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 |
|---|---|---|---|---|---|---|---|---|---|
totally-not-an-llm/EverythingLM-data-V3 | 2023-09-11T02:54:38.000Z | [
"license:mit",
"region:us"
] | totally-not-an-llm | null | null | null | 12 | 294 | ---
license: mit
---
# EverythingLM V3 Dataset
**EverythingLM V3** is a diverse instruct dataset consisting of roughly 1.1k of sysprompt-user-assistant triads. These were generated using principles from both evol-instruct and Orca. The dataset encompasses a wide array of topics and interactions.
### Diferences from ... |
clarin-pl/kpwr-ner | 2023-01-30T22:54:02.000Z | [
"task_categories:other",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:18K",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pl",
"license:cc-by-3.0",
"structure-predict... | clarin-pl | KPWR-NER tagging dataset. | null | null | 6 | 293 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pl
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- 18K
- 10K<n<100K
source_datasets:
- original
task_categories:
- other
task_ids:
- named-entity-recognition
pretty_name: KPWr-NER
tags:
- structure-prediction
---
... |
MU-NLPC/Calc-gsm8k | 2023-10-07T16:40:00.000Z | [
"task_categories:text-generation",
"task_categories:question-answering",
"size_categories:1K<n<10K",
"language:en",
"license:mit",
"arxiv:2110.14168",
"arxiv:2305.15017",
"region:us"
] | MU-NLPC | null | null | null | 1 | 293 | ---
license: mit
task_categories:
- text-generation
- question-answering
language:
- en
size_categories:
- 1K<n<10K
---
# Dataset Card for "Calc-gsm8k"
## Summary
This dataset is an instance of gsm8k dataset, converted to a simple html-like language that can be easily parsed (e.g. by BeautifulSoup). The data contain... |
result-kand2-sdxl-wuerst-karlo/80bca589 | 2023-09-28T22:53:52.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 293 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 242
num_examples: 10
download_size: 1409
dataset_size: 242
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "80bca58... |
result-kand2-sdxl-wuerst-karlo/dda30fff | 2023-09-28T22:55:08.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 293 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 164
num_examples: 10
download_size: 1316
dataset_size: 164
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "dda30ff... |
result-kand2-sdxl-wuerst-karlo/bfc3e463 | 2023-09-28T22:55:10.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 293 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 164
num_examples: 10
download_size: 1316
dataset_size: 164
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "bfc3e46... |
wmt15 | 2023-04-05T13:43:50.000Z | [
"task_categories:translation",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:translation",
"size_categories:10M<n<100M",
"source_datasets:extended|europarl_bilingual",
"source_datasets:extended|giga_fren",
"source_datasets:extended|news_commentary",
"source_datase... | null | null | @InProceedings{bojar-EtAl:2015:WMT,
author = {Bojar, Ond\v{r}ej and Chatterjee, Rajen and Federmann, Christian and Haddow, Barry and Huck, Matthias and Hokamp, Chris and Koehn, Philipp and Logacheva, Varvara and Monz, Christof and Negri, Matteo and Post, Matt and Scarton, Carolina and Speci... | null | 2 | 289 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- cs
- de
- en
- fi
- fr
- ru
license:
- unknown
multilinguality:
- translation
size_categories:
- 10M<n<100M
source_datasets:
- extended|europarl_bilingual
- extended|giga_fren
- extended|news_commentary
- extended|un_multi
task_categories:... |
AIML-TUDA/i2p | 2023-05-25T08:04:07.000Z | [
"license:mit",
"arxiv:2211.05105",
"region:us"
] | AIML-TUDA | null | null | null | 3 | 289 | ---
license: mit
---
# Inaproppriate Image Prompts (I2P)
The I2P benchmark contains real user prompts for generative text2image prompts that are unproportionately likely to produce <i>inappropriate</i> images.
I2P was introduced in the 2023 CVPR paper [Safe Latent Diffusion: Mitigating Inappropriate Degeneration in D... |
akariasai/PopQA | 2022-12-22T01:01:20.000Z | [
"region:us"
] | akariasai | null | null | null | 3 | 289 | # Dataset Card for PopQA
## Dataset Summary
PopQA is a large-scale open-domain question answering (QA) dataset, consisting of 14k entity-centric QA pairs. Each question is created by converting a knowledge tuple retrieved from Wikidata using a template. Each question come with the original `subject_entitiey`, `objec... |
lksy/ru_instruct_gpt4 | 2023-06-02T16:56:03.000Z | [
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"language:ru",
"license:cc-by-4.0",
"chat",
"region:us"
] | lksy | null | null | null | 12 | 289 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
- name: full_output
dtype: string
splits:
- name: train
num_bytes: 22424451
num_examples: 15056
download_size: 23276814
dataset_size: 22424451
license: cc-by-4... |
yxchar/amazon-tlm | 2021-11-04T22:22:29.000Z | [
"region:us"
] | yxchar | null | null | null | 0 | 288 | Entry not found |
craigslist_bargains | 2022-11-18T19:47:08.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"arxi... | null | We study negotiation dialogues where two agents, a buyer and a seller,
negotiate over the price of an time for sale. We collected a dataset of more
than 6K negotiation dialogues over multiple categories of products scraped from Craigslist.
Our goal is to develop an agent that negotiates with humans through such convers... | @misc{he2018decoupling,
title={Decoupling Strategy and Generation in Negotiation Dialogues},
author={He He and Derek Chen and Anusha Balakrishnan and Percy Liang},
year={2018},
eprint={1808.09637},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | null | 7 | 287 | ---
annotations_creators:
- machine-generated
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- dialogue-modeling
paperswithcode_id: craigslistbargains
pret... |
open-source-metrics/issues | 2023-09-26T13:43:16.000Z | [
"region:us"
] | open-source-metrics | null | null | null | 0 | 287 | ---
dataset_info:
features:
- name: dates
dtype: string
- name: type
struct:
- name: authorAssociation
dtype: string
- name: comment
dtype: bool
- name: issue
dtype: bool
splits:
- name: candle
num_bytes: 69320
num_examples: 1815
- name: text_generation_inferenc... |
silk-road/alpaca-data-gpt4-chinese | 2023-05-23T05:33:21.000Z | [
"task_categories:text-generation",
"size_categories:10K<n<100K",
"language:zh",
"language:en",
"license:apache-2.0",
"gpt",
"alpaca",
"fine-tune",
"region:us"
] | silk-road | null | null | null | 35 | 287 | ---
license: apache-2.0
task_categories:
- text-generation
language:
- zh
- en
tags:
- gpt
- alpaca
- fine-tune
pretty_name: Alpaca-Data-GPT4-Chinese
size_categories:
- 10K<n<100K
--- |
facat/sci-llm-60k | 2023-09-14T02:18:33.000Z | [
"region:us"
] | facat | null | null | null | 0 | 287 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: prompt
dtype: string
- name: context
dtype: string
- name: chosen
dtype: string
- name: A
dtype: string
- name: B
dtype: string
... |
uit-nlp/vietnamese_students_feedback | 2022-10-13T15:39:37.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:topic-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:vi",
"license:unknown",
... | uit-nlp | Students’ feedback is a vital resource for the interdisciplinary research involving the combining of two different
research fields between sentiment analysis and education.
