-3.0",
"arxiv:1803.08614"... | null | MultiBooked is a corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification.
The corpora are compiled from hotel reviews taken mainly from booking.com. The corpora are in Kaf/Naf format, which is
an xml-style stand-off format that allows for multiple layers of annotation. Each revie... | @inproceedings{Barnes2018multibooked,
author={Barnes, Jeremy and Lambert, Patrik and Badia, Toni},
title={MultiBooked: A corpus of Basque and Catalan Hotel Reviews Annotated for Aspect-level Sentiment Classification},
booktitle = {Proceedings of the Eleventh International Conference on Language Resources an... | 0 | 129 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
- eu
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: multibooked
pretty_name: Mult... | 7,425 | [
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polemo2 | 2023-01-25T14:42:43.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:bsd-3-clause",
"region:us"
] | null | The PolEmo2.0 is a set of online reviews from medicine and hotels domains. The task is to predict the sentiment of a review. There are two separate test sets, to allow for in-domain (medicine and hotels) as well as out-of-domain (products and university) validation. | @inproceedings{kocon-etal-2019-multi,
title = "Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews",
author = "Koco{\'n}, Jan and
Milkowski, Piotr and
Za{\'s}ko-Zieli{\'n}ska, Monika",
booktitle = "Proceedings of the 23rd Conference on Computational Natural Language Learni... | 0 | 129 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- bsd-3-clause
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: polemo2
dataset_info:
- config_na... | 4,410 | [
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roman_urdu | 2023-01-25T14:43:17.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ur",
"license:unknown",
"region:us"
] | null | This is an extensive compilation of Roman Urdu Dataset (Urdu written in Latin/Roman script) tagged for sentiment analysis. | @InProceedings{Sharf:2018,
title = "Performing Natural Language Processing on Roman Urdu Datasets",
authors = "Zareen Sharf and Saif Ur Rahman",
booktitle = "International Journal of Computer Science and Network Security",
volume = "18",
number = "1",
pages = "141-148",
year = "2018"
}
@misc{Dua:2019,
author = "Dua, D... | 1 | 129 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- ur
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: roman-urdu-data-set
pretty_name: R... | 4,101 | [
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CLUTRR/v1 | 2022-10-25T10:03:19.000Z | [
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:unknown",
"arxiv:1908.06177",
"region:us"
] | CLUTRR | CLUTRR (Compositional Language Understanding and Text-based Relational Reasoning),
a diagnostic benchmark suite, is first introduced in (https://arxiv.org/abs/1908.06177)
to test the systematic generalization and inductive reasoning capabilities of NLU systems. | @article{sinha2019clutrr,
Author = {Koustuv Sinha and Shagun Sodhani and Jin Dong and Joelle Pineau and William L. Hamilton},
Title = {CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text},
Year = {2019},
journal = {Empirical Methods of Natural Language Processing (EMNLP)},
arxiv = {1908.06177}
} | 2 | 129 | 2022-03-09T19:33:00 | ---
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
---
# Dataset Card for CLUTRR
## Table of Contents
## Dataset Description
### Dataset Summary
**CLUTRR** (**C**ompositional **L**anguage **U**nderstanding and **T**ext-based **R**elational **R**easoning), a diagnostic... | 5,676 | [
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ywchoi/pubmed_abstract_6 | 2022-09-13T01:09:44.000Z | [
"region:us"
] | ywchoi | null | null | 0 | 129 | 2022-09-13T01:08:00 | Entry not found | 15 | [
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edarchimbaud/timeseries-1m-stocks | 2023-11-01T10:03:07.000Z | [
"task_categories:tabular-regression",
"language:en",
"license:mit",
"region:us"
] | edarchimbaud | null | null | 1 | 129 | 2023-05-29T13:50:59 | ---
language:
- en
license: mit
task_categories:
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dmayhem93/agieval-lsat-lr | 2023-06-18T17:26:20.000Z | [
"license:mit",
"arxiv:2304.06364",
"arxiv:2104.06598",
"region:us"
] | dmayhem93 | null | null | 0 | 129 | 2023-06-18T12:50:37 | ---
dataset_info:
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sequence: int64
splits:
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num_bytes: 923886
num_examples: 510
download_size: 469904
dataset_size: 923886
license: mit
---
# Dataset Card for "agieval-lsat-lr"
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alzoubi36/privacy_qa | 2023-06-24T07:54:51.000Z | [
"region:us"
] | alzoubi36 | null | null | 0 | 129 | 2023-06-24T07:53:01 | ---
dataset_info:
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Nexusflow/NexusRaven_API_evaluation | 2023-09-29T05:19:42.000Z | [
"arxiv:2306.05301",
"arxiv:2307.16789",
"region:us"
] | Nexusflow | null | null | 3 | 129 | 2023-09-28T07:58:02 | ---
dataset_info:
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lchakkei/OpenOrca-Traditional-Chinese-Text | 2023-10-15T02:10:20.000Z | [
"region:us"
] | lchakkei | null | null | 0 | 129 | 2023-10-10T16:37:00 | ---
configs:
