id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 68.7k ⌀ | citation stringlengths 0 10.7k ⌀ | cardData null | likes int64 0 3.55k | downloads int64 0 10.1M | card stringlengths 0 1.01M |
|---|---|---|---|---|---|---|---|---|---|
PlanTL-GOB-ES/SQAC | 2022-11-18T12:00:35.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:original",
"language:es",
"license:cc-by-sa-4.0",
"arxiv:1606.05250",
"region:us"
] | PlanTL-GOB-ES | This dataset contains 6,247 contexts and 18,817 questions with their answers, 1 to 5 for each fragment.
The sources of the contexts are:
* Encyclopedic articles from [Wikipedia in Spanish](https://es.wikipedia.org/), used under [CC-by-sa licence](https://creativecommons.org/licenses/by-sa/3.0/legalcode).
* News fro... | bibtex
@article{DBLP:journals/corr/abs-2107-07253,
author = {Asier Guti{\'{e}}rrez{-}Fandi{\~{n}}o and
Jordi Armengol{-}Estap{\'{e}} and
Marc P{\`{a}}mies and
Joan Llop{-}Palao and
Joaqu{\'{\i}}n Silveira{-}Ocampo and
Casimiro Pio Carrino a... | null | 7 | 171 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- es
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Spanish Question Answering Corpus (SQAC)
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# SQAC (Spanish Question-A... |
scikit-learn/imdb | 2022-06-16T09:11:24.000Z | [
"license:other",
"region:us"
] | scikit-learn | null | null | null | 0 | 171 | ---
license: other
---
This is the sentiment analysis dataset based on IMDB reviews initially released by Stanford University.
```
This is a dataset for binary sentiment classification containing substantially more data than previous benchmark datasets.
We provide a set of 25,000 highly polar movie reviews for traini... |
tner/wnut2017 | 2022-08-06T23:30:30.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:monolingual",
"size_categories:1k<10K",
"language:en",
"license:other",
"region:us"
] | tner | [WNUT 2017 NER dataset](https://aclanthology.org/W17-4418/) | @inproceedings{derczynski-etal-2017-results,
title = "Results of the {WNUT}2017 Shared Task on Novel and Emerging Entity Recognition",
author = "Derczynski, Leon and
Nichols, Eric and
van Erp, Marieke and
Limsopatham, Nut",
booktitle = "Proceedings of the 3rd Workshop on Noisy User-gene... | null | 0 | 171 | ---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1k<10K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: WNUT 2017
---
# Dataset Card for "tner/wnut2017"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tner)
- ... |
luigisaetta/atco2 | 2022-08-29T07:36:28.000Z | [
"region:us"
] | luigisaetta | null | null | null | 2 | 171 | This dataset contains ATC communication.
It can be used to fine tune an **ASR** model, specialised for Air Traffic Control Communications (ATC)
Its data have been taken from the [ATCO2 site](https://www.atco2.org/data) |
ChristophSchuhmann/improved_aesthetics_5plus | 2022-08-11T12:46:57.000Z | [
"license:apache-2.0",
"region:us"
] | ChristophSchuhmann | null | null | null | 13 | 171 | ---
license: apache-2.0
---
|
taka-yayoi/databricks-dolly-15k-ja | 2023-04-17T09:18:13.000Z | [
"license:cc-by-sa-3.0",
"region:us"
] | taka-yayoi | null | null | null | 1 | 171 | ---
license: cc-by-sa-3.0
---
こちらのデータセットを活用させていただき、Dollyのトレーニングスクリプトで使えるように列名の変更とJSONLへの変換を行っています。
https://huggingface.co/datasets/kunishou/databricks-dolly-15k-ja
Dolly
https://github.com/databrickslabs/dolly |
jiacheng-ye/nl2bash | 2023-04-17T12:55:38.000Z | [
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:en",
"code",
"region:us"
] | jiacheng-ye | The dataset is constructed from
https://github.com/TellinaTool/nl2bash | @inproceedings{LinWZE2018:NL2Bash,
author = {Xi Victoria Lin and Chenglong Wang and Luke Zettlemoyer and Michael D. Ernst},
title = {NL2Bash: A Corpus and Semantic Parser for Natural Language Interface to the Linux Operating System},
booktitle = {Proceedings of the Eleventh International Conference on Language... | null | 0 | 171 | ---
task_categories:
- text-generation
language:
- en
tags:
- code
pretty_name: NL2Bash
size_categories:
- 1K<n<10K
--- |
tomas-gajarsky/cifar100-lt | 2023-06-24T20:25:07.000Z | [
"task_categories:image-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:cifar100",
"language:en",
"license:apache-2.0",
"region:us"
] | tomas-gajarsky | The CIFAR-100-LT dataset is comprised of under 60,000 color images, each measuring 32x32 pixels,
distributed across 100 distinct classes.
The number of samples within each class decreases exponentially with factors of 10 and 100.
