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 |
|---|---|---|---|---|---|---|---|---|---|
open-llm-leaderboard/details_meta-llama__Llama-2-70b-hf | 2023-09-18T06:46:57.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 781 | ---
pretty_name: Evaluation run of meta-llama/Llama-2-70b-hf
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [meta-llama/Llama-2-70b-hf](https://huggingface.co/meta-llama/Llama-2-70b-hf)\
\ on the [Open LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leade... |
result-kand2-sdxl-wuerst-karlo/323c0619 | 2023-09-15T06:43:16.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 779 | ---
dataset_info:
features:
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dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 236
num_examples: 10
download_size: 1424
dataset_size: 236
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "323c061... |
clarin-pl/polemo2-official | 2022-08-29T16:40:01.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:8K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:cc-by-sa-4.0",
"reg... | clarin-pl | PolEmo 2.0: Corpus of Multi-Domain Consumer Reviews, evaluation data for article presented at CoNLL. | @inproceedings{kocon-etal-2019-multi,
title = "Multi-Level Sentiment Analysis of {P}ol{E}mo 2.0: Extended Corpus of Multi-Domain Consumer Reviews",
author = "Koco{\'n}, Jan and
Mi{\l}kowski, Piotr and
Za{\'s}ko-Zieli{\'n}ska, Monika",
booktitle = "Proceedings of the 23rd Conference on Computat... | null | 4 | 778 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: 'Polemo2'
size_categories:
- 8K
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
---
# P... |
result-kand2-sdxl-wuerst-karlo/f0cdf5c4 | 2023-09-15T09:18:20.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 776 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 207
num_examples: 10
download_size: 1427
dataset_size: 207
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "f0cdf5c... |
dkoterwa/kor-sts | 2023-07-25T09:52:30.000Z | [
"license:cc-by-sa-4.0",
"region:us"
] | dkoterwa | null | null | null | 0 | 775 | ---
license: cc-by-sa-4.0
dataset_info:
features:
- name: id
dtype: int64
- name: genre
dtype: string
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: float64
splits:
- name: train
num_bytes: 1034815
num_examples: 5691
- name: valid
n... |
SetFit/mrpc | 2022-02-28T13:18:30.000Z | [
"region:us"
] | SetFit | null | null | null | 4 | 774 | # Glue MRPC
This dataset is a port of the official [`mrpc` dataset](https://huggingface.co/datasets/glue/viewer/mrpc/train) on the Hub.
Note that the sentence1 and sentence2 columns have been renamed to text1 and text2 respectively.
Also, the test split is not labeled; the label column values are always -1.
|
result-kand2-sdxl-wuerst-karlo/d6e12779 | 2023-09-15T09:41:14.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 774 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 208
num_examples: 10
download_size: 1403
dataset_size: 208
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "d6e1277... |
result-kand2-sdxl-wuerst-karlo/a350d62a | 2023-09-15T11:08:21.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 774 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 179
num_examples: 10
download_size: 1365
dataset_size: 179
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "a350d62... |
rewoo/planner_instruction_tuning_2k | 2023-05-22T04:54:20.000Z | [
"license:mit",
"region:us"
] | rewoo | null | null | null | 15 | 771 | ---
license: mit
---
*Bootstrap 2k Planner finetuning dataset for ReWOO.*
It is a mixture of "correct" HotpotQA and TriviaQA task planning trajectories in ReWOO Framework. |
result-kand2-sdxl-wuerst-karlo/e395fcfb | 2023-09-15T15:42:19.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 771 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 152
num_examples: 10
download_size: 1308
dataset_size: 152
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "e395fcf... |
Alanox/stanford-dogs | 2023-09-08T13:51:01.000Z | [
"license:mit",
"region:us"
] | Alanox | The Stanford Dogs dataset contains images of 120 breeds of dogs from around the world. This dataset has been built using images and annotation from ImageNet for the task of fine-grained image categorization. | null | null | 1 | 769 | ---
pretty_name: "Stanford Dogs"
license: "mit"
task_category: "Classification"
---
