id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
huggingface/documentation-images | 2023-11-03T00:00:09.000Z | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | huggingface | null | null | 19 | 105 | 2022-03-02T23:29:22 | ---
license: cc-by-nc-sa-4.0
---
### This dataset contains images used in the documentation of HuggingFace's libraries.
HF Team: Please make sure you optimize the assets before uploading them.
My favorite tool for this is https://tinypng.com/.
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graphs-datasets/PROTEINS | 2023-02-07T16:39:11.000Z | [
"task_categories:graph-ml",
"license:unknown",
"region:us"
] | graphs-datasets | null | null | 0 | 105 | 2022-08-01T15:50:33 | ---
license: unknown
task_categories:
- graph-ml
---
# Dataset Card for PROTEINS
## 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)
- [External Us... | 4,863 | [
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TUKE-DeutscheTelekom/skquad | 2022-12-05T14:10:32.000Z | [
"task_categories:question-answering",
"task_categories:text-retrieval",
"task_ids:open-domain-qa",
"task_ids:extractive-qa",
"task_ids:document-retrieval",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categor... | TUKE-DeutscheTelekom | Slovak Question Answering Dataset | TBD | 3 | 105 | 2022-12-02T11:28:37 | ---
annotations_creators:
- crowdsourced
language:
- sk
language_creators:
- crowdsourced
- found
license:
- cc-by-sa-4.0
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: squad
pretty_name: skquad
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- wikipedia
task_categories:
- question-answer... | 4,907 | [
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RicardoRei/wmt-da-human-evaluation | 2023-02-17T10:41:18.000Z | [
"size_categories:1M<n<10M",
"language:bn",
"language:cs",
"language:de",
"language:en",
"language:et",
"language:fi",
"language:fr",
"language:gu",
"language:ha",
"language:hi",
"language:is",
"language:ja",
"language:kk",
"language:km",
"language:lt",
"language:lv",
"language:pl",... | RicardoRei | null | null | 0 | 105 | 2023-02-16T18:49:07 | ---
license: apache-2.0
size_categories:
- 1M<n<10M
language:
- bn
- cs
- de
- en
- et
- fi
- fr
- gu
- ha
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- is
- ja
- kk
- km
- lt
- lv
- pl
- ps
- ru
- ta
- tr
- uk
- xh
- zh
- zu
tags:
- mt-evaluation
- WMT
- 41-lang-pairs
---
# Dataset Summary
This dataset contains all DA human annotations from previous WMT ... | 2,176 | [
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SotirisLegkas/clickbait | 2023-06-23T11:30:01.000Z | [
"region:us"
] | SotirisLegkas | null | null | 0 | 105 | 2023-06-23T11:08:28 | Entry not found | 15 | [
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qgyd2021/lip_service_4chan | 2023-10-27T01:51:52.000Z | [
"task_categories:question-answering",
"size_categories:10M<n<100M",
"language:zh",
"license:cc-by-4.0",
"art",
"region:us"
] | qgyd2021 | null | @dataset{lip_service_4chan,
author = {Xing Tian},
title = {lip_service_4chan},
month = sep,
year = 2023,
publisher = {Xing Tian},
version = {1.0},
} | 0 | 105 | 2023-09-07T08:50:39 | ---
task_categories:
- question-answering
language:
- zh
tags:
- art
pretty_name: lip_service
size_categories:
- 10M<n<100M
license: cc-by-4.0
---
## Lip Service
满嘴芬芳
### 数据来源
基于网站 [吵架对线陪练员](https://aibang.run/chat/sb) 的服务.
我们采用 [moss-003-sft-data](https://github.com/OpenLMLab/MOSS) 对话数据中的提问做 prompt,
然后调用 [吵架对线陪练员]... | 478 | [
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SneakyInsect/maestro-rollingsplit | 2023-10-04T13:21:21.000Z | [
"region:us"
] | SneakyInsect | null | null | 0 | 105 | 2023-10-02T11:02:50 | ---
dataset_info:
features:
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Arsive/toxicity_classification_jigsaw | 2023-10-03T12:51:28.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<200K",
"language:en",
"license:apache-2.0",
"region:us"
] | Arsive | null | null | 0 | 105 | 2023-10-03T06:51:48 | ---
license: apache-2.0
task_categories:
- text-classification
language:
- en
size_categories:
- 1K<n<200K
---
### Dataset info
#### Training Dataset:
You are provided with a large number of Wikipedia comments which have been labeled by human raters for toxic behavior. The types of toxicity are:
- toxic
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tyzhu/squad_first_sent_v4_train_30_eval_10 | 2023-10-03T10:41:48.000Z | [
"region:us"
] | tyzhu | null | null | 0 | 105 | 2023-10-03T10:00:10 | ---
dataset_info:
features:
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struct:
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sequence: int64
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dtype: str... | 881 | [
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flytech/llama-python-codes-30k | 2023-11-02T19:17:20.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10M<n<100M",
"language:en",
"license:llama2",
"code",
"python",
"instruct",
"llama",
"flytech",
"region:us"
] | flytech | null | null | 9 | 105 | 2023-10-08T16:10:50 | ---
author: FlyTech
license: llama2
task_categories:
- question-answering
- text-generation
- text2text-generation
language:
- en
tags:
- code
- python
- instruct
- llama
- flytech
pretty_name: Llama1/2 Python Codes 30k Tokenized
size_categories:
- 10M<n<100M
---
### <span style="color:#3560B0; font-weight: bold;">Pyth... | 3,476 | [
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OsamaBsher/AITA-Reddit-Dataset | 2023-11-01T22:19:37.000Z | [
"task_categories:text-generation",
"task_categories:text-classification",
"size_categories:100K<n<1M",
"arxiv:2310.18336",
"region:us"
] | OsamaBsher | null | null | 1 | 105 | 2023-10-20T17:31:34 | ---
task_categories:
- text-generation
- text-classification
size_categories:
- 100K<n<1M
---
# Dataset Card for AITA Reddit Posts and Comments
Posts of the AITA subreddit, with the 2 top voted comments that share the post verdict. Extracted using REDDIT PushShift (from 2013 to April 2023)
## Dataset Details
The da... | 775 | [
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result-kand2-sdxl-wuerst-karlo/58bc4cd4 | 2023-10-21T18:49:34.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | 0 | 105 | 2023-10-21T18:49:33 | ---
dataset_info:
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num_examples: 10
download_size: 1342
dataset_size: 168
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "58bc4cd... | 455 | [
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atmallen/qm_1.0e_eval | 2023-10-31T19:40:56.000Z | [
"region:us"
] | atmallen | null | null | 0 | 105 | 2023-10-27T05:41:56 | ---
configs:
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- na... | 1,118 | [
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best2009 | 2023-01-25T14:27:17.000Z | [
"task_categories:token-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:th",
"license:cc-by-nc-sa-3.0",
"word-tokenization",
"region:us"
] | null | `best2009` is a Thai word-tokenization dataset from encyclopedia, novels, news and articles by
[NECTEC](https://www.nectec.or.th/) (148,995/2,252 lines of train/test). It was created for
[BEST 2010: Word Tokenization Competition](https://thailang.nectec.or.th/archive/indexa290.html?q=node/10).