Vietnamese Students’ Feedback Corpus (UIT-VSFC) is the resource consists of over 16,000 sentences which are
human-annotated with two different tas... | @InProceedings{8573337,
author={Nguyen, Kiet Van and Nguyen, Vu Duc and Nguyen, Phu X. V. and Truong, Tham T. H. and Nguyen, Ngan Luu-Thuy},
booktitle={2018 10th International Conference on Knowledge and Systems Engineering (KSE)},
title={UIT-VSFC: Vietnamese Students’ Feedback Corpus for Sentiment Analysis},
y... | null | 6 | 286 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- vi
license:
- unknown
multilinguality:
- monolingual
pretty_name: "Vietnamese Students\u2019 Feedback Corpus"
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classifica... |
laion/laion2B-en | 2023-08-13T10:21:14.000Z | [
"license:cc-by-4.0",
"region:us"
] | laion | null | null | null | 137 | 286 | ---
license: cc-by-4.0
---
HEIGHT and WIDTH are swapped |
CertifiedJoon/Korean-Instruction | 2023-07-06T17:44:53.000Z | [
"task_categories:question-answering",
"size_categories:n<1K",
"language:ko",
"license:cdla-permissive-2.0",
"region:us"
] | CertifiedJoon | null | null | null | 3 | 286 | ---
license: cdla-permissive-2.0
dataset_info:
features:
- name: Instruction
dtype: string
- name: Response
dtype: string
- name: Source
dtype: string
- name: MetaData
dtype: string
splits:
- name: train
num_bytes: 2099234
num_examples: 1720
download_size: 907301
dataset_size: ... |
doc2dial | 2022-11-18T19:58:53.000Z | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
"region:us"
] | null | Doc2dial is dataset of goal-oriented dialogues that are grounded in the associated documents. It includes over 4500 annotated conversations with an average of 14 turns that are grounded in over 450 documents from four domains. Compared to the prior document-grounded dialogue datasets this dataset covers a variety of di... | @inproceedings{feng-etal-2020-doc2dial,
title = "doc2dial: A Goal-Oriented Document-Grounded Dialogue Dataset",
author = "Feng, Song and Wan, Hui and Gunasekara, Chulaka and Patel, Siva and Joshi, Sachindra and Lastras, Luis",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natu... | null | 2 | 285 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- closed-domain-qa
paperswithcode_id: doc2dial
pretty_name: doc2dial
dataset_... |
webis/tldr-17 | 2023-06-05T12:48:30.000Z | [
"task_categories:summarization",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"reddit-posts-summarization",
"region:us"
] | webis | This corpus contains preprocessed posts from the Reddit dataset.
The dataset consists of 3,848,330 posts with an average length of 270 words for content,
and 28 words for the summary.
Features includes strings: author, body, normalizedBody, content, summary, subreddit, subreddit_id.
Content is used as document and sum... | @inproceedings{volske-etal-2017-tl,
title = {TL;DR: Mining {R}eddit to Learn Automatic Summarization},
author = {V{\"o}lske, Michael and Potthast, Martin and Syed, Shahbaz and Stein, Benno},
booktitle = {Proceedings of the Workshop on New Frontiers in Summarization},
month = {sep},
year = {2017},... | null | 25 | 285 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: webis-tldr-17-corpus
pretty_name: Reddit Webis-TLDR-17
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- summarization
task_ids: []
t... |
okite97/news-data | 2022-08-25T10:36:01.000Z | [
"task_categories:text-classification",
"task_ids:topic-classification",
"task_ids:multi-class-classification",
"annotations_creators:other",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:afl-3.0",
"region... | okite97 | null | null | null | 2 | 285 | ---
annotations_creators:
- other
language:
- 'en'
language_creators:
- found
license:
- afl-3.0
multilinguality:
- monolingual
pretty_name: News Dataset
size_categories:
- 1K<n<10K
source_datasets:
- original
tags: []
task_categories:
- text-classification
task_ids:
- topic-classification
- multi-class-classification
... |
YeungNLP/firefly-train-1.1M | 2023-04-10T06:15:28.000Z | [
"region:us"
] | YeungNLP | null | null | null | 173 | 285 | 本数据应用于项目：[Firefly（流萤）: 中文对话式大语言模型](https://github.com/yangjianxin1/Firefly) ，训练后得到的模型[firefly-1b4](https://huggingface.co/YeungNLP/firefly-1b4)
如果您觉得此数据集对您有帮助，请like此数据集并在Github项目中star我们。
我们收集了23个常见的中文数据集，对于每个任务，由人工书写若干种指令模板，保证数据的高质量与丰富度，数据量为115万 。数据分布如下图所示：
每条数据的格式如下，包含任务类... |
Skelebor/book_titles_and_descriptions_en_clean | 2022-06-28T11:23:46.000Z | [
"region:us"
] | Skelebor | null | null | null | 1 | 284 | Entry not found |
zxvix/c4_biomedicalacademic_2 | 2023-09-12T06:21:01.000Z | [
"region:us"
] | zxvix | null | null | null | 0 | 284 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: text
dtype: string
- name: timestamp
dtype: timestamp[s]
- name: url
dtype: string
- name: original_text
dtype: string
splits:
- name: test
num_bytes: 3027569.0
n... |
iara-project/news-articles-ptbr-dataset | 2023-09-21T03:12:30.000Z | [
"region:us"
] | iara-project | null | null | null | 1 | 284 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: title
dtype: string
- name: text
dtype: string
- name: date
dtype: string
- name: category
dtype: string
- name: category_natural_la... |
glaiveai/glaive-code-assistant | 2023-09-27T22:51:02.000Z | [
"size_categories:100K<n<1M",
"license:apache-2.0",
"region:us"
] | glaiveai | null | null | null | 28 | 284 | ---
license: apache-2.0
size_categories:
- 100K<n<1M
---
# Glaive-code-assistant
Glaive-code-assistant is a dataset of ~140k code problems and solutions generated using Glaive’s synthetic data generation platform.