# Dataset
This dataset is extracted from [Stanford Dogs Dataset](http://vision.stanford.edu/aditya86/ImageNetDogs/)
# Load
```python
import datasets
dataset = datasets.load_dataset("Alanox/stanford-dogs", split="full")
print(datas... |
result-kand2-sdxl-wuerst-karlo/94daaaa5 | 2023-09-15T16:14:38.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 769 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
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- name: train
num_bytes: 198
num_examples: 10
download_size: 1363
dataset_size: 198
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "94daaaa... |
Dahoas/hf_cot_gsm8k | 2023-10-01T14:40:46.000Z | [
"region:us"
] | Dahoas | null | null | null | 0 | 768 | ---
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: prompt
dtype: string
- name: response
dtype: string
splits:
- name: train
num_bytes: 8663589
num_examples: 7217
- name: val
num_bytes: 301562
num_examples: 256
- name: test
... |
result-kand2-sdxl-wuerst-karlo/e06f76e8 | 2023-09-15T18:17:10.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 766 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 169
num_examples: 10
download_size: 1323
dataset_size: 169
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "e06f76e... |
tner/bionlp2004 | 2022-08-10T01:01:51.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:other",
"region:us"
] | tner | [BioNLP2004 NER dataset](https://aclanthology.org/W04-1213.pdf) | @inproceedings{collier-kim-2004-introduction,
title = "Introduction to the Bio-entity Recognition Task at {JNLPBA}",
author = "Collier, Nigel and
Kim, Jin-Dong",
booktitle = "Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications ({NLPBA}/{B... | null | 2 | 764 | ---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: BioNLP2004
---
# Dataset Card for "tner/bionlp2004"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/t... |
result-kand2-sdxl-wuerst-karlo/bbe01f48 | 2023-09-15T18:27:46.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 764 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 217
num_examples: 10
download_size: 1377
dataset_size: 217
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "bbe01f4... |
cambridgeltl/vsr_zeroshot | 2023-03-22T17:27:58.000Z | [
"task_categories:text-classification",
"task_categories:question-answering",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"multimodal",
"vision-and-language",
"arxiv:2205.00363",
"region:us"
] | cambridgeltl | null | null | null | 1 | 763 | ---
license: cc-by-4.0
task_categories:
- text-classification
- question-answering
language:
- en
tags:
- multimodal
- vision-and-language
pretty_name: VSR (zeroshot)
size_categories:
- 1K<n<10K
---
# VSR: Visual Spatial Reasoning
This is the **zero-shot set** of **VSR**: *Visual Spatial Reasoning* (TACL 2023) [[pape... |
C-MTEB/T2Retrieval | 2023-07-28T10:11:06.000Z | [
"region:us"
] | C-MTEB | null | null | null | 0 | 761 | ---
configs:
- config_name: default
data_files:
- split: corpus
path: data/corpus-*
- split: queries
path: data/queries-*
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: corpus
num_bytes: 265607316
num_examples: 118605
- name: queries... |
teven/enwiki_100k | 2023-04-03T17:16:55.000Z | [
"region:us"
] | teven | null | null | null | 1 | 755 | ---
dataset_info:
features:
- name: metadata
dtype: string
- name: text
dtype: string
- name: id
dtype: string
splits:
- name: train
num_bytes: 2570893740
num_examples: 1000000
download_size: 1550572660
dataset_size: 2570893740
---
# Dataset Card for "enwiki_100k"
[More Information ... |
fantasyfish/laion-art | 2023-06-30T08:55:13.000Z | [
"region:us"
] | fantasyfish | null | null | null | 0 | 755 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: aesthetic
dtype: float64
splits:
- name: train
num_bytes: 11640624315.8
num_examples: 20072
- name: test
num_bytes: 538961083.0
num_examples: 855
download_size: 12347056207
dataset_siz... |
mstz/heart_failure | 2023-04-16T17:31:15.000Z | [
"task_categories:tabular-classification",
"size_categories:n<1K",
"language:en",
"license:cc",
"heart failure",
"tabular_classification",
"binary_classification",
"UCI",
"region:us"
] | mstz | null | null | null | 2 | 754 | ---
language:
- en
tags:
- heart failure
- tabular_classification
- binary_classification
- UCI
pretty_name: Heart failure
size_categories:
- n<1K
task_categories:
- tabular-classification
configs:
- death
license: cc
---