The dataset includes 10,000 test images, with 100 images per class,
and fewer than 50,... | @TECHREPORT{Krizhevsky09learningmultiple,
author = {Alex Krizhevsky},
title = {Learning multiple layers of features from tiny images},
institution = {},
year = {2009}
} | null | 0 | 171 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license: apache-2.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- cifar100
task_categories:
- image-classification
task_ids: []
paperswithcode_id: cifar-100
pretty_name: Cifar100-LT
dataset_info:
featu... |
covid_qa_castorini | 2022-11-03T16:30:54.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:apache-2.0",
"arxiv:2004.1... | null | CovidQA is the beginnings of a question answering dataset specifically designed for COVID-19, built by hand from knowledge gathered from Kaggle's COVID-19 Open Research Dataset Challenge. | @article{tang2020rapidly,
title={Rapidly Bootstrapping a Question Answering Dataset for COVID-19},
author={Tang, Raphael and Nogueira, Rodrigo and Zhang, Edwin and Gupta, Nikhil and Cam, Phuong and Cho, Kyunghyun and Lin, Jimmy},
journal={arXiv preprint arXiv:2004.11339},
year={2020}
} | null | 0 | 170 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extractive-qa
paperswithcode_id: covidqa
pretty_name: Cov... |
maritaca-ai/ag_news_pt | 2023-02-16T00:58:33.000Z | [
"region:us"
] | maritaca-ai | AG is a collection of more than 1 million news articles. News articles have been
gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of
activity. ComeToMyHead is an academic news search engine which has been running
since July, 2004. The dataset is provided by the academic comunity for researc... | @inproceedings{Zhang2015CharacterlevelCN,
title={Character-level Convolutional Networks for Text Classification},
author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
booktitle={NIPS},
year={2015}
} | null | 1 | 170 | Entry not found |
Francesco/trail-camera | 2023-03-30T09:11:17.000Z | [
"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 | null | 0 | 170 | ---
dataset_info:
features:
- name: image_id
dtype: int64
- name: image
dtype: image
- name: width
dtype: int32
- name: height
dtype: int32
- name: objects
sequence:
- name: id
dtype: int64
- name: area
dtype: int64
- name: bbox
sequence: float32
lengt... |
ai4bharat/IN22-Conv | 2023-09-12T11:11:17.000Z | [
"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-Conv is the conversation domain subset of IN22. It is designed to assess translation quality in typical day-to-day conversational-style applications. ... | @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... | null | 2 | 170 | ---
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... |
qa_zre | 2023-04-05T13:37:03.000Z | [
"task_categories:question-answering",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:unknown",
"zero-shot-relation-extraction",
"region:us"
] | null | A dataset reducing relation extraction to simple reading comprehension questions | @inproceedings{levy-etal-2017-zero,
title = "Zero-Shot Relation Extraction via Reading Comprehension",
author = "Levy, Omer and
Seo, Minjoon and
Choi, Eunsol and
Zettlemoyer, Luke",
booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 201... | null | 1 | 169 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: QaZre
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- question-answering
task_ids: []
paperswithcode_id: null
tags:
- zero-shot-relatio... |
imodels/credit-card | 2022-08-14T15:37:54.000Z | [
"task_categories:tabular-classification",
"size_categories:10K<n<100K",
"interpretability",
"fairness",
"medicine",
"region:us"
] | imodels | null | null | null | 3 | 169 | ---
annotations_creators: []
language: []
language_creators: []
license: []
multilinguality: []
pretty_name: credit-card
size_categories:
- 10K<n<100K
source_datasets: []
tags:
- interpretability
- fairness
- medicine
task_categories:
- tabular-classification
task_ids: []
---
Port of the credit-card dataset from UCI (... |
ashraq/ott-qa-20k | 2022-10-21T09:06:25.000Z | [
"region:us"
] | ashraq | null | null | null | 3 | 169 | ---
dataset_info:
features:
- name: url
dtype: string
- name: title
dtype: string
- name: header
sequence: string
- name: data
sequence:
sequence: string
- name: section_title
dtype: string
- name: section_text
dtype: string
- name: uid
dtype: string
- name: intro
... |
antolin/python-150_interduplication | 2023-09-18T08:35:19.000Z | [
"region:us"
] | antolin | null | null | null | 1 | 169 | ---
dataset_info:
features:
- name: id_within_dataset
dtype: int64
- name: snippet
dtype: string
- name: tokens
sequence: string
- name: nl
dtype: string
- name: split_within_dataset
dtype: string
- name: is_duplicated
dtype: bool
splits:
- name: train
num_bytes: 41652808.0... |
species_800 | 2023-06-16T11:33:29.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | null | We have developed an efficient algorithm and implementation of a dictionary-based approach to named entity recognition,
which we here use to identifynames of species and other taxa in text. The tool, SPECIES, is more than an order of
magnitude faster and as accurate as existing tools. The precision and recall was asses... | @article{pafilis2013species,
title={The SPECIES and ORGANISMS resources for fast and accurate identification of taxonomic names in text},
author={Pafilis, Evangelos and Frankild, Sune P and Fanini, Lucia and Faulwetter, Sarah and Pavloudi, Christina and Vasileiadou, Aikaterini and Arvanitidis, Christo... | null | 2 | 168 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: species800
dataset_info:
... |
animelover/danbooru2022 | 2023-07-13T05:49:37.000Z | [
"task_categories:text-to-image",
"size_categories:1M<n<10M",
"language:en",
"license:cc0-1.0",
"doi:10.57967/hf/0425",
"region:us"
] | animelover | null | null | null | 92 | 168 | ---
license: cc0-1.0
task_categories:
- text-to-image
language:
- en
pretty_name: Danbooru 2022
size_categories:
- 1M<n<10M
---
Collect images from [danbooru website](https://danbooru.donmai.us/).
Post id range: 6019085 - 1019085
About 4M+ images.
All images with the shortest edge greater than 768 are scaled to the... |
CM/codexglue_code2text_python | 2023-04-22T01:52:50.000Z | [
"region:us"
] | CM | null | null | null | 2 | 168 | ---
dataset_info:
features:
- name: id
dtype: int32
- name: repo
dtype: string
- name: path
dtype: string
- name: func_name
dtype: string
- name: original_string
dtype: string
- name: language
dtype: string
- name: code
dtype: string
- name: code_tokens
sequence: string... |
SotirisLegkas/clickbait | 2023-06-23T11:30:01.000Z | [
"region:us"
] | SotirisLegkas | null | null | null | 0 | 168 | Entry not found |
sentiment140 | 2023-04-05T13:40:06.000Z | [
"language:en",
"region:us"
] | null | Sentiment140 consists of Twitter messages with emoticons, which are used as noisy labels for
sentiment classification. For more detailed information please refer to the paper. | @article{go2009twitter,
title={Twitter sentiment classification using distant supervision},
author={Go, Alec and Bhayani, Richa and Huang, Lei},
journal={CS224N project report, Stanford},
volume={1},
number={12},
pages={2009},
year={2009}
} | null | 8 | 167 | ---
language:
- en
paperswithcode_id: sentiment140
pretty_name: Sentiment140
train-eval-index:
- config: sentiment140
task: text-classification