The data is intended to be used to make models act as code assistants, and so the data is structured in... |
Dong237/empathetic_dialogues_cleaned | 2023-09-22T14:10:27.000Z | [
"region:us"
] | Dong237 | null | null | null | 0 | 284 | ---
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: conv_id
dtype: string
- name: context
dtype: string
- name: prompt
dtype: string
- name:... |
riddle_sense | 2022-11-18T21:42:04.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:other",
"region:us"
] | null | Answering such a riddle-style question is a challenging cognitive process, in that it requires
complex commonsense reasoning abilities, an understanding of figurative language, and counterfactual reasoning
skills, which are all important abilities for advanced natural language understanding (NLU). However,
there is cur... | @InProceedings{lin-etal-2021-riddlesense,
title={RiddleSense: Reasoning about Riddle Questions Featuring Linguistic Creativity and Commonsense Knowledge},
author={Lin, Bill Yuchen and Wu, Ziyi and Yang, Yichi and Lee, Dong-Ho and Ren, Xiang},
journal={Proceedings of the 59th Annual Meeting of the Association for Comput... | null | 12 | 283 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
pretty_name: RiddleSense
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
dataset_info:
features:
- name: ans... |
mteb/biorxiv-clustering-p2p | 2022-09-27T19:15:27.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 0 | 283 | ---
language:
- en
--- |
Chris1/cityscapes_segmentation | 2022-11-03T19:43:00.000Z | [
"region:us"
] | Chris1 | null | null | null | 1 | 282 | Entry not found |
DynamicSuperb/SpeechDetection_LibriSpeech-TestClean | 2023-07-12T05:42:02.000Z | [
"region:us"
] | DynamicSuperb | null | null | null | 0 | 282 | ---
dataset_info:
features:
- name: file
dtype: string
- name: audio
dtype: audio
- name: instruction
dtype: string
- name: label
dtype: string
splits:
- name: test
num_bytes: 358157508.64
num_examples: 2620
download_size: 349425014
dataset_size: 358157508.64
---
# Dataset Card... |
Clinton/Text-to-sql-v1 | 2023-07-26T11:09:22.000Z | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:en",
"license:apache-2.0",
"SQL",
"region:us"
] | Clinton | null | null | null | 15 | 281 | ---
license: apache-2.0
task_categories:
- text-generation
language:
- en
tags:
- SQL
size_categories:
- 100K<n<1M
--- |
multi_eurlex | 2023-06-14T13:34:30.000Z | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"task_ids:topic-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:bg",
"language:cs",
"languag... | null | MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predict the relevant EUROVOC concepts (labels);
this is multi-label classification task (given ... | @InProceedings{chalkidis-etal-2021-multieurlex,
author = {Chalkidis, Ilias
and Fergadiotis, Manos
and Androutsopoulos, Ion},
title = {MultiEURLEX -- A multi-lingual and multi-label legal document
classification dataset for zero-shot cross-lingual transfer},
booktitle... | null | 21 | 280 | ---
annotations_creators:
- found
language_creators:
- found
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hr
- hu
- it
- lt
- lv
- mt
- nl
- pl
- pt
- ro
- sk
- sl
- sv
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- t... |
arbml/ashaar | 2022-09-03T18:05:56.000Z | [
"region:us"
] | arbml | null | null | null | 0 | 280 | # ashaar
introducing ashaar, the largest dataset for arabic poetry
# general statistics
| metric | value |
|-----------------|-----------|
| number of poems | 254,630 |
| number of baits | 3,857,429 |
| number of poets | 7,167 |
# License
This dataset is released under fair use for research d... |
tomasg25/scientific_lay_summarisation | 2022-10-26T11:11:33.000Z | [
"task_categories:summarization",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"abstractive-summarization",
"scientific-papers",
"la... | tomasg25 | This repository contains the PLOS and eLife datasets, introduced in the EMNLP 2022 paper "[Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature
](https://arxiv.org/abs/2210.09932)".
Each dataset contains full biomedical research articles paired with expert-written lay summaries (i.e., non-... | @misc{Goldsack_2022,
doi = {10.48550/ARXIV.2210.09932},
url = {https://arxiv.org/abs/2210.09932},
author = {Goldsack, Tomas and Zhang, Zhihao and Lin, Chenghua and Scarton, Carolina},
title = {Making Science Simple: Corpora for the Lay Summarisation of Scientific Literature},
publisher = {arXiv},
year = {20... | null | 12 | 280 | ---
annotations_creators:
- found
language:
- en
language_creators:
- found
license:
- unknown
multilinguality:
- monolingual
pretty_name: ScientificLaySummarisation
size_categories:
- 10K<n<100K
- 1K<n<10K
source_datasets:
- original
tags:
- abstractive-summarization
- scientific-papers
- lay-summarization
- PLOS
- eL... |
thu-coai/Safety-Prompts | 2023-08-25T15:02:51.000Z | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:zh",
"license:apache-2.0",
"arxiv:2304.10436",
"region:us"
] | thu-coai | null | null | null | 28 | 280 | ---
license: apache-2.0
task_categories:
- text-generation
language:
- zh
pretty_name: Safety-Prompts
size_categories:
- 100K<n<1M
---
# Dataset Card for Dataset Name
GitHub Repository: https://github.com/thu-coai/Safety-Prompts
Paper: https://arxiv.org/abs/2304.10436
|
magnifi/contextual-tiny-v1 | 2023-09-13T17:22:57.000Z | [
"region:us"
] | magnifi | null | null | null | 0 | 279 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: user_text
dtype: string
- name: true_intent
dtype: string
- name: chat_history
dtype: string
- name: contextual
dtype: boo... |
rasgaard/20_newsgroups | 2023-09-13T07:25:05.000Z | [
"region:us"
] | rasgaard | null | null | null | 0 | 278 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: label_text
dtype: string
splits:
- name: train
num_bytes: 12724811.858405516
num_examples: 10182
- name: val
num_bytes: 1414701.1415944847
num_examples: 1132
- name: test
num_bytes: ... |
bigbio/bioasq_task_b | 2022-12-22T15:41:12.000Z | [
"multilinguality:monolingual",
"language:en",
"license:other",
"region:us"
] | bigbio | The data are intended to be used as training and development data for BioASQ
10, which will take place during 2022. There is one file containing the data:
- training10b.json
The file contains the data of the first nine editions of the challenge: 4234
questions [1] with their relevant documents, snippets, concepts and... | @article{tsatsaronis2015overview,
title = {
An overview of the BIOASQ large-scale biomedical semantic indexing and
question answering competition
},
author = {
Tsatsaronis, George and Balikas, Georgios and Malakasiotis, Prodromos
and Partalas, Ioannis and Zschunke, Matthias and Alvers, Mic... | null | 3 | 277 | ---
language:
- en
bigbio_language:
- English
license: other
multilinguality: monolingual
bigbio_license_shortname: NLM_LICENSE
pretty_name: BioASQ Task B
homepage: http://participants-area.bioasq.org/datasets/