The test set answers are ... | @inproceedings{kosawat2009best,
title={BEST 2009: Thai word segmentation software contest},
author={Kosawat, Krit and Boriboon, Monthika and Chootrakool, Patcharika and Chotimongkol, Ananlada and Klaithin, Supon and Kongyoung, Sarawoot and Kriengket, Kanyanut and Phaholphinyo, Sitthaa and Purodakananda, Sumonmas an... | 0 | 104 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- th
license:
- cc-by-nc-sa-3.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids: []
pretty_name: best2009
tags:
- word-tokenization
dataset_info:
f... | 8,403 | [
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factckbr | 2023-01-25T14:30:15.000Z | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
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"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pt",
"license:mit",
"region:us"
] | null | A dataset to study Fake News in Portuguese, presenting a supposedly false News along with their respective fact check and classification.
The data is collected from the ClaimReview, a structured data schema used by fact check agencies to share their results in search engines, enabling data collect in real time.
The FAC... | @inproceedings{10.1145/3323503.3361698,
author = {Moreno, Jo\\~{a}o and Bressan, Gra\\c{c}a},
title = {FACTCK.BR: A New Dataset to Study Fake News},
year = {2019},
isbn = {9781450367639},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org... | 3 | 104 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
pretty_name: FACTCK BR
dataset_info:
features:
- name: url
... | 4,058 | [
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muchocine | 2023-01-25T14:40:54.000Z | [
"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:es",
"license:unknown",
"region:us"
] | null | The Muchocine reviews dataset contains 3,872 longform movie reviews in Spanish language,
each with a shorter summary review, and a rating on a 1-5 scale. | null | 4 | 104 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- es
license:
- unknown
multilinguality:
- monolingual
size_categories:
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source_datasets:
- original
task_categories:
- text-classification
task_ids:
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pretty_name: Muchocine
dataset_info:
features:
- name: rev... | 5,258 | [
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srwac | 2022-11-03T16:08:14.000Z | [
"task_categories:text-generation",
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"language_creators:found",
"multilinguality:monolingual",
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"source_datasets:original",
"language:sr",... | null | The Serbian web corpus srWaC was built by crawling the .rs top-level domain in 2014. The corpus was near-deduplicated on paragraph level, normalised via diacritic restoration, morphosyntactically annotated and lemmatised. The corpus is shuffled by paragraphs. Each paragraph contains metadata on the URL, domain and lang... | @misc{11356/1063,
title = {Serbian web corpus {srWaC} 1.1},
author = {Ljube{\v s}i{\'c}, Nikola and Klubi{\v c}ka, Filip},
url = {http://hdl.handle.net/11356/1063},
note = {Slovenian language resource repository {CLARIN}.{SI}},
copyright = {Creative Commons - Attribution-{ShareAlike} 4.0 International ({CC} {BY}-{... | 1 | 104 | 2022-03-02T23:29:22 | ---
annotations_creators:
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language_creators:
- found
language:
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license:
- cc-by-sa-3.0
multilinguality:
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size_categories:
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source_datasets:
- original
task_categories:
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- fill-mask
task_ids:
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paperswithcode_id: n... | 3,955 | [
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Cropinky/rap_lyrics_english | 2021-07-21T03:07:36.000Z | [
"region:us"
] | Cropinky | null | null | 3 | 104 | 2022-03-02T23:29:22 | ## Rap lyrics dataset
this is the repo containing the dataset we made for the hugging face community week, in order to download more songs you need to request and get(it's very simple and fast) your genius API key which ou put in the genius.py file<br/>
#TODO: turn it into an actual huggingface dataset | 304 | [
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cbrew475/hwu66 | 2022-02-22T18:18:36.000Z | [
"region:us"
] | cbrew475 | This project contains natural language data for human-robot interaction in a projecthome domain which
Xingkun Liu et al, from Heriot-Watt University, collected and annotated. It can be used for evaluating
NLU services/platforms. | @InProceedings{XLiu.etal:IWSDS2019,
author = {Xingkun Liu, Arash Eshghi, Pawel Swietojanski and Verena Rieser},
title = {Benchmarking Natural Language Understanding Services for building Conversational Agents},
booktitle = {Proceedings of the Tenth International Workshop on Spoken Dialogue Systems Technolo... | 0 | 104 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
Artificio/WikiArt | 2023-01-18T17:13:54.000Z | [
"region:us"
] | Artificio | null | null | 4 | 104 | 2022-07-21T21:18:50 | ---
dataset_info:
features:
- name: title
dtype: string
- name: artist
dtype: string
- name: date
dtype: string
- name: genre
dtype: string
- name: style
dtype: string
- name: description
dtype: string
- name: filename
dtype: string
- name: image
dtype: image
- name: ... | 663 | [
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0.024169921875,
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-0.043853759765625,
-0.044097900390625,
-0.012... |
lmqg/qa_squadshifts_synthetic | 2023-01-15T14:25:15.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|wikipedia",
"language:en",
"license:cc-by-4.0",
"arxiv:2210.03992",
"region:us"
] | lmqg | null | @inproceedings{ushio-etal-2022-generative,
title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
author = "Ushio, Asahi and
Alva-Manchego, Fernando and
Camacho-Collados, Jose",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Nat... | 0 | 104 | 2022-12-20T08:31:18 | ---
license: cc-by-4.0
pretty_name: Synthetic QA dataset on SQuADShifts.