task_id: multi_class_classification
splits:
train_split: train
eval_split: test
col_mapping:
text: text
sentiment: target
metrics:
- type: accuracy
... |
ScandEval/angry-tweets-mini | 2023-07-05T09:52:07.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:da",
"license:cc-by-4.0",
"region:us"
] | ScandEval | null | null | null | 0 | 167 | ---
license: cc-by-4.0
task_categories:
- text-classification
language:
- da
size_categories:
- 1K<n<10K
--- |
kensho/spgispeech | 2022-10-21T14:46:30.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:other",
"arxiv:2104.02014",
"region:us"
] | kensho | 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... | null | 19 | 167 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
pretty_name: SpgiSpeech
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- automatic-speech-recognition
extra_gated_prompt: |-
Your access to and use of th... |
MoritzLaurer/multilingual-NLI-26lang-2mil7 | 2022-08-22T21:40:14.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:multi-input-text-classification",
"annotations_creators:crowdsourced",
"language_creators:machinetranslation",
"size_categories:1M<n<5",
"source_datasets:multi_nli",
"source_datasets:anli",
"source_datasets:fever... | MoritzLaurer | null | null | null | 28 | 167 | ---
annotations_creators:
- crowdsourced
language_creators:
- machinetranslation
size_categories:
- 1M<n<5
source_datasets:
- multi_nli
- anli
- fever
- lingnli
- alisawuffles/WANLI
task_categories:
- text-classification
task_ids:
- natural-language-inference
- multi-input-text-classification
language:
- multilingual
... |
ywchoi/pubmed_abstract_1 | 2022-09-13T00:56:17.000Z | [
"region:us"
] | ywchoi | null | null | null | 0 | 167 | Entry not found |
bigbio/anat_em | 2022-12-22T15:43:16.000Z | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-3.0",
"region:us"
] | bigbio | The extended Anatomical Entity Mention corpus (AnatEM) consists of 1212 documents (approx. 250,000 words) manually annotated to identify over 13,000 mentions of anatomical entities. Each annotation is assigned one of 12 granularity-based types such as Cellular component, Tissue and Organ, defined with reference to the ... | @article{pyysalo2014anatomical,
title={Anatomical entity mention recognition at literature scale},
author={Pyysalo, Sampo and Ananiadou, Sophia},
journal={Bioinformatics},
volume={30},
number={6},
pages={868--875},
year={2014},
publisher={Oxford University Press}
} | null | 0 | 167 |
---
language:
- en
bigbio_language:
- English
license: cc-by-sa-3.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_SA_3p0
pretty_name: AnatEM
homepage: http://nactem.ac.uk/anatomytagger/#AnatEM
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
---
# Dataset Card for An... |
kuanhuggingface/promptTTS_encodec_v2_small | 2023-06-12T05:45:16.000Z | [
"region:us"
] | kuanhuggingface | null | null | null | 0 | 167 | ---
dataset_info:
features:
- name: file_id
dtype: string
- name: instruction
dtype: string
- name: transcription
dtype: string
- name: src_encodec_0
sequence: int64
- name: src_encodec_1
sequence: int64
- name: src_encodec_2
sequence: int64
- name: src_encodec_3
sequence: in... |
Amani27/massive_translation_dataset | 2023-07-25T14:54:44.000Z | [
"task_categories:translation",
"size_categories:10K<n<100K",
"language:en",
"language:de",
"language:es",
"language:hi",
"language:fr",
"language:it",
"language:ar",
"language:nl",
"language:ja",
"language:pt",
"license:cc-by-4.0",
"region:us"
] | Amani27 | null | null | null | 3 | 167 | ---
configs:
- config_name: default
data_files:
- split: train
path: "train.csv"
- split: validation
path: "validation.csv"
- split: test
path: "test.csv"
license: cc-by-4.0
task_categories:
- translation
language:
- en
- de
- es
- hi
- fr
- it
- ar
- nl
- ja
- pt
size_categories:
- 10K<n<100K
... |
euclaise/mqa | 2023-09-25T01:52:04.000Z | [
"task_categories:question-answering",
"size_categories:10K<n<100K",
"region:us"
] | euclaise | null | null | null | 0 | 167 | ---
dataset_info:
features:
- name: msg
dtype: string
- name: resp_correct
dtype: string
- name: resp_incorrect
sequence: string
splits:
- name: train
num_bytes: 21626021.146013975
num_examples: 23408
download_size: 18857093
dataset_size: 21626021.146013975
configs:
- config_name: de... |
thaisum | 2022-11-18T21:51:46.000Z | [
"task_categories:summarization",
"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:100K<n<1M",
"source_d... | null | ThaiSum is a large-scale corpus for Thai text summarization obtained from several online news websites namely Thairath,
ThaiPBS, Prachathai, and The Standard. This dataset consists of over 350,000 article and summary pairs
written by journalists. | @mastersthesis{chumpolsathien_2020,
title={Using Knowledge Distillation from Keyword Extraction to Improve the Informativeness of Neural Cross-lingual Summarization},
author={Chumpolsathien, Nakhun},
year={2020},
school={Beijing Institute of Technology} | null | 7 | 166 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- th
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- summarization
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcod... |
stanford-crfm/DSIR-filtered-pile-50M | 2023-09-16T14:50:10.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"size_categories:10M<n<100M",
"language:en",
"license:mit",
"language modeling",
"masked language modeling",
"pretraining",
"pile",
"DSIR",
"arxiv:2302.03169",
"region:us"
] | stanford-crfm | null | null | null | 4 | 166 | ---
license: mit
language:
- en
size_categories:
- 10M<n<100M
task_categories:
- text-generation
- fill-mask
tags:
- language modeling
- masked language modeling
- pretraining
- pile
- DSIR
---
# Dataset Card for DSIR-filtered-pile-50M
## Dataset Description
- **Repository:** https://github.com/p-lambda/dsir
- **Pape... |
ruanchaves/faquad-nli | 2023-04-13T18:26:38.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:extended|wikipedia",
"language:pt",
"license:cc-by-4.0",
"region:us"
] | ruanchaves | null | 1 | 166 | ---
pretty_name: FaQuAD-NLI
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive-qa
# paperswithcode_id: faquad
tra... | ||
distil-whisper/librispeech_asr | 2023-09-25T10:30:13.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:cc-by-4.0",
"region:us"
] | distil-whisper | LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz,
prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read
audiobooks from the LibriVox project, and has been carefully segmented and aligned.87 | @inproceedings{panayotov2015librispeech,
title={Librispeech: an ASR corpus based on public domain audio books},
author={Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev},
booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on},
pages={5206--... | null | 0 | 166 | ---
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
language:
- en
-pretty_name: LibriSpeech ASR
---
# Distil Whisper: LibriSpeech ASR
This is a variant of the [LibriSpeech ASR](https://huggingface.co/datasets/librispeech_asr) dataset, augmented to return the pseudo-labelled Whisper
Transcription... |
paniniDot/sci_lay | 2023-09-05T16:39:49.000Z | [
"task_categories:summarization",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"license:cc-by-4.0",
"medical",
"region:us"
] | paniniDot | SCILAY comprises 43,790 instances, each representing a scientific article in the biomedical domain.