# Heart failure
The [Heart failure dataset](https://www.kaggle.com/datasets/andrewmvd/heart-failur... |
result-kand2-sdxl-wuerst-karlo/1d35978a | 2023-09-16T01:30:03.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 754 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 163
num_examples: 10
download_size: 1301
dataset_size: 163
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "1d35978... |
mteb/biosses-sts | 2022-09-27T19:13:38.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 0 | 752 | ---
language:
- en
--- |
wdc/products-2017 | 2022-10-23T05:50:24.000Z | [
"task_categories:text-classification",
"annotations_creators:weak supervision",
"annotations_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | wdc | Many e-shops have started to mark-up product data within their HTML pages using the schema.org vocabulary. The Web Data Commons project regularly extracts such data from the Common Crawl, a large public web crawl. The Web Data Commons Training and Test Sets for Large-Scale Product Matching contain product offers from d... | @inproceedings{primpeli2019wdc,
title={The WDC training dataset and gold standard for large-scale product matching},
author={Primpeli, Anna and Peeters, Ralph and Bizer, Christian},
booktitle={Companion Proceedings of The 2019 World Wide Web Conference},
pages={381--386},
year={2019}
} | null | 1 | 751 | ---
annotations_creators:
- weak supervision
- expert-generated
language:
- en
language_bcp47:
- en-US
license:
- unknown
multilinguality:
- monolingual
pretty_name: products-2017
size_categories:
- 1K<n<10K
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
- data-integration
task_ids:
- ... |
madao33/new-title-chinese | 2022-07-01T06:26:15.000Z | [
"region:us"
] | madao33 | null | null | null | 1 | 751 | Entry not found |
BeIR/nfcorpus | 2022-10-23T06:01:44.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | null | 0 | 745 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... |
C-MTEB/T2Retrieval-qrels | 2023-07-28T10:11:11.000Z | [
"region:us"
] | C-MTEB | null | null | null | 0 | 744 | ---
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
dataset_info:
features:
- name: qid
dtype: string
- name: pid
dtype: string
- name: score
dtype: int64
splits:
- name: dev
num_bytes: 3133383
num_examples: 118932
download_size: 1146734
dataset_size... |
result-kand2-sdxl-wuerst-karlo/a48196ad | 2023-09-16T10:13:26.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 744 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 155
num_examples: 10
download_size: 1306
dataset_size: 155
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "a48196a... |
result-kand2-sdxl-wuerst-karlo/8e18a25b | 2023-09-16T15:18:38.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 739 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 191
num_examples: 10
download_size: 1358
dataset_size: 191
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "8e18a25... |
result-kand2-sdxl-wuerst-karlo/a2d1bcf0 | 2023-09-16T15:16:31.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 738 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 220
num_examples: 10
download_size: 1379
dataset_size: 220
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "a2d1bcf... |
aqua_rat | 2022-11-18T18:20:44.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:apache-... | null | A large-scale dataset consisting of approximately 100,000 algebraic word problems.
The solution to each question is explained step-by-step using natural language.
This data is used to train a program generation model that learns to generate the explanation,
while generating the program that solves the question. | @InProceedings{ACL,
title = {Program induction by rationale generation: Learning to solve and explain algebraic word problems},
authors={Ling, Wang and Yogatama, Dani and Dyer, Chris and Blunsom, Phil},
year={2017}
} | null | 7 | 734 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- expert-generated
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: aqua-rat
pre... |
covost2 | 2022-11-18T19:46:56.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:extended|other-common-voice",
"language:ar",
"language:ca",
... | null | CoVoST 2, a large-scale multilingual speech translation corpus covering translations from 21 languages into English and from English into 15 languages. The dataset is created using Mozilla’s open source Common Voice database of crowdsourced voice recordings.