bigbio_pubmed: true
bigbio_public: false
bigbio_tasks:
- QUESTION_ANSWERING
---
# Dataset Card for BioASQ ... |
mstz/arhythmia | 2023-04-15T11:37:57.000Z | [
"task_categories:tabular-classification",
"size_categories:n<1K",
"language:en",
"license:cc",
"arrhythmia",
"tabular_classification",
"multiclass_classification",
"binary_classification",
"UCI",
"region:us"
] | mstz | null | @misc{misc_arrhythmia_5,
author = {Guvenir,H., Acar,Burak & Muderrisoglu,Haldun},
title = {{Arrhythmia}},
year = {1998},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: \\url{10.24432/C5BS32}}
} | null | 0 | 277 | ---
language:
- en
tags:
- arrhythmia
- tabular_classification
- multiclass_classification
- binary_classification
- UCI
pretty_name: Arhythmia
size_categories:
- n<1K
task_categories:
- tabular-classification
configs:
- arhytmia
- has_arhytmia
license: cc
---
# Arhythmia
The [Arrhythmia dataset](https://archive.ics.uc... |
toughdata/quora-question-answer-dataset | 2023-08-28T13:36:21.000Z | [
"task_categories:question-answering",
"task_categories:conversational",
"task_categories:text2text-generation",
"language:en",
"license:gpl-3.0",
"question",
"answer",
"quora",
"region:us"
] | toughdata | null | null | null | 0 | 277 | ---
license: gpl-3.0
task_categories:
- question-answering
- conversational
- text2text-generation
language:
- en
tags:
- question
- answer
- quora
pretty_name: Quora Question/Answer Pairs
---
Quora Question Answer Dataset (Quora-QuAD) contains 56,402 question-answer pairs scraped from Quora.
# Usage:
For instructions... |
jondurbin/airoboros-2.2 | 2023-10-03T19:01:21.000Z | [
"license:other",
"region:us"
] | jondurbin | null | null | null | 1 | 277 | ---
license: other
---
## Overview
This dataset is mostly a continuation of https://hf.co/datasets/jondurbin/airoboros-2.1, with some notable additions and fixes.
- Some of the content is "toxic"/"harmful", and contains profanity and other types of sensitive content.
- None of the content or views contained in text ... |
DFKI-SLT/tacred | 2023-05-17T12:55:00.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|other",
"language:en",
"licen... | DFKI-SLT | TACRED is a large-scale relation extraction dataset with 106,264 examples built over newswire
and web text from the corpus used in the yearly TAC Knowledge Base Population (TAC KBP) challenges.
Examples in TACRED cover 41 relation types as used in the TAC KBP challenges (e.g., per:schools_attended
and org:members) o... | @inproceedings{zhang-etal-2017-position,
title = "Position-aware Attention and Supervised Data Improve Slot Filling",
author = "Zhang, Yuhao and
Zhong, Victor and
Chen, Danqi and
Angeli, Gabor and
Manning, Christopher D.",
booktitle = "Proceedings of the 2017 Conference on Empiri... | null | 3 | 276 | ---
annotations_creators:
- crowdsourced
- expert-generated
language:
- en
language_creators:
- found
license:
- other
multilinguality:
- monolingual
pretty_name: The TAC Relation Extraction Dataset, TACRED Revisited and Re-TACRED
size_categories:
- 100K<n<1M
source_datasets:
- extended|other
tags:
- relation extractio... |
Babelscape/rebel-dataset | 2023-06-15T12:12:59.000Z | [
"task_categories:text-retrieval",
"task_categories:text-generation",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"relation-extraction",
... | Babelscape | REBEL is a silver dataset created for the paper REBEL: Relation Extraction By End-to-end Language generation | @inproceedings{huguet-cabot-navigli-2021-rebel,
title = "REBEL: Relation Extraction By End-to-end Language generation",
author = "Huguet Cabot, Pere-Llu{\'\i}s and
Navigli, Roberto",
booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2021",
month = nov,
year = "... | null | 14 | 275 | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- en
license: cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-retrieval
- text-generation
task_ids: []
pretty_name: rebel-dataset
tags:
- relation-ext... |
medalpaca/medical_meadow_pubmed_causal | 2023-04-06T17:01:00.000Z | [
"task_categories:question-answering",
"language:en",
"region:us"
] | medalpaca | null | null | null | 2 | 275 | ---
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... |
allenai/mup | 2022-10-25T10:16:52.000Z | [
"license:odc-by",
"region:us"
] | allenai | null | null | null | 2 | 274 | ---
license:
- odc-by
---
# MuP - Multi Perspective Scientific Document Summarization
Generating summaries of scientific documents is known to be a challenging task. Majority of existing work in summarization assumes only one single best gold summary for each given document. Having only one gold summary negatively im... |
sidhq/email-thread-summary | 2023-07-17T03:19:09.000Z | [
"task_categories:summarization",
"language:en",
"region:us"
] | sidhq | null | null | null | 2 | 274 | ---
dataset_info:
features:
- name: thread
struct:
- name: subject
dtype: string
- name: messages
list:
- name: timestamp
dtype: timestamp[s]
- name: from
dtype: string
- name: to
sequence: string
- name: body
dtype: string
- name: su... |
wiki_auto | 2023-06-01T14:59:51.000Z | [
"task_categories:text2text-generation",
"task_ids:text-simplification",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|other-wikipedia",
"language:en",
"... | null | WikiAuto provides a set of aligned sentences from English Wikipedia and Simple English Wikipedia
as a resource to train sentence simplification systems. The authors first crowd-sourced a set of manual alignments
between sentences in a subset of the Simple English Wikipedia and their corresponding versions in English Wi... | @inproceedings{acl/JiangMLZX20,
author = {Chao Jiang and
Mounica Maddela and
Wuwei Lan and
Yang Zhong and
Wei Xu},
editor = {Dan Jurafsky and
Joyce Chai and
Natalie Schluter and
Joel R. Tetreault},
title... | null | 7 | 273 | ---
annotations_creators:
- crowdsourced
- machine-generated
language_creators:
- found
language:
- en
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- extended|other-wikipedia
task_categories:
- text2text-generation
task_ids:
- text-simplification
pretty_name: Wiki... |
mteb/medrxiv-clustering-s2s | 2022-09-27T19:10:50.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 1 | 272 | ---
language:
- en
--- |
bloyal/oas_paired_human_sars_cov_2 | 2023-08-28T19:31:21.000Z | [
"size_categories:100K<n<1M",
"license:cc-by-4.0",
"region:us"
] | bloyal | null | null | null | 0 | 272 | ---
license: cc-by-4.0
size_categories:
- 100K<n<1M
---
# Paired SARS-COV-2 heavy/light chain sequences from the Observed Antibody Space database
Human paired heavy/light chain amino acid sequences from the Observed Antibody Space (OAS) database obtained from SARS-COV-2 studies.
https://opig.stats.ox.ac.uk/webapps/o... |
njoncode/medical-audio-dataset | 2023-09-18T10:44:55.000Z | [
"region:us"
] | njoncode | This new dataset is designed for Speech Recognition. | @InProceedings{huggingface:dataset,
title = {A medical audio dataset},
author={huggingface, Inc.