Each instance in the dataset includes the following components:
- plain_text: Containing a plain language summary of the scientific article. This section is written in a simple and accessible language, and is intend... | null | 0 | 166 | ---
license: cc-by-4.0
task_categories:
- summarization
tags:
- medical
pretty_name: Sci Lay - Biomedic Articles Lay Summarization Dataset
size_categories:
- 10K<n<100K
- 1K<n<10K
source_datasets:
- original
dataset_info:
- config_name: all
features:
- name: doi
dtype: string
- name: pmcid
dtype: string
... | |
amitness/maltese-news-nli-sports | 2023-09-10T18:27:51.000Z | [
"region:us"
] | amitness | null | null | null | 0 | 166 | ---
dataset_info:
features:
- name: title
dtype: string
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': not_entailment
'1': entailment
splits:
- name: train
num_bytes: 564856
num_examples: 409
- name: validation
num_bytes: ... |
jakartaresearch/semeval-absa | 2022-08-14T05:38:21.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"aspect-based-sentiment-analysis",
"seme... | jakartaresearch | This dataset is built as a playground for aspect-based sentiment analysis. | null | null | 1 | 165 | ---
annotations_creators:
- found
language:
- en
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'SemEval 2015: Aspect-based Sentiement Analysis'
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- aspect-based-sentiment-analysis
- semeval
- semeval2015
task_categ... |
clarin-knext/trec-covid-pl | 2023-06-07T08:12:18.000Z | [
"language:pl",
"arxiv:2305.19840",
"region:us"
] | clarin-knext | null | null | null | 0 | 165 | ---
language:
- pl
---
Part of **BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language**.
Link to arxiv: https://arxiv.org/pdf/2305.19840.pdf
Contact: konrad.wojtasik@pwr.edu.pl |
jxie/country211 | 2023-08-13T19:11:22.000Z | [
"region:us"
] | jxie | null | null | null | 0 | 165 | ---
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: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': AD
... |
DDSC/dagw_reddit_filtered_v1.0.0 | 2022-11-06T15:30:56.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:DDSC/partial-danish-gigaword-no-twitter",
"source_datasets:DDSC/reddit-da",
"language:da... | DDSC | null | null | null | 1 | 164 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- DDSC/partial-danish-gigaword-no-twitter
- DDSC/reddit-da
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_na... |
bitext/Bitext-customer-support-llm-chatbot-training-dataset | 2023-09-19T23:48:25.000Z | [
"task_categories:question-answering",
"task_categories:table-question-answering",
"size_categories:10K<n<100K",
"language:en",
"license:cdla-sharing-1.0",
"question-answering",
"llm",
"chatbot",
"costumer-support",
"conversional-ai",
"generative-ai",
"natural-language-understanding",
"fine-t... | bitext | null | null | null | 4 | 163 | ---
license: cdla-sharing-1.0
task_categories:
- question-answering
- table-question-answering
language:
- en
tags:
- question-answering
- llm
- chatbot
- costumer-support
- conversional-ai
- generative-ai
- natural-language-understanding
- fine-tuning
- Retail
pretty_name: >-
Bitext - Customer Service Tagged Trainin... |
skadewdl3/recipe-nlg-llama2 | 2023-10-04T07:40:19.000Z | [
"region:us"
] | skadewdl3 | null | null | null | 0 | 163 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: title
dtype: string
- name: ingredients
dtype: string
- name: directions
dtype: string
- name: link
dtype: string
- name: source
dtype: string
- name: NER
dtype: string
- name: prompt
dtype: string
splits:
... |
vblagoje/lfqa_support_docs | 2021-12-30T10:28:31.000Z | [
"region:us"
] | vblagoje | null | null | null | 6 | 162 | Support documents for building https://huggingface.co/vblagoje/bart_lfqa model
|
c-s-ale/alpaca-gpt4-data-zh | 2023-05-03T17:56:55.000Z | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:zh",
"license:cc-by-4.0",
"gpt",
"alpaca",
"fine-tune",
"instruct-tune",
"instruction",
"arxiv:2304.03277",
"region:us"
] | c-s-ale | null | null | null | 20 | 162 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 32150579
num_examples: 48818
download_size: 35100559
dataset_size: 32150579
license: cc-by-4.0
language:
- zh
pretty_name: Instructi... |
sirius0707/imagenet_10 | 2023-07-23T02:29:00.000Z | [
"task_categories:image-classification",
"language:en",
"region:us"
] | sirius0707 | null | null | null | 0 | 162 | ---
task_categories:
- image-classification
language:
- en
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': goldfish
'1': scuba diver
'2': seashore
'3': green lizard
'4': s... |
tmu_gfm_dataset | 2022-11-03T16:30:48.000Z | [
"task_categories:text2text-generation",
"annotations_creators:crowdsourced",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"grammatical-error-correction",
"region:us"
] | null | A dataset for GEC metrics with manual evaluations of grammaticality, fluency, and meaning preservation for system outputs. More detail about the creation of the dataset can be found in Yoshimura et al. (2020). | @inproceedings{yoshimura-etal-2020-reference,
title = "{SOME}: Reference-less Sub-Metrics Optimized for Manual Evaluations of Grammatical Error Correction",
author = "Yoshimura, Ryoma and
Kaneko, Masahiro and
Kajiwara, Tomoyuki and
Komachi, Mamoru",
booktitle = "Proceedings of the 28th ... | null | 2 | 161 | ---
annotations_creators:
- crowdsourced
language_creators:
- machine-generated
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
paperswithcode_id: null
pretty_name: TMU-GFM-Dataset
tags:
- gramm... |
ccdv/arxiv-classification | 2022-10-22T09:23:50.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:topic-classification",
"size_categories:10K<n<100K",
"language:en",
"long context",
"region:us"
] | ccdv | Arxiv Classification Dataset: a classification of Arxiv Papers (11 classes).
It contains 11 slightly unbalanced classes, 33k Arxiv Papers divided into 3 splits: train (23k), val (5k) and test (5k).