language: en
multilinguality: monolingual
size_categories: 10K<n<100K
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for "lmqg/qa_squadshifts_synthetic"
## Dataset Descrip... | 2,035 | [
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dreamerdeo/finqa | 2023-03-06T08:29:39.000Z | [
"region:us"
] | dreamerdeo | null | null | 1 | 104 | 2023-03-05T08:38:40 | dataset_info:
features:
- name: id
dtype: string
- name: post_text
sequence: string
- name: pre_text
sequence: string
- name: question
dtype: string
- name: answers
dtype: string
- name: table
sequence:
sequence: string
splits:
- name: train
num_bytes: 26984130
nu... | 515 | [
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0.... |
izumi-lab/llm-japanese-dataset-vanilla | 2023-09-29T14:40:26.000Z | [
"size_categories:1M<n<10M",
"language:ja",
"license:cc-by-sa-4.0",
"arxiv:2305.12720",
"arxiv:2309.03412",
"region:us"
] | izumi-lab | null | null | 7 | 104 | 2023-05-23T14:45:27 | ---
license: cc-by-sa-4.0
language:
- ja
size_categories:
- 1M<n<10M
---
# llm-japanese-dataset-vanilla
LLM構築用の日本語チャットデータセット
[izumi-lab/llm-japanese-dataset](https://huggingface.co/datasets/izumi-lab/llm-japanese-dataset) から，日英翻訳のデータセット等を抜いたものです．
主に，日本語LLMモデルなどに対して，チャット(Instruction)応答タスクに関してLoRAなどでチューニングするために使用できます．... | 1,925 | [
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0.016... |
neural-bridge/full_cqa_22k | 2023-10-02T20:14:12.000Z | [
"region:us"
] | neural-bridge | null | null | 0 | 104 | 2023-10-02T20:13:17 | ---
dataset_info:
features:
- name: clear_prompt
dtype: string
splits:
- name: train
num_bytes: 43183498.53262665
num_examples: 17433
- name: test
num_bytes: 10797732.467373349
num_examples: 4359
download_size: 32335855
dataset_size: 53981231.0
---
# Dataset Card for "full_cqa_12k"
[M... | 449 | [
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ContextualAI/trivia_qa | 2023-10-07T00:42:28.000Z | [
"region:us"
] | ContextualAI | null | null | 1 | 104 | 2023-10-07T00:40:15 | ---
dataset_info:
features:
- name: target
dtype: string
- name: query
dtype: string
- name: gold_generation
sequence: string
splits:
- name: train
num_bytes: 29497317
num_examples: 78785
- name: dev
num_bytes: 3349643
num_examples: 8837
- name: test
num_bytes: 4316214
... | 560 | [
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casperhansen/longalpaca_1k_test | 2023-10-15T11:55:55.000Z | [
"license:cc-by-nc-4.0",
"region:us"
] | casperhansen | null | null | 0 | 104 | 2023-10-15T11:48:27 | ---
license: cc-by-nc-4.0
---
Dataset preprocessed from https://huggingface.co/datasets/Yukang/LongAlpaca-12k.
This contains 1000 samples that have a minimum length of 16k tokens and a maximum of 32k tokens.
## Script to reproduce
```python
from datasets import load_dataset
from transformers import AutoTokenizer
im... | 1,563 | [
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0.0277404785... |
caner | 2023-03-16T14:47:48.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar",
"license:unknown",
"region:us"
] | null | Classical Arabic Named Entity Recognition corpus as a new corpus of tagged data that can be useful for handling the issues in recognition of Arabic named entities. | @article{article,
author = {Salah, Ramzi and Zakaria, Lailatul},
year = {2018},
month = {12},
pages = {},
title = {BUILDING THE CLASSICAL ARABIC NAMED ENTITY RECOGNITION CORPUS (CANERCORPUS)},
volume = {96},
journal = {Journal of Theoretical and Applied Information Technology}
} | 1 | 103 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- ar
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: CANER
dataset_info:
fea... | 4,417 | [
[
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0.0301513671875,
-0.0281219482421875,
-0.08837890625,
-0.05316162109375,
0.018112182617... |
clickbait_news_bg | 2023-01-25T14:28:03.000Z | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:bg",
"license:unknown",
"region:us"
] | null | Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017. | @InProceedings{clickbait_news_bg,
title = {Dataset with clickbait and fake news in Bulgarian. Introduced for the Hack the Fake News 2017.},
authors={Data Science Society},
year={2017},
url={https://gitlab.com/datasciencesociety/case_fake_news/}
} | 0 | 103 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- bg
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
pretty_name: Clickbait/Fake News in Bulgarian
datas... | 5,951 | [
[
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0.0262451171875,
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0.025390625,
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-0.062042236328125,
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0.0076065063476562... |
hkcancor | 2023-02-23T08:43:12.000Z | [
"task_categories:translation",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:yue",
... | null | The Hong Kong Cantonese Corpus (HKCanCor) comprise transcribed conversations
recorded between March 1997 and August 1998. It contains recordings of
spontaneous speech (51 texts) and radio programmes (42 texts),
which involve 2 to 4 speakers, with 1 text of monologue.
In total, the corpus contains around 230,000 Chines... | @article{luke2015hong,
author={Luke, Kang-Kwong and Wong, May LY},
title={The Hong Kong Cantonese corpus: design and uses},
journal={Journal of Chinese Linguistics},
year={2015},
pages={309-330},
month={12}
}
@misc{lee2020,
author = {Lee, Jackson},
title = {PyCantonese: Cantonese Linguistics and NLP in ... | 10 | 103 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- yue
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- translation
- text-generation
- fill-mask
task_ids:
- dialogue-modeling
paperswithcode_id: hong-kong-ca... | 9,244 | [
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0.045379638671875,
0.049774169921875,
-0.024383544921875,
-0.06768798828125,
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... |
yoruba_gv_ner | 2023-01-25T15:03:39.000Z | [
"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:yo",
"license:cc-by-3.0",
"region:us"
] | null | The Yoruba GV NER dataset is a labeled dataset for named entity recognition in Yoruba. The texts were obtained from
Yoruba Global Voices News articles https://yo.globalvoices.org/ . We concentrate on
four types of named entities: persons [PER], locations [LOC], organizations [ORG], and dates & time [DATE].