},
year={2023}
} | null | 0 | 272 | Entry not found |
veggiebird/biology-scienceqa | 2023-09-22T05:36:16.000Z | [
"region:us"
] | veggiebird | null | null | null | 0 | 272 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
- name: embeddings
sequence: float32
splits:
- name: train
num_bytes: 7464263
num_examples: 1596
download_size: 7087955
dataset_size: 7464263
configs:
- config... |
HuggingFaceH4/stack-exchange-preferences | 2023-03-08T03:37:53.000Z | [
"task_categories:question-answering",
"size_categories:10M<n<100M",
"language:en",
"license:cc-by-sa-4.0",
"RLHF",
"preferences",
"human-feedback",
"Stack Exchange",
"arxiv:2112.00861",
"region:us"
] | HuggingFaceH4 | null | null | null | 72 | 271 | ---
license: cc-by-sa-4.0
task_categories:
- question-answering
language:
- en
pretty_name: H4 Stack Exchange Preferences Dataset
tags:
- RLHF
- preferences
- human-feedback
- Stack Exchange
download_size: 22132072448
size_categories:
- 10M<n<100M
---
# Dataset Card for H4 Stack Exchange Preferences Dataset
## Dataset... |
IlyaGusev/ru_turbo_alpaca | 2023-05-25T19:45:14.000Z | [
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"language:ru",
"license:cc-by-4.0",
"instruction-finetuning",
"instruction generation",
"alpaca",
"region:us"
] | IlyaGusev | null | null | null | 49 | 271 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
- name: alternative_output
dtype: string
- name: label
dtype: string
- name: all_labels
sequence: string
- name: agreement
dtype: float32
- name: overlap
... |
sid6i7/patient-doctor | 2023-03-30T20:02:27.000Z | [
"region:us"
] | sid6i7 | null | null | null | 3 | 271 | Entry not found |
isashap/resumedatasetspeft | 2023-09-20T03:45:23.000Z | [
"region:us"
] | isashap | null | null | null | 0 | 271 | Entry not found |
qa4mre | 2023-04-05T13:36:59.000Z | [
"task_categories:multiple-choice",
"task_ids:multiple-choice-qa",
"annotations_creators:other",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"language:bg",
"language:de",
"language:en",
"language:es",
"langu... | null | QA4MRE dataset was created for the CLEF 2011/2012/2013 shared tasks to promote research in
question answering and reading comprehension. The dataset contains a supporting
passage and a set of questions corresponding to the passage. Multiple options
for answers are provided for each question, of which only one is correc... | null | null | 2 | 270 | ---
annotations_creators:
- other
language:
- ar
- bg
- de
- en
- es
- it
- ro
language_creators:
- found
license:
- unknown
multilinguality:
- multilingual
pretty_name: 'QA4MRE: Question Answering for Machine Reading Evaluation'
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- multiple-choice... |
SetFit/stsb | 2022-02-28T14:20:16.000Z | [
"region:us"
] | SetFit | null | null | null | 0 | 270 | # Glue STS-B
This dataset is a port of the official [`sts-b` dataset](https://huggingface.co/datasets/glue/viewer/stsb/validation) on the Hub.
This is not a classification task, so the label_text column is only included for consistency
Note that the sentence1 and sentence2 columns have been renamed to text1 and t... |
result-kand2-sdxl-wuerst-karlo/c09c453b | 2023-09-29T10:08:13.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 270 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 195
num_examples: 10
download_size: 1353
dataset_size: 195
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "c09c453... |
open-llm-leaderboard/details_Riiid__sheep-duck-llama-2-70b-v1.1 | 2023-10-04T07:22:11.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 270 | ---
pretty_name: Evaluation run of Riiid/sheep-duck-llama-2-70b-v1.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [Riiid/sheep-duck-llama-2-70b-v1.1](https://huggingface.co/Riiid/sheep-duck-llama-2-70b-v1.1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/Hugg... |
gradio/NYC-Airbnb-Open-Data | 2022-10-09T05:31:38.000Z | [
"license:afl-3.0",
"region:us"
] | gradio | null | null | null | 2 | 268 | ---
license: afl-3.0
---
|
parambharat/tamil_asr_corpus | 2022-12-07T17:32:59.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|common_voice",
"source_datasets:extended|openslr",
"language:ta",
"license:cc-by-4.0",
"region:us"
] | parambharat | The corpus contains roughly 1000 hours of audio and trasncripts in Tamil language. The transcripts have beedn de-duplicated using exact match deduplication. | @misc{mile_1,
doi = {10.48550/ARXIV.2207.13331},
url = {https://arxiv.org/abs/2207.13331},
author = {A, Madhavaraj and Pilar, Bharathi and G, Ramakrishnan A},
title = {Subword Dictionary Learning and Segmentation Techniques for Automatic Speech Recognition in Tamil and Kannada},
publisher = {arXiv},
year = ... | null | 1 | 268 | ---
annotations_creators:
- found
language:
- ta
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Tamil ASR Corpus
size_categories:
- 100K<n<1M
source_datasets:
- extended|common_voice
- extended|openslr
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---... |
Thaweewat/alpaca-cleaned-52k-th | 2023-05-09T16:18:02.000Z | [
"task_categories:question-answering",
"task_categories:summarization",
"size_categories:10K<n<100K",
"language:th",
"license:cc-by-sa-3.0",
"instruction-finetuning",
"region:us"
] | Thaweewat | null | null | null | 3 | 268 | ---
license: cc-by-sa-3.0
task_categories:
- question-answering
- summarization
tags:
- instruction-finetuning
language:
- th
size_categories:
- 10K<n<100K
---
# Summary
This is a Thai 🇹🇭-instructed dataset translated from cleaned version of the original Alpaca Dataset released by Stanford using Google Cloud Transla... |
open-llm-leaderboard/details_uni-tianyan__Uni-TianYan | 2023-09-18T02:40:22.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 268 | ---
pretty_name: Evaluation run of uni-tianyan/Uni-TianYan
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [uni-tianyan/Uni-TianYan](https://huggingface.co/uni-tianyan/Uni-TianYan) on the\
\ [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard... |
ghomasHudson/muld | 2022-11-02T12:55:17.000Z | [
"task_categories:question-answering",
"task_categories:summarization",
"task_categories:text-generation",
"task_categories:translation",
"task_ids:abstractive-qa",
"annotations_creators:found",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:translation",
"multilin... | ghomasHudson | MuLD: The Multitask Long Document Benchmark