Copied from "Long Document Classification From Local Word Glimpses via Recurrent Attention Learning" by JUN HE LIQUN WAN... | null | null | 9 | 161 | ---
language: en
task_categories:
- text-classification
tags:
- long context
task_ids:
- multi-class-classification
- topic-classification
size_categories: 10K<n<100K
---
**Arxiv Classification: a classification of Arxiv Papers (11 classes).**
This dataset is intended for long context classification (documents have ... |
rahular/itihasa | 2022-10-24T18:06:01.000Z | [
"task_categories:text2text-generation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:unknown",
"source_datasets:original",
"language:sa",
"language:en",
"license:apache-2.0",
"conditional-text-generation",
"region:... | rahular | A Sanskrit-English machine translation dataset. | @inproceedings{aralikatte-etal-2021-itihasa,
title = "Itihasa: A large-scale corpus for {S}anskrit to {E}nglish translation",
author = "Aralikatte, Rahul and
de Lhoneux, Miryam and
Kunchukuttan, Anoop and
S{\o}gaard, Anders",
booktitle = "Proceedings of the 8th Workshop on Asian Transla... | null | 3 | 161 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- sa
- en
license:
- apache-2.0
multilinguality:
- translation
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
pretty_name: Itihasa
metrics:
- bleu
- sacrebleu
- rouge... |
jonaskoenig/Questions-vs-Statements-Classification | 2022-07-11T15:36:35.000Z | [
"region:us"
] | jonaskoenig | null | null | null | 2 | 161 | [Needs More Information]
# Dataset Card for Questions-vs-Statements-Classification
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
... |
joelniklaus/legal_case_document_summarization | 2023-02-02T23:52:54.000Z | [
"region:us"
] | joelniklaus | null | null | null | 7 | 161 | # Dataset Card for LegalCaseDocumentSummarization
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structu... |
RicardoRei/wmt-mqm-human-evaluation | 2023-02-16T18:29:11.000Z | [
"size_categories:100K<n<1M",
"language:en",
"language:de",
"language:ru",
"language:zh",
"license:apache-2.0",
"mt-evaluation",
"WMT",
"region:us"
] | RicardoRei | null | null | null | 0 | 161 | ---
license: apache-2.0
language:
- en
- de
- ru
- zh
tags:
- mt-evaluation
- WMT
size_categories:
- 100K<n<1M
---
# Dataset Summary
This dataset contains all MQM human annotations from previous [WMT Metrics shared tasks](https://wmt-metrics-task.github.io/) and the MQM annotations from [Experts, Errors, and Context]... |
RIW/small-coco-wm_50 | 2023-03-11T23:13:04.000Z | [
"region:us"
] | RIW | null | null | null | 0 | 161 | ---
dataset_info:
features:
- name: image
dtype: image
- name: caption
dtype: string
- name: url
dtype: string
- name: key
dtype: string
- name: status
dtype: string
- name: error_message
dtype: 'null'
- name: width
dtype: int64
- name: height
dtype: int64
- name: ori... |
ruanchaves/porsimplessent | 2023-04-12T15:57:26.000Z | [
"size_categories:1K<n<10K",
"region:us"
] | ruanchaves | null | 1 | 161 | ---
size_categories:
- 1K<n<10K
---
# Dataset Card for PorSimplesSent
## Dataset Description
- **Repository:** [sidleal/porsimplessent](https://github.com/sidleal/porsimplessent)
- **Paper:** [A Nontrivial Sentence Corpus for the Task of Sentence Readability Assessment in Portuguese](https://aclanthology.org/C18-103... | ||
IlyaGusev/oasst1_ru_main_branch | 2023-09-15T20:58:01.000Z | [
"task_categories:conversational",
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:ru",
"license:apache-2.0",
"region:us"
] | IlyaGusev | null | null | null | 3 | 161 | ---
language:
- ru
license: apache-2.0
size_categories:
- 1K<n<10K
task_categories:
- conversational
- text-generation
dataset_info:
features:
- name: messages
sequence:
- name: role
dtype: string
- name: content
dtype: string
- name: id
dtype: string
splits:
- name: train
num_... |
ArtifactAI/arxiv-cs-ml-instruct-tune-50k | 2023-06-21T13:45:31.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc0-1.0",
"doi:10.57967/hf/0800",
"region:us"... | ArtifactAI | null | null | null | 3 | 161 | ---
annotations_creators:
- no-annotation
language:
- en
license:
- cc0-1.0
multilinguality:
- monolingual
pretty_name: arxiv-cs-ml-instruct-tune-50k
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: arx... |
loremipsum3658/and | 2023-08-24T21:29:56.000Z | [
"region:us"
] | loremipsum3658 | null | null | null | 0 | 161 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: nup
dtype: string
- name: data
dtype: string
- name: titulo
dtype: string
- name: andame... |
mattymchen/lrs3-test | 2023-09-05T10:37:16.000Z | [
"region:us"
] | mattymchen | null | null | null | 0 | 161 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: idx
dtype: int64
- name: audio
sequence: int16
- name: video
sequence:
sequence:
sequence: uint8
- name: label
dtype: string
splits:
- name: train
num... |
result-kand2-sdxl-wuerst-karlo/023acaec | 2023-10-03T22:23:40.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 161 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 233
num_examples: 10
download_size: 1392
dataset_size: 233
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "023acae... |
nielsr/rvlcdip-demo | 2022-03-08T12:11:13.000Z | [
"region:us"
] | nielsr | null | null | null | 0 | 160 | Entry not found |
Francesco/peanuts-sd4kf | 2023-03-30T09:30:58.000Z | [
"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 | null | 0 | 160 | ---
dataset_info:
features:
- name: image_id
dtype: int64
- name: image
dtype: image
- name: width
dtype: int32
- name: height
dtype: int32
- name: objects
sequence:
- name: id
dtype: int64
- name: area
dtype: int64
- name: bbox
sequence: float32
lengt... |
CM/codexglue_code2text_go | 2023-04-22T01:51:07.000Z | [
"region:us"
] | CM | null | null | null | 0 | 160 | ---
dataset_info:
features:
- name: id
dtype: int32
- name: repo
dtype: string
- name: path
dtype: string
- name: func_name
dtype: string
- name: original_string
dtype: string
- name: language
dtype: string
- name: code
dtype: string
- name: code_tokens
sequence: string... |
teknium/GPTeacher-General-Instruct | 2023-04-29T23:27:46.000Z | [
"license:mit",
"region:us"
] | teknium | null | null | null | 28 | 160 | ---
license: mit
---
GPTeacher General-Instruct dataset is GPT-4 Generated self-instruct dataset.
There are multiple versions, with more or less similarity reductions.
The dedupe only dataset contains 18194 entries, with less the more similarity is reduced.