The Yoruba ... | @inproceedings{alabi-etal-2020-massive,
title = "Massive vs. Curated Embeddings for Low-Resourced Languages: the Case of {Yorùbá} and {T}wi",
author = "Alabi, Jesujoba and
Amponsah-Kaakyire, Kwabena and
Adelani, David and
Espa{\\~n}a-Bonet, Cristina",
booktitle = "Proceedings of the 12t... | 0 | 103 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- yo
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: Yoruba GV NER Corpus
dat... | 6,184 | [
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... |
Abirate/code_net_dev_dataset | 2021-12-12T09:26:00.000Z | [
"region:us"
] | Abirate | null | null | 1 | 103 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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0.0379... |
Arnold/hausa_common_voice | 2022-02-10T03:28:22.000Z | [
"region:us"
] | Arnold | null | null | 0 | 103 | 2022-03-02T23:29:22 | This dataset is from the common voice corpus 7.0 using the Hausa dataset | 72 | [
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-0.00... |
gabtan99/pex-conversations | 2022-10-20T19:34:29.000Z | [
"task_ids:dialogue-modeling",
"task_ids:language-modeling",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:original",
"language:tl",
"language:fil",
"license:unknown",
"multi-turn",
"region:us"
] | gabtan99 | null | null | 1 | 103 | 2022-03-02T23:29:22 | ---
language:
- tl
- fil
license:
- unknown
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- sequence-modeling
task_ids:
- dialogue-modeling
- language-modeling
pretty_name: PEx Conversations
tags:
- multi-turn
---
# PinoyExchange (PEx) Conversations Dataset
# ... | 1,872 | [
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0.01406860... |
iarfmoose/question_generator | 2021-11-29T05:22:03.000Z | [
"region:us"
] | iarfmoose | null | null | 4 | 103 | 2022-03-02T23:29:22 | This dataset is made up of data taken from SQuAD v2.0, RACE, CoQA, and MSMARCO. Some examples have been filtered out of the original datasets and others have been modified.
There are two fields; question and text. The question field contains the question, and the text field contains both the answer and the context in ... | 655 | [
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0.049591064453125,
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projecte-aina/catalanqa | 2023-09-13T12:45:53.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ca",
"license:cc-by-sa-4.0",
"arxiv:1606.05250",
"region:us"
] | projecte-aina | CatalanQA: an extractive QA dataset from original Catalan Sources: Wikipedia and VilaWeb newswire.
It is an aggregation and balancing of 2 previous datasets: VilaQUAD and ViquiQUAD, which were described in
This dataset can be used to build extractive-QA and Language Models.
Splts have been balanced by kind of ques... | None | 1 | 103 | 2022-06-29T14:22:10 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: catalanqa
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
## Table of Contents
- [Table... | 6,748 | [
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0.01517486572265625... |
SLPL/naab | 2022-11-03T06:33:48.000Z | [
"task_categories:fill-mask",
"task_categories:text-generation",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"multilinguality:monolingual",
"size_categories:100M<n<1B",
"language:fa",
"license:mit",
"arxiv:2208.13486",
"region:us"
] | SLPL | Huge corpora of textual data are always known to be a crucial need for training deep models such as transformer-based ones. This issue is emerging more in lower resource languages - like Farsi. We propose naab, the biggest cleaned and ready-to-use open-source textual corpus in Farsi. It contains about 130GB of data, 25... | @misc{https://doi.org/10.48550/arxiv.2208.13486,
doi = {10.48550/ARXIV.2208.13486},
url = {https://arxiv.org/abs/2208.13486},
author = {Sabouri, Sadra and Rahmati, Elnaz and Gooran, Soroush and Sameti, Hossein},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer ... | 25 | 103 | 2022-08-18T13:47:40 | ---
language:
- fa
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100M<n<1B
task_categories:
- fill-mask
- text-generation
task_ids:
- language-modeling
- masked-language-modeling
pretty_name: naab (A ready-to-use plug-and-play corpus in Farsi)
---
# naab: A ready-to-use plug-and-play corpus in Farsi... | 11,260 | [
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... |
parambharat/mile_dataset | 2022-12-05T11:46:00.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ta",
"license:cc-by-2.0",
"Tamil ASR",
"Speech Recognition",
"arxiv:22... | parambharat | IISc-MILE Tamil ASR Corpus contains transcribed speech corpus for training ASR systems for Tamil language. It contains ~150 hours of read speech data collected from 531 speakers in a noise-free recording environment with high quality USB microphones. | @misc{mile_1,
doi = {10.48550/ARXIV.2207.13331},
url = {https://arxiv.org/abs/2207.13331},
author = {A, Madhavaraj and Pilar, Bharathi and G, Ramakrishnan A},
title = {Subword Dictionary Learning and Segmentation Techniques for Automatic Speech Recognition in Tamil and Kannada},
publisher = {arXiv},
year = ... | 1 | 103 | 2022-12-05T11:37:10 | ---
annotations_creators:
- expert-generated
language:
- ta
language_creators:
- expert-generated
license:
- cc-by-2.0
multilinguality:
- monolingual
pretty_name: IISc-MILE Tamil ASR Corpus
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- Tamil ASR
- Speech Recognition
task_categories:
- automatic-spee... | 3,545 | [
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SZTAKI-HLT/HunSum-1 | 2023-01-24T16:21:00.000Z | [
"task_categories:summarization",
"task_ids:news-articles-summarization",
"multilinguality:monolingual",
"language:hu",
"license:cc-by-nc-sa-4.0",
"region:us"
] | SZTAKI-HLT | null | null | 2 | 103 | 2023-01-06T07:42:26 | ---
language:
- hu
multilinguality:
- monolingual
task_categories:
- summarization
task_ids:
- news-articles-summarization
pretty_name: HunSum-1
license: cc-by-nc-sa-4.0
---
# Dataset Card for HunSum-1
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
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Multimodal-Fatima/FGVC_Aircraft_test | 2023-06-02T02:15:19.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 103 | 2023-01-28T02:49:32 | ---
dataset_info:
features:
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'1': A310
'2': A320
'3': A330
'4': A340
'5': A380
'6': ATR-42
'7': ATR-72
'8': An-12
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Olec/cyber-threat-intelligence_v2 | 2023-04-15T11:00:18.000Z | [
"region:us"
] | Olec | null | null | 4 | 103 | 2023-03-31T15:08:08 | ---
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ztphs980/taptap_datasets | 2023-05-23T12:32:37.000Z | [
"language:en",
"license:mit",
"arxiv:2305.09696",
"region:us"
] | ztphs980 | null | null | 2 | 103 | 2023-05-20T14:34:39 | ---
license: mit
language:
- en
---
This repository contains a total of 483 tabular datasets with meaningful column names collected from OpenML, UCI, and Kaggle platforms. The last column of each dataset is the label column. For more details, please refer to our paper https://arxiv.org/abs/2305.09696.