A set of NLP tasks where each example is over 10,000 tokens long. | @misc{hudson2022muld,
title{MuLD: The Multitask Long Document Benchmark},
author={G Thomas Hudson, Noura Al Moubayed}
year={2022},
eprint={TODO},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
Some of these datasets are directly based on existing datasets. Please cite these works. | null | 5 | 267 | ---
annotations_creators:
- found
- crowdsourced
language_creators:
- found
language:
- en
- de
license: []
multilinguality:
- translation
- monolingual
size_categories:
- unknown
source_datasets:
- original
- extended|hotpot_qa
- extended|open_subtitles
task_categories:
- question-answering
- summarization
- text-gene... |
ai4bharat/IndicQA | 2023-06-20T03:03:32.000Z | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"language:as",
"language:bn",
"language:gu",
"language:hi",
"language:kn",
... | ai4bharat | \ | \ | null | 1 | 267 | ---
annotations_creators:
- expert-generated
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: IndicQA
size_categories:
- n<1K
source_datasets:
- original
tags: []
task_categories:
- question-answering
task_ids:
... |
olm/olm-wikipedia-20221220 | 2022-12-29T03:12:35.000Z | [
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:en",
"pretraining",
"language modelling",
"wikipedia",
"web",
"region:us"
] | olm | null | null | null | 2 | 267 | ---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- found
license: []
multilinguality:
- monolingual
pretty_name: OLM December 2022 Wikipedia
size_categories:
- 1M<n<10M
source_datasets: []
tags:
- pretraining
- language modelling
- wikipedia
- web
task_categories: []
task_ids: []
---
# Datas... |
bzantium/LongBench | 2023-09-25T04:03:43.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"task_categories:summarization",
"task_categories:conversational",
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"language:zh",
"Long Context",
"arxiv:2308.14508",
"arxiv:2108.00573",
"... | bzantium | LongBench is a comprehensive benchmark for multilingual and multi-task purposes, with the goal to fully measure and evaluate the ability of pre-trained language models to understand long text. This dataset consists of twenty different tasks, covering key long-text application scenarios such as multi-document QA, single... | null | null | 0 | 267 | ---
task_categories:
- question-answering
- text-generation
- summarization
- conversational
- text-classification
language:
- en
- zh
tags:
- Long Context
size_categories:
- 1K<n<10K
---
# Introduction
**LongBench** is the first benchmark for bilingual, multitask, and comprehensive assessment of **long context under... |
yxchar/ag-tlm | 2021-11-04T21:20:14.000Z | [
"region:us"
] | yxchar | null | null | null | 0 | 266 | Entry not found |
mteb/medrxiv-clustering-p2p | 2022-09-27T19:10:43.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 0 | 266 | ---
language:
- en
--- |
heegyu/kowiki-sentences | 2022-10-06T00:54:57.000Z | [
"task_categories:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:ko",
"license:cc-by-sa-3.0",
"region:us"
] | heegyu | null | null | null | 1 | 266 | ---
license: cc-by-sa-3.0
language:
- ko
language_creators:
- other
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
task_categories:
- other
---
20221001 한국어 위키를 kss(backend=mecab)을 이용해서 문장 단위로 분리한 데이터
- 549262 articles, 4724064 sentences
- 한국어 비중이 50% 이하거나 한국어 글자가 10자 이하인 경우를 제외 |
DKYoon/SlimPajama-6B | 2023-08-21T16:54:47.000Z | [
"task_categories:text-generation",
"size_categories:1M<n<10M",
"language:en",
"region:us"
] | DKYoon | null | null | null | 4 | 266 | ---
language:
- en
size_categories:
- 1M<n<10M
task_categories:
- text-generation
pretty_name: SlimPajama-6B
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: t... |
open-llm-leaderboard/details_ICBU-NPU__FashionGPT-70B-V1.1 | 2023-09-19T01:01:39.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 266 | ---
pretty_name: Evaluation run of ICBU-NPU/FashionGPT-70B-V1.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [ICBU-NPU/FashionGPT-70B-V1.1](https://huggingface.co/ICBU-NPU/FashionGPT-70B-V1.1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_... |
wiki_asp | 2022-11-18T21:59:51.000Z | [
"task_categories:summarization",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"aspect-based-summarization",
"arxiv:2011.07832",
"region:us"
] | null | WikiAsp is a multi-domain, aspect-based summarization dataset in the encyclopedic
domain. In this task, models are asked to summarize cited reference documents of a
Wikipedia article into aspect-based summaries. Each of the 20 domains include 10
domain-specific pre-defined aspects. | @article{hayashi20tacl,
title = {WikiAsp: A Dataset for Multi-domain Aspect-based Summarization},
authors = {Hiroaki Hayashi and Prashant Budania and Peng Wang and Chris Ackerson and Raj Neervannan and Graham Neubig},
journal = {Transactions of the Association for Computational Linguistics (TACL)},
year = ... | null | 3 | 265 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
task_ids: []
paperswithcode_id: wikiasp
pretty_name: WikiAsp
tags:
- aspect-based-su... |
Fazzie/Teyvat | 2022-12-13T02:09:42.000Z | [
"task_categories:text-to-image",
"annotations_creators:no-annotation",
"language_creators:found",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | Fazzie | Teyvat is the first small-scale text-to-image prompt dataset for Genshin impact. | null | null | 18 | 265 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
source_datasets:
- original
task_categories:
- text-to-image
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 71202
num_examples:... |
ashraq/tmdb-people-image | 2023-04-21T20:02:31.000Z | [
"region:us"
] | ashraq | null | null | null | 2 | 265 | ---
dataset_info:
features:
- name: adult
dtype: bool
- name: also_known_as
dtype: string
- name: biography
dtype: string
- name: birthday
dtype: string
- name: deathday
dtype: string
- name: gender
dtype: int64
- name: homepage
dtype: string
- name: id
dtype: int64
-... |
JanosAudran/financial-reports-sec | 2023-01-06T17:44:08.000Z | [
"task_categories:fill-mask",
"task_categories:text-classification",
"task_ids:masked-language-modeling",
"task_ids:multi-class-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_cat... | JanosAudran | The dataset contains the annual report of US public firms filing with the SEC EDGAR system.