Format is identical to alpaca's, with a varyiable mix of I... |
DISCOX/DISCO-10K-random | 2023-06-20T14:25:17.000Z | [
"license:cc-by-4.0",
"region:us"
] | DISCOX | null | null | null | 1 | 160 | ---
license: cc-by-4.0
dataset_info:
features:
- name: video_url_youtube
dtype: string
- name: video_title_youtube
dtype: string
- name: track_name_spotify
dtype: string
- name: video_duration_youtube_sec
dtype: float64
- name: preview_url_spotify
dtype: string
- name: video_view_count... |
FudanSELab/ClassEval | 2023-09-04T06:35:53.000Z | [
"task_categories:text2text-generation",
"size_categories:n<1K",
"language:en",
"license:mit",
"code-generation",
"arxiv:2308.01861",
"region:us"
] | FudanSELab | FudanSELab ClassEval | @misc{du2023classeval,
title={ClassEval: A Manually-Crafted Benchmark for Evaluating LLMs on Class-level Code Generation},
author={Xueying Du and Mingwei Liu and Kaixin Wang and Hanlin Wang and Junwei Liu and Yixuan Chen and Jiayi Feng and Chaofeng Sha and Xin Peng and Yiling Lou},
year={2023},
... | null | 1 | 160 | ---
license: mit
language:
- en
size_categories:
- n<1K
tags:
- code-generation
task_categories:
- text2text-generation
pretty_name: ClassEval
configs:
- config_name: default
data_files:
- split: test
path: "ClassEval_data.json"
---
# Dataset Card for FudanSELab ClassEval
## Dataset Description
- **Repos... |
Rowan/hellaswag | 2023-09-28T14:49:00.000Z | [
"language:en",
"arxiv:1905.07830",
"region:us"
] | Rowan | HellaSwag: Can a Machine Really Finish Your Sentence? is a new dataset for commonsense NLI. A paper was published at ACL2019. | @inproceedings{zellers2019hellaswag,
title={HellaSwag: Can a Machine Really Finish Your Sentence?},
author={Zellers, Rowan and Holtzman, Ari and Bisk, Yonatan and Farhadi, Ali and Choi, Yejin},
booktitle ={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
year={20... | null | 29 | 159 | ---
language:
- en
paperswithcode_id: hellaswag
pretty_name: HellaSwag
dataset_info:
features:
- name: ind
dtype: int32
- name: activity_label
dtype: string
- name: ctx_a
dtype: string
- name: ctx_b
dtype: string
- name: ctx
dtype: string
- name: endings
sequence: string
- name: ... |
nli_tr | 2023-06-01T14:59:47.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"task_ids:text-scoring",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:... | null | \
The Natural Language Inference in Turkish (NLI-TR) is a set of two large scale datasets that were obtained by translating the foundational NLI corpora (SNLI and MNLI) using Amazon Translate. | \
@inproceedings{budur-etal-2020-data,
title = "Data and Representation for Turkish Natural Language Inference",
author = "Budur, Emrah and
\"{O}zçelik, Rıza and
G\"{u}ng\"{o}r, Tunga",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMN... | null | 5 | 159 | ---
annotations_creators:
- expert-generated
language_creators:
- machine-generated
language:
- tr
license:
- cc-by-3.0
- cc-by-4.0
- cc-by-sa-3.0
- mit
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- extended|snli
- extended|multi_nli
task_categories:
- text-classification
task_i... |
distil-whisper/gigaspeech-l | 2023-09-25T10:28:52.000Z | [
"task_categories:automatic-speech-recognition",
"language:en",
"license:other",
"region:us"
] | distil-whisper | GigaSpeech is an evolving, multi-domain English speech recognition corpus with 10,000 hours of high quality
labeled audio suitable for supervised training, and 40,000 hours of total audio suitable for semi-supervised
and unsupervised training. Around 40,000 hours of transcribed audio is first collected from audiobooks,... | @article{DBLP:journals/corr/abs-2106-06909,
author = {Guoguo Chen and
Shuzhou Chai and
Guanbo Wang and
Jiayu Du and
Wei{-}Qiang Zhang and
Chao Weng and
Dan Su and
Daniel Povey and
Jan Trmal and
... | null | 0 | 159 | ---
license: other
task_categories:
- automatic-speech-recognition
language:
- en
extra_gated_prompt: |-
SpeechColab does not own the copyright of the audio files. For researchers and educators who wish to use the audio files for non-commercial research and/or educational purposes, we can provide access through the... |
fedyanin/feud | 2023-07-25T12:01:51.000Z | [
"license:cc",
"region:us"
] | fedyanin | null | null | null | 0 | 159 | ---
license: cc
---
# Feud dataset
Dataset of question and answers that resemble family feud tv show style. There multiple possible answers for each question. Dataset is aimed to benhmark a balance between diversity and correctness of a language model |
ds4sd/FinTabNet_OTSL | 2023-08-31T16:01:59.000Z | [
"task_categories:object-detection",
"task_categories:table-to-text",
"size_categories:10K<n<100K",
"license:other",
"table-structure-recognition",
"table-understanding",
"PDF",
"arxiv:2305.03393",
"region:us"
] | ds4sd | null | null | null | 1 | 159 | ---
license: other
pretty_name: FinTabNet-OTSL
size_categories:
- 10K<n<100K
tags:
- table-structure-recognition
- table-understanding
- PDF
task_categories:
- object-detection
- table-to-text
---
# Dataset Card for FinTabNet_OTSL
## Dataset Description
- **Homepage:** https://ds4sd.github.io
- **Paper:** https://arx... |
eduagarcia/generic_conll | 2023-08-29T02:59:05.000Z | [
"region:us"
] | eduagarcia | null | null | null | 0 | 159 | Entry not found |
hrithikpiyush/acl-arc | 2022-04-26T11:40:41.000Z | [
"license:apache-2.0",
"region:us"
] | hrithikpiyush | null | null | null | 0 | 158 | ---
license: apache-2.0
---
|
jonathanli/law-stack-exchange | 2023-02-23T16:37:19.000Z | [
"task_categories:text-classification",
"language:en",
"stackexchange",
"law",
"region:us"
] | jonathanli | null | null | null | 5 | 158 | ---
task_categories:
- text-classification
language:
- en
tags:
- stackexchange
- law
pretty_name: Law Stack Exchange
---
# Dataset Card for Law Stack Exchange Dataset
## Dataset Description
- **Paper: [Parameter-Efficient Legal Domain Adaptation](https://aclanthology.org/2022.nllp-1.10/)**
- **Point of Contact: jx... |
jbpark0614/speechocean762 | 2022-10-24T09:43:54.000Z | [
"region:us"
] | jbpark0614 | null | null | null | 3 | 158 | ---
dataset_info:
features:
- name: index
dtype: int64
- name: speaker_id_str
dtype: int64
- name: speaker_id
dtype: int64
- name: question_id
dtype: int64
- name: total_score
dtype: int64
- name: accuracy
dtype: int64
- name: completeness
dtype: float64
- name: fluency
... |
jonathanli/hyperpartisan-longformer-split | 2022-12-31T16:08:16.000Z | [
"arxiv:2004.05150",
"region:us"
] | jonathanli | null | null | null | 0 | 158 | # Hyperpartisan news detection
This dataset has the hyperpartisan new dataset, processed and split exactly as it was for [longformer](https://arxiv.org/abs/2004.05150) experiments.