You can use the ... | 864 | [
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garcianacho/human_genome_csv | 2023-10-04T12:41:28.000Z | [
"task_categories:token-classification",
"license:apache-2.0",
"biology",
"genome",
"human genome",
"bioinformatics",
"region:us"
] | garcianacho | null | null | 0 | 103 | 2023-09-20T08:52:07 | ---
license: apache-2.0
task_categories:
- token-classification
tags:
- biology
- genome
- human genome
- bioinformatics
---
## Human Genome Dataset
Here is a human genome ready to be used to train LLM.
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vishnupriyavr/wiki-movie-plots-with-summaries-faiss-embeddings | 2023-10-08T16:02:50.000Z | [
"region:us"
] | vishnupriyavr | null | null | 0 | 103 | 2023-10-08T16:02:41 | ---
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result-kand2-sdxl-wuerst-karlo/e1cc4189 | 2023-10-23T14:05:26.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | 0 | 103 | 2023-10-23T14:05:25 | ---
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configs:
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path: data/train-*
---
# Dataset Card for "e1cc418... | 455 | [
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bigheiniuJ/JimmyLuAug | 2023-11-03T00:36:31.000Z | [
"region:us"
] | bigheiniuJ | null | null | 0 | 103 | 2023-10-30T17:17:08 | ---
configs:
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bbc_hindi_nli | 2023-01-25T14:27:06.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|bbc__hindi_news_classification",
"language:hi",
"license:mit",
"... | null | This dataset is used to train models for Natural Language Inference Tasks in Low-Resource Languages like Hindi. | @inproceedings{uppal-etal-2020-two,
title = "Two-Step Classification using Recasted Data for Low Resource Settings",
author = "Uppal, Shagun and
Gupta, Vivek and
Swaminathan, Avinash and
Zhang, Haimin and
Mahata, Debanjan and
Gosangi, Rakesh and
Shah, Rajiv Ratn an... | 0 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- hi
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|bbc__hindi_news_classification
task_categories:
- text-classification
task_ids:
- natural-language-inference
pretty_name: BBC Hi... | 9,123 | [
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covid_tweets_japanese | 2023-01-25T14:28:47.000Z | [
"task_categories:text-classification",
"task_ids:fact-checking",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ja",
"license:cc-by-nd-4.0",
"region:us"
] | null | 53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. The original tweets are not contained. Please use Twitter API... | No paper about this dataset is published yet. Please cite this dataset as "鈴木 優: COVID-19 日本語 Twitter データセット （http://www.db.info.gifu-u.ac.jp/covid-19-twitter-dataset/）" | 1 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- ja
license:
- cc-by-nd-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
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task_ids:
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pretty_name: COVID-19 日本語Twitterデータセット (COVID-19 Japanese T... | 5,242 | [
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dyk | 2023-01-25T14:29:39.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:bsd-3-clause",
"region:us"
] | null | The Did You Know (pol. Czy wiesz?) dataset consists of human-annotated question-answer pairs. The task is to predict if the answer is correct. We chose the negatives which have the largest token overlap with a question. | @inproceedings{marcinczuk2013open,
title={Open dataset for development of Polish Question Answering systems},
author={Marcinczuk, Michal and Ptak, Marcin and Radziszewski, Adam and Piasecki, Maciej},
booktitle={Proceedings of the 6th Language & Technology Conference: Human Language Technologies as a Challenge for Compu... | 0 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- bsd-3-clause
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
pretty_name: dyk
dataset_info:
features:
- name: q_id... | 3,552 | [
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event2Mind | 2023-04-05T10:06:10.000Z | [
"task_categories:text2text-generation",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown",
"common-sense-inference",
"arxiv:1805.06939",
"region:us"
] | null | In Event2Mind, we explore the task of understanding stereotypical intents and reactions to events. Through crowdsourcing, we create a large corpus with 25,000 events and free-form descriptions of their intents and reactions, both of the event's subject and (potentially implied) other participants. | @inproceedings{event2Mind,
title={Event2Mind: Commonsense Inference on Events, Intents, and Reactions},
author={Hannah Rashkin and Maarten Sap and Emily Allaway and Noah A. Smith† Yejin Choi},
year={2018}
} | 0 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- unknown
multilinguality:
- monolingual
pretty_name: Event2Mind
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text2text-generation
task_ids: []
paperswithcode_id: event2mind
tags:
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imdb_urdu_reviews | 2023-01-25T14:32:49.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:found",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ur",
"license:odbl",
"region:us"
] | null | Large Movie translated Urdu Reviews Dataset.
This is a dataset for binary sentiment classification containing substantially more data than previous
benchmark datasets. We provide a set of 40,000 highly polar movie reviews for training, and 10,000 for testing.