Each annual report (10K filing) is broken into 20 sections. Each section is split into individual sentences.
Sentiment labels are provided on a per filing basis from the market reaction around the filing data.
Additional metadat... | null | null | 38 | 265 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- expert-generated
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: US public firm Annual Reports (10-K)
size_categories:
- 10M<n<100M
source_datasets:
- extended|other
tags:
- "'finance"
- financial
- 10... |
axiong/pmc_llama_instructions | 2023-09-01T04:52:44.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:openrail",
"biology",
"med",
"region:us"
] | axiong | null | null | null | 10 | 265 | ---
license: openrail
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- biology
- med
---
This repo provides part of the dataset used for PMC-LLaMA-13B's instruction tuning.
| Data | Size | Link |
| --- | --- | --- |
| ChatDoctor | 100K | https://www.yunxiangli.top/ChatDoctor/ |
| MedQA |... |
kyujinpy/KoCoT_2000 | 2023-10-10T13:19:00.000Z | [
"task_categories:text-generation",
"task_categories:text-classification",
"size_categories:1k<n<5k",
"language:en",
"license:cc-by-4.0",
"arxiv:2305.14045",
"region:us"
] | kyujinpy | null | null | null | 6 | 265 | ---
license: cc-by-4.0
task_categories:
- text-generation
- text-classification
language:
- en
size_categories:
- 1k<n<5k
---
# KoCoT-Collection
Using DeepL dataset, translation about [kaist-CoT](https://huggingface.co/datasets/kaist-ai/CoT-Collection).
---
# Original Dataset Card for Dataset Name
## Dataset Descr... |
mteb/reddit-clustering-p2p | 2022-09-27T19:13:59.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 0 | 264 | ---
language:
- en
---
10 sets with the following stats:
1. 91 labels & 15592 samples
2. 64 labels & 79172 samples
3. 38 labels & 1942 samples
4. 11 labels & 13224 samples
5. 64 labels & 92303 samples
6. 87 labels & 28607 samples
7. 10 labels & 69146 samples
8. 48 labels & 67469 samples
9. 64 labels & 29683 samples
1... |
humarin/chatgpt-paraphrases | 2023-04-05T16:27:16.000Z | [
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
"language:en",
"license:openrail",
"region:us"
] | humarin | null | null | null | 30 | 264 | ---
license: openrail
task_categories:
- text2text-generation
language:
- en
size_categories:
- 100K<n<1M
---
This is a dataset of paraphrases created by ChatGPT.
Model based on this dataset is avaible: [model](https://huggingface.co/humarin/chatgpt_paraphraser_on_T5_base)
## We used this prompt to generate paraphras... |
open-llm-leaderboard/details_AIDC-ai-business__Marcoroni-70B-v1 | 2023-09-22T18:17:15.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 264 | ---
pretty_name: Evaluation run of AIDC-ai-business/Marcoroni-70B-v1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [AIDC-ai-business/Marcoroni-70B-v1](https://huggingface.co/AIDC-ai-business/Marcoroni-70B-v1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/Hugg... |
open-llm-leaderboard/details_mistralai__Mistral-7B-v0.1 | 2023-09-27T15:32:21.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 264 | ---
pretty_name: Evaluation run of mistralai/Mistral-7B-v0.1
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leade... |
strombergnlp/broad_twitter_corpus | 2022-07-01T15:46:36.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | strombergnlp | This is the Broad Twitter corpus, a dataset of tweets collected over stratified times, places and social uses.
The goal is to represent a broad range of activities, giving a dataset more representative of the language used
in this hardest of social media formats to process. Further, the BTC is annotated for named ent... | @inproceedings{derczynski2016broad,
title={Broad twitter corpus: A diverse named entity recognition resource},
author={Derczynski, Leon and Bontcheva, Kalina and Roberts, Ian},
booktitle={Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
pages={1169--... | null | 3 | 263 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: broad-twitter-corpus
pretty_name... |
hoskinson-center/proof-pile | 2023-08-19T03:24:11.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"language:en",
"license:apache-2.0",
"math",
"mathematics",
"formal-mathematics",
"region:us"
] | hoskinson-center | A dataset of high quality mathematical text. | @InProceedings{huggingface:dataset,
title = {proof-pile},
author={Zhangir Azerbayev, Edward Ayers, Bartosz Piotrowski
},
year={2022}
} | null | 26 | 263 | ---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- found
license: [apache-2.0]
multilinguality:
- monolingual
pretty_name: proof-pile
size_categories: []
source_datasets: []
tags:
- math
- mathematics
- formal-mathematics
task_categories:
- text-generation
task_ids:
- language-modeling
---
#... |
reciprocate/megasynth | 2023-07-03T09:37:26.000Z | [
"region:us"
] | reciprocate | null | null | null | 0 | 263 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: selected
dtype: string
- name: rejected
dtype: string
- name: source
dtype: string
splits:
- name: train
num_bytes: 21906656
num_examples: 11792
- name: test
num_bytes: 2305629
num_examples: 1249
download_... |
Jules33/jtbenchmark1 | 2023-09-12T05:54:00.000Z | [
"region:us"
] | Jules33 | null | null | null | 0 | 263 | Entry not found |
arxiv_dataset | 2022-11-03T16:16:19.000Z | [
"task_categories:translation",
"task_categories:summarization",
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:explanation-generation",
"task_ids:fact-checking-retrieval",
"task_ids:text-simplification",
"annotations_creators:no-annota... | null | A dataset of 1.7 million arXiv articles for applications like trend analysis, paper recommender engines, category prediction, co-citation networks, knowledge graph construction and semantic search interfaces. | @misc{clement2019arxiv,
title={On the Use of ArXiv as a Dataset},
author={Colin B. Clement and Matthew Bierbaum and Kevin P. O'Keeffe and Alexander A. Alemi},
year={2019},
eprint={1905.00075},
archivePrefix={arXiv},
primaryClass={cs.IR}
} | null | 37 | 262 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- translation
- summarization
- text-retrieval
task_ids:
- document-retrieval
- entity-linking-retriev... |
head_qa | 2023-06-01T14:59:51.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:es",
"license:mit",
"region:us"
] | null | HEAD-QA is a multi-choice HEAlthcare Dataset. The questions come from exams to access a specialized position in the
Spanish healthcare system, and are challenging even for highly specialized humans. They are designed by the Ministerio
de Sanidad, Consumo y Bienestar Social.