Note that in order to limit the required storage for prepari... | @misc{wang2020covost,
title={CoVoST 2: A Massively Multilingual Speech-to-Text Translation Corpus},
author={Changhan Wang and Anne Wu and Juan Pino},
year={2020},
eprint={2007.10310},
archivePrefix={arXiv},
primaryClass={cs.CL} | null | 6 | 734 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- ar
- ca
- cy
- de
- es
- et
- fa
- fr
- id
- it
- ja
- lv
- mn
- nl
- pt
- ru
- sl
- sv
- ta
- tr
- zh
language_bcp47:
- sv-SE
- zh-CN
license:
- cc-by-nc-4.0
multilinguality:
- multilingual
size_categories:
- ... |
health_fact | 2023-01-25T14:32:02.000Z | [
"task_categories:text-classification",
"task_ids:fact-checking",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"arxi... | null | PUBHEALTH is a comprehensive dataset for explainable automated fact-checking of
public health claims. Each instance in the PUBHEALTH dataset has an associated
veracity label (true, false, unproven, mixture). Furthermore each instance in the
dataset has an explanation text field. The explanation is a justification for w... | @inproceedings{kotonya-toni-2020-explainable,
title = "Explainable Automated Fact-Checking for Public Health Claims",
author = "Kotonya, Neema and Toni, Francesca",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods
in Natural Language Processing (EMNLP)",
month = nov,
year = "... | null | 14 | 734 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- fact-checking
- multi-class-classification
paperswithcode_id: pubhealth
pretty... |
teknium/GPT4-LLM-Cleaned | 2023-05-04T01:48:35.000Z | [
"region:us"
] | teknium | null | null | null | 84 | 734 | This is the GPT4-LLM dataset from : https://github.com/Instruction-Tuning-with-GPT-4/GPT-4-LLM
It has been filtered of all OpenAI disclaimers and refusals. (Disclaimer: It may have removed some additional things besides just OAI disclaimers, as I used the followings script which is a bit more broad: https://huggingfac... |
marsyas/gtzan | 2022-11-06T20:34:20.000Z | [
"region:us"
] | marsyas | GTZAN is a dataset for musical genre classification of audio signals. The dataset consists of 1,000 audio tracks, each of 30 seconds long. It contains 10 genres, each represented by 100 tracks. The tracks are all 22,050Hz Mono 16-bit audio files in WAV format. The genres are: blues, classical, country, disco, hiphop, j... | @misc{tzanetakis_essl_cook_2001,
author = "Tzanetakis, George and Essl, Georg and Cook, Perry",
title = "Automatic Musical Genre Classification Of Audio Signals",
url = "http://ismir2001.ismir.net/pdf/tzanetakis.pdf",
publisher = "The International Society for Music Information Retrieval",
year = "200... | null | 5 | 732 | ---
pretty_name: GTZAN
---
# Dataset Card for GTZAN
## Table of Contents
- [Dataset Card for GTZAN](#dataset-card-for-gtzan)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Languages](#languages)
- [Dataset Structure](#data... |
result-kand2-sdxl-wuerst-karlo/fbc48c23 | 2023-09-16T20:33:59.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 732 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 169
num_examples: 10
download_size: 1322
dataset_size: 169
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "fbc48c2... |
svhn | 2023-01-25T14:45:04.000Z | [
"task_categories:image-classification",
"task_categories:object-detection",
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:machine-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",... | null | SVHN is a real-world image dataset for developing machine learning and object recognition algorithms with minimal requirement on data preprocessing and formatting.
It can be seen as similar in flavor to MNIST (e.g., the images are of small cropped digits), but incorporates an order of magnitude more labeled data (over ... | @article{netzer2011reading,
title={Reading digits in natural images with unsupervised feature learning},
author={Netzer, Yuval and Wang, Tao and Coates, Adam and Bissacco, Alessandro and Wu, Bo and Ng, Andrew Y},
year={2011}
} | null | 9 | 731 | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- machine-generated
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- image-classification
- object-detection
task_ids: []
paperswithcode_id: svhn
... |
OxAISH-AL-LLM/wiki_toxic | 2022-09-19T15:53:19.000Z | [
"task_categories:text-classification",
"task_ids:hate-speech-detection",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|other",
"language:en",
"license:cc0-1.0",
"wikipedia",
"toxicity",