To increase the availability of sentiment analysis dataset f... | @InProceedings{maas-EtAl:2011:ACL-HLT2011,
author = {Maas, Andrew L. and Daly,nRaymond E. and Pham, Peter T. and Huang, Dan and Ng, Andrew Y...},
title = {Learning Word Vectors for Sentiment Analysis},
month = {June},
year = {2011},
address = {Portland, Oregon, USA},
publisher = {Associati... | 0 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- machine-generated
language:
- ur
license:
- odbl
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: ImDB Urdu Reviews
dataset_info:
feat... | 3,343 | [
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CAiRE/ASCEND | 2022-10-24T12:43:58.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:multilingual",
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"source_datasets:original",
"language:en",
"language:zh",
"license:cc-by-sa-4.0",
"speech-recognition",
"code-s... | CAiRE | ASCEND (A Spontaneous Chinese-English Dataset) introduces a high-quality resource of spontaneous multi-turn conversational dialogue Chinese-English code-switching corpus collected in Hong Kong. ASCEND consists of 10.62 hours of spontaneous speech with a total of ~12.3K utterances. The corpus is split into 3 sets: train... | @inproceedings{lovenia2021ascend,
title = {ASCEND: A Spontaneous Chinese-English Dataset for Code-switching in Multi-turn Conversation},
author = {Lovenia, Holy and Cahyawijaya, Samuel and Winata, Genta Indra and Xu, Peng and Yan, Xu and Liu, Zihan and Frieske, Rita and Yu, Tiezheng and Dai, Wenliang and Bar... | 10 | 102 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- zh
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: 'ASCEND: A Spontaneous Chinese-En... | 3,645 | [
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anuragshas/ur_opus100_processed | 2022-01-30T16:03:56.000Z | [
"region:us"
] | anuragshas | null | null | 1 | 102 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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fvillena/spanish_diagnostics | 2021-05-30T02:32:52.000Z | [
"region:us"
] | fvillena | null | null | 0 | 102 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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roskoN/dailydialog | 2021-08-06T14:14:18.000Z | [
"region:us"
] | roskoN | The DailyDialog dataset as provided in the original form with a bit of preprocessing applied to enable dast prototyping.
The splits are as in the original distribution. | @inproceedings{li2017dailydialog,
title={DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset},
author={Li, Yanran and Su, Hui and Shen, Xiaoyu and Li, Wenjie and Cao, Ziqiang and Niu, Shuzi},
booktitle={Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Lon... | 0 | 102 | 2022-03-02T23:29:22 | # DailyDialog: A Manually Labelled Multi-turn Dialogue Dataset
The data is based on the original distribution ([link to original website](http://yanran.li/dailydialog)) ([link to paper](https://aclanthology.org/I17-1099/)).
It is created as a convenience to enablefaster prototyping.
# License
DailyDialog dataset i... | 581 | [
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zoheb/sketch-scene | 2022-10-30T10:07:48.000Z | [
"task_categories:text-to-image",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:n<10K",
"source_datasets:FS-COCO",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | zoheb | null | null | 13 | 102 | 2022-10-29T18:15:58 | ---
license: cc-by-nc-sa-4.0
language:
- en
language_creators:
- machine-generated
multilinguality:
- monolingual
pretty_name: 'Sketch Scene Descriptions'
size_categories:
- n<10K
source_datasets:
- FS-COCO
tags: []
task_categories:
- text-to-image
task_ids: []
---
# Dataset Card for Sketch Scene Descriptions
_Datase... | 1,412 | [
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bigbio/ask_a_patient | 2022-12-22T15:43:18.000Z | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-4.0",
"region:us"
] | bigbio | The AskAPatient dataset contains medical concepts written on social media mapped to how they are formally written in medical ontologies (SNOMED-CT and AMT). | @inproceedings{limsopatham-collier-2016-normalising,
title = "Normalising Medical Concepts in Social Media Texts by Learning Semantic Representation",
author = "Limsopatham, Nut and
Collier, Nigel",
booktitle = "Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (... | 1 | 102 | 2022-11-13T18:26:06 |
---
language:
- en
bigbio_language:
- English
license: cc-by-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_4p0
pretty_name: AskAPatient
homepage: https://zenodo.org/record/55013
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- NAMED_ENTITY_DISAMBIGUATION
---
# ... | 1,263 | [
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bigbio/chemdner | 2022-12-22T15:44:21.000Z | [
"multilinguality:monolingual",
"language:en",
"license:unknown",
"region:us"
] | bigbio | We present the CHEMDNER corpus, a collection of 10,000 PubMed abstracts that
contain a total of 84,355 chemical entity mentions labeled manually by expert
chemistry literature curators, following annotation guidelines specifically
defined for this task. The abstracts of the CHEMDNER corpus were selected to be
represent... | @article{Krallinger2015,
title = {The CHEMDNER corpus of chemicals and drugs and its annotation principles},
author = {
Krallinger, Martin and Rabal, Obdulia and Leitner, Florian and Vazquez,
Miguel and Salgado, David and Lu, Zhiyong and Leaman, Robert and Lu, Yanan
and Ji, Donghong and Low... | 1 | 102 | 2022-11-13T22:07:46 |
---
language:
- en
bigbio_language:
- English
license: unknown
multilinguality: monolingual
bigbio_license_shortname: UNKNOWN
pretty_name: CHEMDNER
homepage: https://biocreative.bioinformatics.udel.edu/resources/biocreative-iv/chemdner-corpus/
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_REC... | 4,809 | [
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OllieStanley/humaneval-mbpp-codegen-qa | 2023-03-15T15:13:27.000Z | [
"region:us"
] | OllieStanley | null | null | 1 | 102 | 2023-02-26T14:59:10 | ---
dataset_info:
features:
- name: INSTRUCTION
dtype: string
- name: RESPONSE
dtype: string
- name: SOURCE
dtype: string
splits:
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num_bytes: 225572
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download_size: 89931
dataset_size: 225572
---
# Dataset Card for "humaneval-mbpp-codegen-qa"
This datas... | 534 | [
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Francesco/hand-gestures-jps7z | 2023-03-30T09:18:38.000Z | [
"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 | 0 | 102 | 2023-03-30T09:18:16 | ---
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... | 3,654 | [
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rookshanks/gsm8k | 2023-06-21T22:55:22.000Z | [
"region:us"
] | rookshanks | null | null | 0 | 102 | 2023-06-21T22:53:41 | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
splits:
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num_bytes: 3566510.564699585
num_examples: 6725
- name: test
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num_examples: 1319
- name: validation
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eckendoerffer/justice_fr | 2023-09-30T05:38:31.000Z | [
"size_categories:100K<n<1M",
"language:fr",
"license:cc-by-sa-4.0",
"justice",
"law",
"legal",
"region:us"