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path: data/train-*
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features:
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splits:
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---
# Dataset Card for "OpenOrca-Tradi... | 473 | [
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nlewins/onetalk_questions_full_audio | 2023-10-13T09:58:36.000Z | [
"region:us"
] | nlewins | null | null | 0 | 129 | 2023-10-13T09:55:31 | ---
configs:
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Narya-ai/relevancy-summary-synthetic-dataset | 2023-10-14T13:27:43.000Z | [
"region:us"
] | Narya-ai | null | null | 0 | 129 | 2023-10-14T13:27:36 | ---
dataset_info:
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configs:
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gooaq | 2023-01-25T14:31:10.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:2104.08727",
"region... | null | GooAQ is a large-scale dataset with a variety of answer types. This dataset contains over
5 million questions and 3 million answers collected from Google. GooAQ questions are collected
semi-automatically from the Google search engine using its autocomplete feature. This results in
naturalistic questions of practical in... | @article{gooaq2021,
title={GooAQ: Open Question Answering with Diverse Answer Types},
author={Khashabi, Daniel and Ng, Amos and Khot, Tushar and Sabharwal, Ashish and Hajishirzi, Hannaneh and Callison-Burch, Chris},
journal={arXiv preprint},
year={2021}
} | 3 | 128 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- machine-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: gooaq
pretty_name: 'GooAQ: O... | 9,407 | [
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xsum_factuality | 2023-01-25T15:03:16.000Z | [
"task_categories:summarization",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|other-xsum",
"language:en",
"license:cc-by-4.0",
"hallucinations",
"region:us"
] | null | Neural abstractive summarization models are highly prone to hallucinate content that is unfaithful to the input
document. The popular metric such as ROUGE fails to show the severity of the problem. The dataset consists of
faithfulness and factuality annotations of abstractive summaries for the XSum dataset. We have cro... | @InProceedings{maynez_acl20,
author = "Joshua Maynez and Shashi Narayan and Bernd Bohnet and Ryan Thomas Mcdonald",
title = "On Faithfulness and Factuality in Abstractive Summarization",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
year = ... | 4 | 128 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|other-xsum
task_categories:
- summarization
task_ids: []
pretty_name: XSum Hallucination Annotations
tags:
- hallucination... | 8,049 | [
[
-0.032562255859375,
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... |
FRTNX/cosuju | 2021-03-29T09:01:41.000Z | [
"region:us"
] | FRTNX | Court Summaries and Judgements (CoSuJu) Dataset | @InProceedings{huggingface:dataset,
title = {CoSuJu 500+ Court Judegements and Summaries for Machine Text Summarization},
authors = {Busani Ndlovu, Luke Jordan},
year = {2021}
} | 0 | 128 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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-0.052093505859375,
-0.01494598388671875,
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0.03790... |
SocialGrep/reddit-nonewnormal-complete | 2022-07-01T19:02:06.000Z | [
"annotations_creators:lexyr",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | SocialGrep | This corpus contains the complete data for the activity on subreddit /r/NoNewNormal for the entire duration of its existence. | null | 1 | 128 | 2022-03-02T23:29:22 | ---
annotations_creators:
- lexyr
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
paperswithcode_id: null
---
# Dataset Card for reddit-nonewnormal-complete
## Table of Contents
- [Dataset Description](#datase... | 3,773 | [
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albertvillanova/legal_contracts | 2021-12-10T18:03:23.000Z | [
"region:us"
] | albertvillanova | This new dataset is designed to solve this great NLP task and is crafted with a lot of care. | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | 17 | 128 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
ywchoi/pubmed_abstract_8 | 2022-09-13T01:14:30.000Z | [
"region:us"
] | ywchoi | null | null | 0 | 128 | 2022-09-13T01:13:02 | Entry not found | 15 | [
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0.0379... |
AmazonScience/mintaka | 2022-10-28T10:55:50.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:ar",
"multilinguality:de",
"multilinguality:ja",
"multilinguality:hi",
"multilinguality:pt",
"multilinguality:en",
"multilinguality:es",
"multil... | AmazonScience | Mintaka is a complex, natural, and multilingual dataset designed for experimenting with end-to-end
question-answering models. Mintaka is composed of 20,000 question-answer pairs collected in English,
annotated with Wikidata entities, and translated into Arabic, French, German, Hindi, Italian,... | @inproceedings{sen-etal-2022-mintaka,
title = "Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering",
author = "Sen, Priyanka and Aji, Alham Fikri and Saffari, Amir",
booktitle = "Proceedings of the 29th International Conference on Computati... | 5 | 128 | 2022-10-27T18:38:30 | ---