"tox... | OxAISH-AL-LLM | Jigsaw Toxic Comment Challenge dataset. This dataset was the basis of a Kaggle competition run by Jigsaw | """
_DESCRIPTION = | null | 8 | 729 | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- cc0-1.0
multilinguality:
- monolingual
pretty_name: Toxic Wikipedia Comments
size_categories:
- 100K<n<1M
source_datasets:
- extended|other
tags:
- wikipedia
- toxicity
- toxic comments
task_categories:
- text-classification
t... |
wiki_snippets | 2023-04-05T13:43:20.000Z | [
"task_categories:text-generation",
"task_categories:other",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:extended|wiki40b",
"source_datasets:extended|wikipedia",
... | null | Wikipedia version split into plain text snippets for dense semantic indexing. | @ONLINE {wikidump,
author = {Wikimedia Foundation},
title = {Wikimedia Downloads},
url = {https://dumps.wikimedia.org}
} | null | 0 | 728 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- multilingual
pretty_name: WikiSnippets
size_categories:
- 10M<n<100M
source_datasets:
- extended|wiki40b
- extended|wikipedia
task_categories:
- text-generation
- other
task_ids:
- language-m... |
result-kand2-sdxl-wuerst-karlo/0dc6521d | 2023-09-16T23:57:15.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 727 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 166
num_examples: 10
download_size: 1304
dataset_size: 166
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "0dc6521... |
amitness/sentiment-mt | 2023-08-15T10:39:03.000Z | [
"language:mt",
"region:us"
] | amitness | null | null | null | 0 | 726 | ---
language: mt
dataset_info:
features:
- name: label
dtype:
class_label:
names:
'0': negative
'1': positive
- name: text
dtype: string
splits:
- name: train
num_bytes: 83382
num_examples: 595
- name: validation
num_bytes: 11602
num_examples: 85
-... |
thesistranslation/wmt14 | 2023-08-09T13:08:40.000Z | [
"region:us"
] | thesistranslation | null | @InProceedings{bojar-EtAl:2014:W14-33,
author = {Bojar, Ondrej and Buck, Christian and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Leveling, Johannes and Monz, Christof and Pecina, Pavel and Post, Matt and Saint-Amand, Herve and Soricut, Radu and Specia, Lucia and Tamchyna... | null | 0 | 722 | # Aim of this dataset
The code used to retrieve and create this dataset is almost identical to the one that you can find here [wmt14](https://huggingface.co/datasets/wmt14).
We only added the possibility to retrieve the "es-en" translation pairs from the wmt13. Keep in mind that for this language pair the validation an... |
sem_eval_2010_task_8 | 2023-04-05T13:39:59.000Z | [
"language:en",
"region:us"
] | null | The SemEval-2010 Task 8 focuses on Multi-way classification of semantic relations between pairs of nominals.
The task was designed to compare different approaches to semantic relation classification
and to provide a standard testbed for future research. | @inproceedings{hendrickx-etal-2010-semeval,
title = "{S}em{E}val-2010 Task 8: Multi-Way Classification of Semantic Relations between Pairs of Nominals",
author = "Hendrickx, Iris and
Kim, Su Nam and
Kozareva, Zornitsa and
Nakov, Preslav and
{\'O} S{\'e}aghdha, Diarmuid and
Pad... | null | 4 | 721 | ---
language:
- en
paperswithcode_id: semeval-2010-task-8
pretty_name: SemEval-2010 Task 8
dataset_info:
features:
- name: sentence
dtype: string
- name: relation
dtype:
class_label:
names:
'0': Cause-Effect(e1,e2)
'1': Cause-Effect(e2,e1)
'2': Component-Whole(e... |
result-kand2-sdxl-wuerst-karlo/76e05263 | 2023-09-17T02:45:19.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 721 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 197
num_examples: 10
download_size: 1361
dataset_size: 197
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "76e0526... |
deepset/prompt-injections | 2023-07-31T15:04:06.000Z | [
"region:us"
] | deepset | null | null | null | 15 | 720 | ---
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
splits:
- name: train
num_bytes: 71720
num_examples: 546
- name: test
num_bytes: 15981
num_examples: 116
download_size: 51215
dataset_size: 87701
license: cc-by-4.0
---
# Dataset Card for "deberta... |
liar | 2023-01-25T14:34:21.000Z | [
"task_categories:text-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:unknown",
"fake-news-detection",
"arxiv:1705.00648",
"region:us"
] | null | LIAR is a dataset for fake news detection with 12.8K human labeled short statements from politifact.com's API, and each statement is evaluated by a politifact.com editor for its truthfulness. The distribution of labels in the LIAR dataset is relatively well-balanced: except for 1,050 pants-fire cases, the instances for... | @inproceedings{wang-2017-liar,