] | eckendoerffer | null | null | 3 | 102 | 2023-06-26T01:50:11 | ---
license: cc-by-sa-4.0
language:
- fr
pretty_name: Law & decision from French justice system
tags:
- justice
- law
- legal
size_categories:
- 100K<n<1M
---
# Dataset Card for French Legal Dataset
## Dataset Description
The dataset contains a comprehensive collection of French legal books, codes, and appellate cou... | 3,861 | [
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... |
juanivazquez/jivb-id_card | 2023-06-28T01:50:05.000Z | [
"region:us"
] | juanivazquez | null | null | 0 | 102 | 2023-06-28T00:03:05 | ---
dataset_info:
features:
- name: image
dtype: image
- name: ground_truth
dtype: string
splits:
- name: train
num_bytes: 102797866.0
num_examples: 276
- name: test
num_bytes: 6349261.0
num_examples: 11
download_size: 108916611
dataset_size: 109147127.0
---
# Dataset Card for "j... | 465 | [
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pietrolesci/agnews | 2023-09-13T12:02:12.000Z | [
"task_categories:text-classification",
"size_categories:100K<n<1M",
"language:en",
"region:us"
] | pietrolesci | null | null | 0 | 102 | 2023-09-13T10:17:01 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- config_name: embedding_all-MiniLM-L12-v2
data_files:
- split: train
path: embedding_all-MiniLM-L12-v2/train-*
- split: test
path: embedding_all-MiniLM-L12-v2/test-*
- config_na... | 2,711 | [
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0.023... |
codys12/MergeLlama | 2023-10-09T21:43:13.000Z | [
"license:cc-by-4.0",
"region:us"
] | codys12 | null | null | 3 | 102 | 2023-09-29T19:03:11 | ---
license: cc-by-4.0
---
MergeLlama is a unique dataset that encapsulates real-world merge conflicts alongside their corresponding resolutions. Developed from the foundational dataset shared in "Anonymous. (2022). Data set for FSE 2022 Submission Program Merge Conflict Resolution via Neural Transformers", MergeLlama... | 938 | [
[
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portafolio/llamadas-celular-es-03 | 2023-10-23T19:54:50.000Z | [
"region:us"
] | portafolio | null | null | 0 | 102 | 2023-10-23T19:37:53 | Entry not found | 15 | [
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result-kand2-sdxl-wuerst-karlo/31425212 | 2023-10-24T14:14:19.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | 0 | 102 | 2023-10-24T14:14:18 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
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num_bytes: 203
num_examples: 10
download_size: 1410
dataset_size: 203
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "3142521... | 455 | [
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result-kand2-sdxl-wuerst-karlo/a17bd262 | 2023-10-25T02:44:54.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | 0 | 102 | 2023-10-25T02:44:54 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
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num_bytes: 201
num_examples: 10
download_size: 1374
dataset_size: 201
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "a17bd26... | 455 | [
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dialog_re | 2022-11-18T19:58:15.000Z | [
"task_categories:other",
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en"... | null | DialogRE is the first human-annotated dialogue based relation extraction (RE) dataset aiming
to support the prediction of relation(s) between two arguments that appear in a dialogue.
The dataset annotates all occurrences of 36 possible relation types that exist between pairs
of arguments in the 1,788 dialogues originat... | @inproceedings{yu2020dialogue,
title={Dialogue-Based Relation Extraction},
author={Yu, Dian and Sun, Kai and Cardie, Claire and Yu, Dong},
booktitle={Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics},
year={2020},
url={https://arxiv.org/abs/2004.08056v1}
} | 7 | 101 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
- text-generation
- fill-mask
task_ids:
- dialogue-modeling
paperswithcode_id: dialogre
prett... | 7,445 | [
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0.0103... |
leey4n/KR3 | 2023-07-19T08:35:54.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"multilinguality:monolingual",
"size_categories:100K<n<1m",
"language:ko",
"license:cc-by-nc-sa-4.0",
"region:us"
] | leey4n | null | null | 2 | 101 | 2022-03-02T23:29:22 | ---
annotations_creators: []
language_creators: []
language:
- ko
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: KR3
size_categories:
- 100K<n<1m
source_datasets: []
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
### KR3: Korean Restaurant Reviews with Ratings
K... | 2,374 | [
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imvladikon/hebrew_speech_coursera | 2023-05-05T09:05:00.000Z | [
"task_categories:automatic-speech-recognition",
"size_categories:1K<n<10K",
"language:he",
"region:us"
] | imvladikon | null | null | 5 | 101 | 2022-03-02T23:29:22 | ---
task_categories:
- automatic-speech-recognition
language:
- he
dataset_info:
features:
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: sentence
dtype: string
splits:
- name: train
num_bytes: 6670706136.352
num_examples: 20306
- name: validation
num_bytes: 16480... | 2,667 | [
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ShapeNet/ShapeNetCore | 2023-09-20T15:05:48.000Z | [
"language:en",
"license:other",
"3D shapes",
"region:us"
] | ShapeNet | null | null | 15 | 101 | 2022-08-26T09:34:57 | ---
language:
- en
pretty_name: ShapeNetCore
tags:
- 3D shapes
license: other
extra_gated_heading: Acknowledge license to accept the repository
extra_gated_prompt: >-
To request access to this ShapeNet repo, you will need to provide your **full name** (please provide both your first and last name), the name of yo... | 4,236 | [
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hpprc/jsick | 2023-04-11T06:18:09.000Z | [
"task_categories:sentence-similarity",
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:translation",
"size_categories:10K<n<100K",
"so... | hpprc | Japanese Sentences Involving Compositional Knowledge (JSICK) Dataset.
JSICK is the Japanese NLI and STS dataset by manually translating the English dataset SICK (Marelli et al., 2014) into Japanese.
We hope that our dataset will be useful in research for realizing more advanced models that are capable of appropriately ... | @article{yanaka-mineshima-2022-compositional,
title = "Compositional Evaluation on {J}apanese Textual Entailment and Similarity",
author = "Yanaka, Hitomi and Mineshima, Koji",
journal = "Transactions of the Association for Computational Linguistics",
volume = "10",
year = "2022",
address = "Cam... | 4 | 101 | 2023-04-08T16:02:06 | ---
annotations_creators:
- expert-generated
language:
- ja
- en
language_creators:
- expert-generated
license:
- cc-by-sa-4.0
multilinguality:
- translation
pretty_name: JSICK
size_categories:
- 10K<n<100K
source_datasets:
- extended|sick
tags:
- semantic-textual-similarity
- sts
task_categories:
- sentence-similarity... | 13,106 | [
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kunishou/oasst1-89k-ja | 2023-10-27T12:35:40.000Z | [
"language:ja",
"license:apache-2.0",
"region:us"
] | kunishou | null | null | 13 | 101 | 2023-05-06T09:12:30 | ---
license: apache-2.0
language:
- ja
---
This dataset was created by automatically translating "OpenAssistant/oasst1" into Japanese.