annotations_creators:
- expert-generated
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- ar
- de
- ja
- hi
- pt
- en
- es
- it
- fr
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
paperswithcode_id: mintaka
pretty_name: Min... | 7,470 | [
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-0.0233306884765625,
0.0327... |
pszemraj/scientific_lay_summarisation-plos-norm | 2023-06-20T01:06:39.000Z | [
"task_categories:summarization",
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"source_datasets:tomasg25/scientific_lay_summarisation",
"language:en",
"license:mit",
"arxiv:2210.09932",
"region:us"
] | pszemraj | null | null | 3 | 128 | 2023-03-29T16:24:26 | ---
license: mit
task_categories:
- summarization
- text2text-generation
language:
- en
size_categories:
- 10K<n<100K
source_datasets: tomasg25/scientific_lay_summarisation
---
# scientific_lay_summarisation - PLOS - normalized
This dataset is a modified version of [tomasg25/scientific_lay_summarization](https://hugg... | 3,349 | [
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... |
diffusers/dog-example | 2023-04-18T15:53:56.000Z | [
"region:us"
] | diffusers | null | null | 2 | 128 | 2023-04-18T15:53:06 | Entry not found | 15 | [
[
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0.03790... |
sezer12138/ADE20k_Segementation | 2023-07-21T03:06:25.000Z | [
"region:us"
] | sezer12138 | null | null | 0 | 128 | 2023-07-19T13:18:55 | ---
dataset_info:
features:
- name: image
dtype: image
- name: annotated
dtype: image
- name: Scene_category
dtype:
class_label:
names:
'0': abbey
'1': access_road
'2': acropolis
'3': air_base
'4': aircraft_carrier_object
'5':... | 31,576 | [
[
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0.02593994140625,
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0.057525634765625,
0.041961669921875,
-0.0697021484375,
-0.055145263671875,
-0.032135009765625,
-0... |
OfekGlick/DiscoEval | 2023-10-25T13:19:20.000Z | [
"task_categories:text-classification",
"size_categories:100K<n<1M",
"language:en",
"license:bsd",
"Discourse",
"Discourse Evaluation",
"NLP",
"arxiv:1909.00142",
"region:us"
] | OfekGlick | This dataset contains all tasks of the DiscoEval benchmark for sentence representation learning. | @InProceedings{mchen-discoeval-19,
title = {Evaluation Benchmarks and Learning Criteria for Discourse-Aware Sentence Representations},
author = {Mingda Chen and Zewei Chu and Kevin Gimpel},
booktitle = {Proc. of {EMNLP}},
year={2019}
} | 0 | 128 | 2023-09-22T23:22:52 | ---
license: bsd
task_categories:
- text-classification
language:
- en
tags:
- Discourse
- Discourse Evaluation
- NLP
pretty_name: DiscoEval
size_categories:
- 100K<n<1M
---
# DiscoEval Benchmark Datasets
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [D... | 7,574 | [
[
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numeric_fused_head | 2023-06-01T14:59:47.000Z | [
"task_categories:token-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categories:1K<n<10K",
"source_datasets:original... | null | Fused Head constructions are noun phrases in which the head noun is missing and is said to be "fused" with its dependent modifier. This missing information is implicit and is important for sentence understanding.The missing heads are easily filled in by humans, but pose a challenge for computational models.
For examp... | @article{elazar_head,
author = {Elazar, Yanai and Goldberg, Yoav},
title = {Where’s My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution},
journal = {Transactions of the Association for Computational Linguistics},
volume = {7},
number = {},
pages = {519-... | 1 | 127 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
- expert-generated
- machine-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids: []
paperswithcode_id: numeric-fuse... | 5,932 | [
[
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0.053802490234375,
0.03717041015625,
-0.07196044921875,
-0.07159423828125,
-0.03887939453125,
0.0252... |
Paul/hatecheck-french | 2022-07-05T10:40:23.000Z | [
"task_categories:text-classification",
"task_ids:hate-speech-detection",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:fr",
"license:cc-by-4.0",
"arxiv:2206.09917",
"regi... | Paul | null | null | 0 | 127 | 2022-07-05T10:39:16 | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- fr
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: French HateCheck
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- hate-speech-detection
---
# Dataset C... | 3,489 | [
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... |
metaeval/implicit-hate-stg1 | 2023-05-31T08:52:07.000Z | [
"task_categories:text-classification",
"language:en",
"license:unknown",
"region:us"
] | metaeval | null | null | 0 | 127 | 2023-04-17T08:27:05 | ---
license: unknown
task_categories:
- text-classification
language:
- en
---
https://github.com/SALT-NLP/implicit-hate
```
@inproceedings{elsherief-etal-2021-latent,
title = "Latent Hatred: A Benchmark for Understanding Implicit Hate Speech",
author = "ElSherief, Mai and
Ziems, Caleb and
Muchlin... | 792 | [
[
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0.0023708343505859375,
-0.043304443359375,
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0.... |
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