Code for processing was found at [here](https://github.com/allenai/longformer/blob/master/scripts/hp_preprocess.py).
|
Deysi/spam-detection-dataset | 2023-04-15T17:42:24.000Z | [
"task_categories:text-classification",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"region:us"
] | Deysi | null | null | null | 5 | 158 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 3161821
num_examples: 8175
- name: test
num_bytes: 1094757
num_examples: 2725
download_size: 2578551
dataset_size: 4256578
license: apache-2.0
task_categories:
- te... |
semaj83/ioqm | 2023-10-08T01:13:18.000Z | [
"license:mit",
"region:us"
] | semaj83 | null | null | null | 0 | 158 | ---
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... |
result-kand2-sdxl-wuerst-karlo/dbd855c1 | 2023-10-04T01:53:22.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 158 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 233
num_examples: 10
download_size: 1405
dataset_size: 233
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "dbd855c... |
leslyarun/c4_200m_gec_train100k_test25k | 2022-10-26T07:59:31.000Z | [
"task_categories:text-generation",
"source_datasets:allenai/c4",
"language:en",
"grammatical-error-correction",
"region:us"
] | leslyarun | null | null | null | 2 | 157 | ---
language:
- en
source_datasets:
- allenai/c4
task_categories:
- text-generation
pretty_name: C4 200M Grammatical Error Correction Dataset
tags:
- grammatical-error-correction
---
# C4 200M
# Dataset Summary
C4 200M Sample Dataset adopted from https://huggingface.co/datasets/liweili/c4_200m
C4_200m is a collecti... |
gokuls/wiki_book_corpus_complete_processed_bert_dataset | 2023-02-25T19:22:14.000Z | [
"region:us"
] | gokuls | null | null | null | 0 | 157 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: token_type_ids
sequence: int8
- name: attention_mask
sequence: int8
- name: special_tokens_mask
sequence: int8
splits:
- name: train
num_bytes: 22201610400.0
num_examples: 6167114
download_size: 2763194793
da... |
mhhmm/leetcode-solutions-python | 2023-04-27T06:40:41.000Z | [
"license:lgpl",
"region:us"
] | mhhmm | null | null | null | 14 | 157 | ---
license: lgpl
---
All credits belong to https://www.kaggle.com/datasets/erichartford/leetcode-solutions
I collected only python solutions:
```
id: <number>
code_with_data:
<
# Slug
# Title
# Difficulty
# Content
Code Answer in Python
# Explanation
>
code_only: < Code Answer in Python >
code_with_probl... |
Fsoft-AIC/the-vault-function | 2023-07-04T02:33:36.000Z | [
"task_categories:text-generation",
"multilinguality:multiprogramming languages",
"language:code",
"language:en",
"license:mit",
"arxiv:2305.06156",
"region:us"
] | Fsoft-AIC | The Vault is a multilingual code-text dataset with over 40 million pairs covering 10 popular programming languages.
It is the largest corpus containing parallel code-text data. By building upon The Stack, a massive raw code sample collection,
the Vault offers a comprehensive and clean resource for advancing research ... | @article{manh2023vault,
title={The Vault: A Comprehensive Multilingual Dataset for Advancing Code Understanding and Generation},
author={Manh, Dung Nguyen and Hai, Nam Le and Dau, Anh TV and Nguyen, Anh Minh and Nghiem, Khanh and Guo, Jin and Bui, Nghi DQ},
journal={arXiv preprint arXiv:2305.06156},
year={2023}... | null | 8 | 157 | ---
language:
- code
- en
multilinguality:
- multiprogramming languages
task_categories:
- text-generation
license: mit
dataset_info:
features:
- name: identifier
dtype: string
- name: return_type
dtype: string
- name: repo
dtype: string
- name: path
dtype: string
- name: language
dtype:... |
open-llm-leaderboard/details | 2023-08-25T09:32:19.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 157 | Entry not found |
tyzhu/squad_id_train_10_eval_10 | 2023-09-19T02:18:57.000Z | [
"region:us"
] | tyzhu | null | null | null | 0 | 157 | ---
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: context_id
dtype: string
... |
tomekkorbak/detoxify-pile-chunk3-100000-150000 | 2022-10-06T02:58:25.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 156 | Entry not found |
HuggingFaceH4/self-instruct-seed | 2023-01-31T22:37:02.000Z | [
"task_categories:conversational",
"size_categories:n<1K",
"language:en",
"license:apache-2.0",
"arxiv:2212.10560",
"region:us"
] | HuggingFaceH4 | null | null | null | 14 | 156 | ---
license: apache-2.0
task_categories:
- conversational
language:
- en
size_categories:
- n<1K
---
Manually created seed dataset used in bootstrapping in the Self-instruct paper https://arxiv.org/abs/2212.10560. This is part of the instruction fine-tuning datasets. |
NegarMov/DHI_test | 2023-09-21T08:05:32.000Z | [
"region:us"
] | NegarMov | null | null | null | 0 | 156 | Entry not found |
crd3 | 2022-11-18T19:47:20.000Z | [
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:... | null | Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset.
Critical Role is an unscripted, live-streamed show where a fixed group of people play Dungeons and Dragons, an open-ended role-playing game.
The dataset is collected from 159 Critical Role episodes transcribed to text dialogues, consisting of 398... | @inproceedings{
title = {Storytelling with Dialogue: A Critical Role Dungeons and Dragons Dataset},
author = {Rameshkumar, Revanth and Bailey, Peter},
year = {2020},
publisher = {Association for Computational Linguistics},
conference = {ACL}
} | null | 12 | 155 | ---
pretty_name: CRD3 (Critical Role Dungeons and Dragons Dataset)
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- summarization
- text-generation
- fill-mask
task_ids:
- dialogue... |
fmplaza/EmoEvent | 2023-03-27T08:19:58.000Z | [
"language:en",
"language:es",
"license:apache-2.0",
"region:us"
] | fmplaza | EmoEvent is a multilingual emotion dataset of tweets based on different events that took place in April 2019.