title = "{``}Liar, Liar Pants on Fire{''}: A New Benchmark Dataset for Fake News Detection",
author = "Wang, William Yang",
booktitle = "Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)",
month = jul,
year = "2017",
address =... | null | 4 | 717 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
paperswithcode_id: liar
pretty_name: LIAR
tags:
- fake-news-detection
dat... |
EleutherAI/fever | 2023-04-30T00:09:28.000Z | [
"task_categories:text-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:extended|wikipedia",
"language:en",
"license:cc-by-sa-3.0",
"license:gpl-3.0",
"knowledge-verification",
"region:us"... | EleutherAI | null | null | null | 1 | 717 | ---
language:
- en
paperswithcode_id: fever
annotations_creators:
- crowdsourced
language_creators:
- found
license:
- cc-by-sa-3.0
- gpl-3.0
multilinguality:
- monolingual
pretty_name: FEVER
size_categories:
- 100K<n<1M
source_datasets:
- extended|wikipedia
task_categories:
- text-classification
task_ids: []
tags:
- k... |
cdminix/libritts-aligned | 2023-09-19T06:13:05.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:text-to-speech",
"annotations_creators:crowdsourced",
"language:en",
"license:cc-by-4.0",
"speech",
"audio",
"automatic-speech-recognition",
"text-to-speech",
"arxiv:1904.02882",
"arxiv:2211.16049",
"region:us"
] | cdminix | Dataset used for loading TTS spectrograms and waveform audio with alignments and a number of configurable "measures", which are extracted from the raw audio. | @article{zen2019libritts,
title={LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech},
author={Zen, Heiga and Dang, Viet and Clark, Rob and Zhang, Yu and Weiss, Ron J and Jia, Ye and Chen, Zhifeng and Wu, Yonghui},
journal={Interspeech},
year={2019}
}
@article{https://doi.org/10.48550/arxiv.2211.1604... | null | 3 | 717 | ---
pretty_name: LibriTTS Corpus with Forced Alignments
annotations_creators:
- crowdsourced
language: en
tags:
- speech
- audio
- automatic-speech-recognition
- text-to-speech
license:
- cc-by-4.0
task_categories:
- automatic-speech-recognition
- text-to-speech
extra_gated_prompt: "When using this dataset to download ... |
asset | 2023-06-01T14:59:51.000Z | [
"task_categories:text-classification",
"task_categories:text2text-generation",
"task_ids:text-simplification",
"annotations_creators:machine-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"source_datasets:extended|other-t... | null | ASSET is a dataset for evaluating Sentence Simplification systems with multiple rewriting transformations,
as described in "ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations".
The corpus is composed of 2000 validation and 359 test original sentences tha... | @inproceedings{alva-manchego-etal-2020-asset,
title = "{ASSET}: {A} Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations",
author = "Alva-Manchego, Fernando and
Martin, Louis and
Bordes, Antoine and
Scarton, Carolina and
Sagot, B... | null | 9 | 716 | ---
annotations_creators:
- machine-generated
language_creators:
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
- extended|other-turkcorpus
task_categories:
- text-classification
- text2text-generation
task_ids:
- text-simplification... |
shibing624/nli_zh | 2022-10-30T06:30:56.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"task_ids:text-scoring",
"annotations_creators:shibing624",
"language_creators:shibing624",
"multilinguality:monolingual",
"size_categories:100K<n<20M",
"source_datasets:https://gith... | shibing624 | 纯文本数据，格式：（sentence1， sentence2， label）。常见中文语义匹配数据集，包含ATEC、BQ、LCQMC、PAWSX、STS-B共5个任务。 | null | null | 32 | 714 | ---
annotations_creators:
- shibing624
language_creators:
- shibing624
language:
- zh
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 100K<n<20M
source_datasets:
- https://github.com/shibing624/text2vec
- https://github.com/IceFlameWorm/NLP_Datasets/tree/master/ATEC
- http://icrc.hitsz.edu.cn/inf... |
open-llm-leaderboard/details_lmsys__vicuna-7b-v1.3 | 2023-08-27T12:30:19.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | null | 0 | 713 | ---
pretty_name: Evaluation run of lmsys/vicuna-7b-v1.3
dataset_summary: "Dataset automatically created during the evaluation run of model\
\ [lmsys/vicuna-7b-v1.3](https://huggingface.co/lmsys/vicuna-7b-v1.3) on the [Open\
\ LLM Leaderboard](https://huggingface.co/spaces/HuggingFaceH4/open_llm_leaderboard).\n\
\... |
NumbersStation/NSText2SQL | 2023-07-11T05:26:13.000Z | [