The dataset contains questions about the fol... | @inproceedings{vilares-gomez-rodriguez-2019-head,
title = "{HEAD}-{QA}: A Healthcare Dataset for Complex Reasoning",
author = "Vilares, David and
G{\'o}mez-Rodr{\'i}guez, Carlos",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
... | null | 7 | 262 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
- es
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: headqa
pretty_name: HEAD-QA
da... |
M-CLIP/ImageCaptions-7M-Embeddings | 2022-05-17T23:34:13.000Z | [
"region:us"
] | M-CLIP | null | null | null | 0 | 262 | Entry not found |
biglam/nls_chapbook_illustrations | 2023-02-15T16:11:54.000Z | [
"task_categories:object-detection",
"task_categories:image-classification",
"task_ids:multi-class-image-classification",
"annotations_creators:expert-generated",
"size_categories:1K<n<10K",
"license:other",
"lam",
"historic",
"arxiv:1405.0312",
"region:us"
] | biglam | null | @inproceedings{10.1145/3476887.3476893,
author = {Dutta, Abhishek and Bergel, Giles and Zisserman, Andrew},
title = {Visual Analysis of Chapbooks Printed in Scotland},
year = {2021},
isbn = {9781450386906},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/... | null | 7 | 262 | ---
annotations_creators:
- expert-generated
language_creators: []
license:
- other
multilinguality: []
pretty_name: National Library of Scotland Chapbook Illustrations
size_categories:
- 1K<n<10K
source_datasets: []
tags:
- lam
- historic
task_categories:
- object-detection
- image-classification
task_ids:
- multi-cla... |
lc_quad | 2023-04-05T10:09:15.000Z | [
"task_categories:question-answering",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-3.0",
"knowledge-base-qa",
"region:us"
] | null | LC-QuAD 2.0 is a Large Question Answering dataset with 30,000 pairs of question and its corresponding SPARQL query. The target knowledge base is Wikidata and DBpedia, specifically the 2018 version. Please see our paper for details about the dataset creation process and framework. | @inproceedings{dubey2017lc2,
title={LC-QuAD 2.0: A Large Dataset for Complex Question Answering over Wikidata and DBpedia},
author={Dubey, Mohnish and Banerjee, Debayan and Abdelkawi, Abdelrahman and Lehmann, Jens},
booktitle={Proceedings of the 18th International Semantic Web Conference (ISWC)},
year={2019},
organizat... | null | 5 | 261 | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- cc-by-3.0
multilinguality:
- monolingual
pretty_name: 'LC-QuAD 2.0: Large-scale Complex Question Answering Dataset'
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids: []
p... |
jamescalam/image-text-demo | 2023-02-06T05:29:49.000Z | [
"region:us"
] | jamescalam | Demo dataset for testing or showing image-text capabilities. | @InProceedings{huggingface:dataset,
title = {Small image-text set},
author={James Briggs},
year={2022}
} | null | 0 | 261 | Entry not found |
Birchlabs/openai-prm800k-solutions-only | 2023-06-04T21:56:21.000Z | [
"license:mit",
"region:us"
] | Birchlabs | null | null | null | 5 | 261 | ---
license: mit
---
|
zxvix/pubmed_rap_2 | 2023-09-09T09:59:11.000Z | [
"region:us"
] | zxvix | null | null | null | 0 | 261 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: MedlineCitation
struct:
- name: PMID
dtype: int32
- name: DateCompleted
struct:
- name: Year
dtype: int32
- name: Month
dtype: int32
- nam... |
medalpaca/medical_meadow_cord19 | 2023-04-06T16:47:03.000Z | [
"task_categories:summarization",
"size_categories:100K<n<1M",
"language:en",
"region:us"
] | medalpaca | null | null | null | 3 | 260 | ---
task_categories:
- summarization
language:
- en
size_categories:
- 100K<n<1M
---
# CORD 19
## Dataset Description
- **Homepage:** https://www.kaggle.com/datasets/allen-institute-for-ai/CORD-19-research-challenge
### Dataset Summary
In response to the COVID-19 pandemic, the White House and a coalition of leadin... |
MBZUAI/LaMini-instruction | 2023-04-30T11:01:41.000Z | [
"task_categories:text2text-generation",
"size_categories:1M<n<10M",
"language:en",
"license:cc-by-nc-4.0",
"arxiv:2304.14402",
"region:us"
] | MBZUAI | null | null | null | 105 | 259 | ---
license: cc-by-nc-4.0
task_categories:
- text2text-generation
language:
- en
size_categories:
- 1M<n<10M
dataset_info:
features:
- name: instruction
dtype: string
- name: response
dtype: string
- name: instruction_source
dtype: string
splits:
- name: train
num_bytes: 1162632572
num_e... |
yuvalkirstain/pickapic_v1_no_images | 2023-04-16T14:53:35.000Z | [
"region:us"
] | yuvalkirstain | null | null | null | 0 | 259 | ---
dataset_info:
features:
- name: are_different
dtype: bool
- name: best_image_uid
dtype: string
- name: caption
dtype: string
- name: created_at
dtype: timestamp[ns]
- name: has_label
dtype: bool
- name: image_0_uid
dtype: string
- name: image_0_url
dtype: string
- name:... |
open-llm-leaderboard/details_adonlee__LLaMA_2_70B_LoRA | 2023-09-22T21:37:15.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 259 | ---
pretty_name: Evaluation run of adonlee/LLaMA_2_70B_LoRA
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [adonlee/LLaMA_2_70B_LoRA](https://huggingface.co/adonlee/LLaMA_2_70B_LoRA) on\
\ the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderbo... |
khalidalt/model-written-evals | 2023-07-02T20:24:29.000Z | [
"task_categories:multiple-choice",
"task_categories:zero-shot-classification",
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"task_ids:multiple-choice-coreference-resolution",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:monol... | khalidalt | This new dataset is designed to solve this great NLP task and is crafted with a lot of care. | @misc{perez2022discovering,
doi = {10.48550/ARXIV.2212.09251},
url = {https://arxiv.org/abs/2212.09251},
author = {Perez, Ethan and Ringer, Sam and Lukošiūtė, Kamilė and Nguyen, Karina and Chen, Edwin and Heiner, Scott and Pettit, Craig and Olsson, Catherine and Kundu, Sandipan and Kadavath, Saurav and Jones, And... | null | 0 | 258 | ---
annotations_creators:
- machine-generated
language:
- en
language_creators:
- machine-generated
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Evaluations from "Discovering Language Model Behaviors with Model-Written
Evaluations"
size_categories:
- 100K<n<1M
source_datasets:
- original
tags:
- g... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.