Three annotators labeled the tweets following the six Ekman’s basic emotion model (anger, fear, sadness, joy, disgust, surprise) plus the “neutral or other emotions” category. | @inproceedings{plaza-del-arco-etal-2020-emoevent,
title = "{{E}mo{E}vent: A Multilingual Emotion Corpus based on different Events}",
author = "{Plaza-del-Arco}, {Flor Miriam} and Strapparava, Carlo and {Ure{~n}a-L{\’o}pez}, L. Alfonso and {Mart{\’i}n-Valdivia}, M. Teresa",
booktitle = "Proceedings of the 12th Langua... | null | 6 | 155 | ---
license: apache-2.0
language:
- en
- es
---
# Dataset Card for Emoevent
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#lan... |
atokforps/chunk-t1 | 2023-03-09T20:48:30.000Z | [
"region:us"
] | atokforps | null | null | null | 1 | 155 | Entry not found |
Muennighoff/python-bugs | 2023-03-22T07:46:03.000Z | [
"region:us"
] | Muennighoff | null | null | null | 2 | 155 | Entry not found |
Kyle1668/AG-Tweets | 2023-08-09T22:22:37.000Z | [
"region:us"
] | Kyle1668 | null | null | null | 0 | 155 | ---
pretty_name: AG News Tweets
---
\subsection{Motivation}
AG News is a four-way topic classification task introduced in \cite{Zhang2015CharacterlevelCN}. In this setup, a task model must classify whether a given news article is about world events (\textbf{\textit{World}}), sports and athletics (\textbf{\textit{Spor... |
yentinglin/ntu_adl_recitation | 2023-09-21T02:18:47.000Z | [
"task_categories:text-classification",
"language:en",
"license:apache-2.0",
"region:us"
] | yentinglin | null | null | null | 0 | 155 | ---
license: apache-2.0
task_categories:
- text-classification
language:
- en
--- |
shubhamagarwal92/rw_2308_filtered | 2023-09-21T20:48:20.000Z | [
"region:us"
] | shubhamagarwal92 | null | null | null | 0 | 155 | ---
dataset_info:
features:
- name: aid
dtype: string
- name: mid
dtype: string
- name: abstract
dtype: string
- name: corpusid
dtype: int64
- name: text_except_rw
dtype: string
- name: title
dtype: string
- name: related_work
dtype: string
- name: original_related_work
... |
HumanCompatibleAI/ppo-seals-Ant-v1 | 2023-09-27T06:56:10.000Z | [
"region:us"
] | HumanCompatibleAI | null | null | null | 0 | 155 | ---
dataset_info:
features:
- name: obs
sequence:
sequence: float64
- name: acts
sequence:
sequence: float32
- name: infos
sequence: string
- name: terminal
dtype: bool
- name: rews
sequence: float32
splits:
- name: train
num_bytes: 141011280
num_examples: 104
d... |
maritaca-ai/sst2_pt | 2023-02-10T13:40:00.000Z | [
"region:us"
] | maritaca-ai | The Stanford Sentiment Treebank consists of sentences from movie reviews and
human annotations of their sentiment. The task is to predict the sentiment of a
given sentence. We use the two-way (positive/negative) class split, and use only
sentence-level labels. | @inproceedings{socher2013recursive,
title={Recursive deep models for semantic compositionality over a sentiment treebank},
author={Socher, Richard and Perelygin, Alex and Wu, Jean and Chuang, Jason and Manning, Christopher D and Ng, Andrew and Potts, Christopher},
booktitle={Proceedings of the 2013 conference on ... | null | 1 | 154 | Entry not found |
nbroad/mediasum | 2022-10-25T10:40:11.000Z | [
"task_categories:summarization",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"language:en",
"license:cc-by-nc-sa-4.0",
"arxiv:2103.06410",
"region:us"
] | nbroad | This large-scale media interview dataset contains 463.6K transcripts with abstractive summaries,
collected from interview transcripts and overview / topic descriptions from NPR and CNN. | @article{zhu2021mediasum,
title={MediaSum: A Large-scale Media Interview Dataset for Dialogue Summarization},
author={Zhu, Chenguang and Liu, Yang and Mei, Jie and Zeng, Michael},
journal={arXiv preprint arXiv:2103.06410},
year={2021}
} | null | 1 | 153 | ---
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
task_categories:
- summarization
---
# MediaSum
## Description
This large-scale media interview dataset contains 463.6K transcripts with abstractive summaries,
collected from interview transcripts and overview / t... |
Ammok/apple_stock_price_from_1980-2021 | 2023-09-09T10:57:38.000Z | [
"task_categories:time-series-forecasting",
"task_categories:tabular-regression",
"language:en",
"license:odc-by",
"region:us"
] | Ammok | null | null | null | 0 | 153 | ---
license: odc-by
task_categories:
- time-series-forecasting
- tabular-regression
language:
- en
pretty_name: apple stock price from 1980-2021
--- |
atmallen/mmlu_binary | 2023-09-19T05:12:16.000Z | [
"region:us"
] | atmallen | null | null | null | 0 | 153 | ---
configs:
- config_name: default
data_files:
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: question
dtype: string
- name: subject
dtype: string
- name: choices
sequence: string
- name: answer
dtype: int32
- name: ... |
gfissore/arxiv-abstracts-2021 | 2022-10-27T17:08:00.000Z | [
"task_categories:summarization",
"task_categories:text-retrieval",
"task_categories:text2text-generation",
"task_ids:explanation-generation",
"task_ids:text-simplification",
"task_ids:document-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"annotations_creators:... | gfissore | null | null | null | 14 | 152 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc0-1.0
multilinguality:
- monolingual
pretty_name: arxiv-abstracts-2021
size_categories:
- 1M<n<10M
source_datasets: []
task_categories:
- summarization
- text-retrieval
- text2text-generation
task_ids:
- explanat... |
BeIR/webis-touche2020-qrels | 2022-10-23T06:07:03.000Z | [
"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 | null | 0 | 152 | ---
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:
... |
forta/malicious-smart-contract-dataset | 2023-01-10T22:03:23.000Z | [
"task_categories:token-classification",
"size_categories:100K<n<1M",
"license:mit",
"smart contract",
"ethereum",
"blockchain",
"security",
"region:us"
] | forta | null | null | null | 9 | 152 | ---
license: mit
task_categories:
- token-classification
tags:
- smart contract
- ethereum
- blockchain
- security
pretty_name: Malicious Smart Contract Classification Dataset
size_categories:
- 100K<n<1M
---
# Malicious Smart Contract Classification Dataset
This dataset includes malicious and benign smart contracts ... |
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