The "ng_translation" flag indicates that the translation was not successful, and "1" means that the translation failed.
Therefore, for data with "1", "text" and "text_en" contain... | 3,353 | [
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PeterPanTheGenius/CUHK-PEDES | 2023-07-03T08:37:42.000Z | [
"region:us"
] | PeterPanTheGenius | null | null | 0 | 101 | 2023-07-03T08:23:49 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 4374645533.392
num_examples: 238768
download_size: 575398519
dataset_size: 4374645533.392
---
# Dataset Card for "CUHK-PEDES"
[More Information needed](https://github.com/hug... | 403 | [
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hate_speech_portuguese | 2023-01-25T14:31:44.000Z | [
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] | null | Portuguese dataset for hate speech detection composed of 5,668 tweets with binary annotations (i.e. 'hate' vs. 'no-hate'). | @inproceedings{fortuna-etal-2019-hierarchically,
title = "A Hierarchically-Labeled {P}ortuguese Hate Speech Dataset",
author = "Fortuna, Paula and
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booktitle = "Proceedings of the Third Workshop on Abusive Langu... | 2 | 100 | 2022-03-02T23:29:22 | ---
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hrenwac_para | 2022-11-03T16:07:49.000Z | [
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linnaeus | 2023-06-15T14:40:39.000Z | [
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text2log | 2022-11-03T16:15:15.000Z | [
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benjaminbeilharz/better_daily_dialog | 2022-01-22T18:03:59.000Z | [
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ett | 2022-11-18T22:07:07.000Z | [
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Shuai Zhang and
Jianxin Li and
Hui Xiong and
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title = {Informer: Beyond Efficient Transformer for Long Se... | 3 | 100 | 2022-05-05T12:12:41 | ---
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bigbio/an_em | 2022-12-22T15:43:14.000Z | [
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doi ... | 1 | 100 | 2022-11-13T18:05:07 |
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bigbio/genia_ptm_event_corpus | 2022-12-22T15:44:39.000Z | [
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"language:en",
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] | bigbio | Post-translational-modifications (PTM), amino acid modifications of proteins after translation, are one of the posterior processes of protein biosynthesis for many proteins, and they are critical for determining protein function such as its activity state, localization, turnover and interactions with other biomolecules. ... | @inproceedings{ohta-etal-2010-event,
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Kim, Jin-Dong and
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booktitle = "Proceedings of the 2010 Workshop on Biomedical Natural Language... | 1 | 100 | 2022-11-13T22:08:36 |
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language:
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multilinguality: monolingual
bigbio_license_shortname: GENIA_PROJECT_LICENSE
pretty_name: PTM Events
homepage: http://www.geniaproject.org/other-corpora/ptm-event-corpus
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- CO... | 1,662 | [
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irds/cranfield | 2023-01-05T03:01:23.000Z | [
"task_categories:text-retrieval",
"region:us"
] | irds | null | null | 0 | 100 | 2023-01-05T03:01:17 | ---
pretty_name: '`cranfield`'
viewer: false
source_datasets: []
task_categories:
- text-retrieval
---
# Dataset Card for `cranfield`
The `cranfield` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-datasets.com/cranfi... | 1,155 | [
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Multimodal-Fatima/StanfordCars_test | 2023-06-12T02:33:45.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 100 | 2023-01-28T02:30:24 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': am general hummer suv 2000
'1': acura rl sedan 2012
'2': acura tl sedan 2012
'3': acura tl type-s 2008
'4': acura tsx sedan 2012
'5... | 10,572 | [
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-0... |
Francesco/animals-ij5d2 | 2023-03-30T09:30:09.000Z | [
"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 | 4 | 100 | 2023-03-30T09:29:48 | ---
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... | 3,545 | [
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lucadiliello/wikiqa_grouped | 2023-05-30T08:14:53.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"region:us"
] | lucadiliello | null | null | 0 | 100 | 2023-05-30T08:12:28 | ---
task_categories:
- text-classification
language:
- en
pretty_name: WikiQA
size_categories:
- 1K<n<10K
---
WikiQA dataset with answers grouped together for each question. | 173 | [
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0.0290... |
truehealth/medicationqa | 2023-06-12T14:24:14.000Z | [
"region:us"
] | truehealth | null | null | 1 | 100 | 2023-06-12T11:28:52 | ---
dataset_info:
features:
- name: Question
dtype: string
- name: Focus (Drug)
dtype: string
- name: Question Type
dtype: string
- name: Answer
dtype: string
- name: Section Title
dtype: string
- name: URL
dtype: string
splits:
- name: train
num_bytes: 403030
num_examp... | 541 | [
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xin1997/vulfix_real_deduplicated | 2023-07-02T05:34:34.000Z | [
"region:us"
] | xin1997 | null | null | 0 | 100 | 2023-07-02T05:33:58 | Entry not found | 15 | [
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facat/sci-llm-part | 2023-10-07T13:33:53.000Z | [
"region:us"
] | facat | null | null | 1 | 100 | 2023-10-04T06:21:06 | ---
configs:
- config_name: default
data_files:
- split: gpt1
path: data/gpt1-*
- split: gpt2
path: data/gpt2-*
- split: gpt3
path: data/gpt3-*
- split: gpt4
path: data/gpt4-*
- split: gpt5
path: data/gpt5-*
- split: gpt6
path: data/gpt6-*
- split: han_40k
path: data/han_40k-... | 1,570 | [
[
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-0.0036735... |
hheiden/us-congress-117-bills | 2023-10-06T23:27:47.000Z | [
"task_categories:text-classification",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"legal",
"doi:10.57967/hf/1193",
"region:us"
] | hheiden | null | null | 1 | 100 | 2023-10-06T22:38:16 | ---
license: mit
task_categories:
- text-classification
language:
- en
tags:
- legal
pretty_name: US 117th Congress Bills
size_categories:
- 10K<n<100K
---
# Dataset Card for Dataset US 117th Congress Bills
## Dataset Description
- **Homepage:** https://hunterheidenreich.com/posts/us-117th-congress-data-exploration/... | 5,051 | [
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... |
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