"task_categories:text2text-generation",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"language:en",
"license:other",
"text-to-sql",
"region:us"
] | NumbersStation | null | null | null | 24 | 712 | ---
language:
- en
task_categories:
- text2text-generation
license:
- other
language_creators:
- crowdsourced
- expert-generated
multilinguality:
- multilingual
tags:
- text-to-sql
size_categories:
- 100K<n<1M
pretty_name: NSText2SQL
---
# Dataset Summary
NSText2SQL dataset used to train [NSQL](https:/... |
mozilla-foundation/common_voice_6_1 | 2023-07-29T16:00:07.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"source_datasets:extended|common_voice",
"license:cc0-1.0",
"arxiv:1912.06670",
"region:us"
] | mozilla-foundation | null | @inproceedings{commonvoice:2020,
author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
title = {Common Voice: A Massively-Multilingual Speech Corpus},
booktitle = {Proceedings of the 12th Conference on Lang... | null | 4 | 710 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
license:
- cc0-1.0
multilinguality:
- multilingual
size_categories:
ab:
- n<1K
ar:
- 10K<n<100K
as:
- n<1K
br:
- 10K<n<100K
ca:
- 100K<n<1M
cnh:
- 1K<n<10K
cs:
- 10K<n<100K
cv:
- 10K<n<100K
cy:
- 10K<n<100K
... |
nahyeon00/SQUAD | 2023-07-19T08:51:16.000Z | [
"region:us"
] | nahyeon00 | null | null | null | 0 | 710 | Entry not found |
Jean-Baptiste/wikiner_fr | 2023-06-26T15:33:17.000Z | [
"task_categories:token-classification",
"language:fr",
"region:us"
] | Jean-Baptiste | null | null | null | 3 | 709 | ---
language:
- fr
dataset_info:
features:
- name: id
dtype: int64
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': LOC
'2': PER
'3': MISC
'4': ORG
splits:
- name: test
num_bytes: 595470... |
result-kand2-sdxl-wuerst-karlo/b73eb60b | 2023-09-17T14:04:09.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 709 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 206
num_examples: 10
download_size: 1380
dataset_size: 206
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "b73eb60... |
wiki40b | 2023-04-05T13:43:07.000Z | [
"language:en",
"region:us"
] | null | Clean-up text for 40+ Wikipedia languages editions of pages
correspond to entities. The datasets have train/dev/test splits per language.
The dataset is cleaned up by page filtering to remove disambiguation pages,
redirect pages, deleted pages, and non-entity pages. Each example contains the
wikidata id of the entity, ... | null | 8 | 708 | ---
language:
- en
paperswithcode_id: wiki-40b
pretty_name: Wiki-40B
dataset_info:
features:
- name: wikidata_id
dtype: string
- name: text
dtype: string
- name: version_id
dtype: string
config_name: en
splits:
- name: train
num_bytes: 9423623904
num_examples: 2926536
- name: validat... | |
Yijia-Xiao/pii-medical_flashcards | 2023-09-12T22:24:20.000Z | [
"region:us"
] | Yijia-Xiao | null | null | null | 1 | 706 | ---
dataset_info:
features:
- name: input
dtype: string
- name: output
dtype: string
- name: instruction
dtype: string
- name: cleaned_output
dtype: string
splits:
- name: train
num_bytes: 28620193
num_examples: 33955
download_size: 12411702
dataset_size: 28620193
configs:
- co... |
result-kand2-sdxl-wuerst-karlo/00dbfb2c | 2023-09-17T14:41:51.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 706 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 240
num_examples: 10
download_size: 1450
dataset_size: 240
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "00dbfb2... |
wiki_lingua | 2023-06-16T14:39:41.000Z | [
"task_categories:summarization",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ar",
"language:cs",
"language:de",
"language:en",
"language:es... | null | WikiLingua is a large-scale multilingual dataset for the evaluation of
cross-lingual abstractive summarization systems. The dataset includes ~770k
article and summary pairs in 18 languages from WikiHow. The gold-standard
article-summary alignments across languages was done by aligning the images
that are used to descri... | @inproceedings{ladhak-etal-2020-wikilingua,
title = "{W}iki{L}ingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarization",
author = "Ladhak, Faisal and
Durmus, Esin and
Cardie, Claire and
McKeown, Kathleen",
booktitle = "Findings of the Association for Computational Ling... | null | 23 | 704 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- ar
- cs
- de
- en
- es
- fr
- hi
- id
- it
- ja
- ko
- nl
- pt
- ru
- th
- tr
- vi
- zh
license:
- cc-by-3.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
- 1K<n<10K
source_datasets:
- original
task_categories:
- summ... |
nomic-ai/gpt4all-j-prompt-generations | 2023-04-24T15:20:43.000Z | [
"size_categories:100K<n<1M",
"language:en",
"license:apache-2.0",
"region:us"
] | nomic-ai | null | null | null | 159 | 699 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: response
dtype: string
- name: source
dtype: string
splits:
- name: train
num_bytes: 1774285641
num_examples: 808812
download_size: 990673616
dataset_size: 1774285641
license: apache-2.0
language:
- en
size_categories:
... |
result-kand2-sdxl-wuerst-karlo/8edb1fe9 | 2023-09-18T04:48:26.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 697 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 258
num_examples: 10
download_size: 1429
dataset_size: 258
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "8edb1fe... |
tilyupo/trivia_qa | 2023-08-03T17:00:54.000Z | [
"region:us"
] | tilyupo | null | null | null | 0 | 696 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: question
dtype: string
- name: question_id
dtype: string
- name: question_source
dtype: string
- name: answer
struct:
... |
e2e_nlg_cleaned | 2022-11-18T19:59:46.000Z | [
"task_categories:text2text-generation",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"meaning-representation-to-text",
"arxiv:1706.09254",
"ar... | null | An update release of E2E NLG Challenge data with cleaned MRs and scripts, accompanying the following paper:
Ondřej Dušek, David M. Howcroft, and Verena Rieser (2019): Semantic Noise Matters for Neural Natural Language Generation. In INLG, Tokyo, Japan. | @inproceedings{dusek-etal-2019-semantic,
title = "Semantic Noise Matters for Neural Natural Language Generation",
author = "Du{\v{s}}ek, Ond{\v{r}}ej and
Howcroft, David M. and
Rieser, Verena",
booktitle = "Proceedings of the 12th International Conference on Natural Language Generation",
m... | null | 3 | 695 | ---
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:
- text2text-generation
task_ids: []
paperswithcode_id: null
pretty_name: the Cleaned Version of the ... |
Multimodal-Fatima/SNLI-VE_test | 2023-02-07T22:33:34.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | null | 0 | 694 | ---
dataset_info:
features:
- name: image
dtype: image
- name: filename
dtype: string
- name: premise
dtype: string
- name: hypothesis
dtype: string
- name: label
dtype:
class_label:
names:
'0': entailment
'1': neutral
'2': contradiction
- na... |
ChristophSchuhmann/improved_aesthetics_6.5plus | 2022-08-10T11:34:17.000Z | [
"region:us"
] | ChristophSchuhmann | null | null | null | 32 | 688 | Entry not found |
mteb/imdb | 2022-09-27T19:14:44.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 1 | 687 | ---
language:
- en
--- |
BeIR/trec-covid | 2022-10-23T06:00:45.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | null | 0 | 684 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... |
Amod/mental_health_counseling_conversations | 2023-07-20T19:00:46.000Z | [
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:question-answering",
"task_ids:sentiment-classification",
"task_ids:language-modeling",
"task_ids:open-domain-qa",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"... | Amod | null | null | null | 26 | 683 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license: openrail
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- conversational
- text-generation
- question-answering
task_ids:
- sentiment-classification
- language-modeling
-... |
result-kand2-sdxl-wuerst-karlo/b2489367 | 2023-09-18T15:20:18.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 683 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 254
num_examples: 10
download_size: 1431
dataset_size: 254
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "b248936... |
EleutherAI/hendrycks_ethics | 2023-07-05T21:23:28.000Z | [
"region:us"
] | EleutherAI | The ETHICS dataset is a benchmark that spans concepts in justice, well-being,
duties, virtues, and commonsense morality. Models predict widespread moral
judgments about diverse text scenarios. This requires connecting physical and
social world knowledge to value judgements, a capability that may enable us
to steer chat... | @article{hendrycks2021ethics
title={Aligning AI With Shared Human Values},
author={Dan Hendrycks and Collin Burns and Steven Basart and Andrew Critch and Jerry Li and Dawn Song and Jacob Steinhardt},
journal={Proceedings of the International Conference on Learning Representations (ICLR)},
year={2021}
} | null | 0 | 682 | Entry not found |
result-kand2-sdxl-wuerst-karlo/4e6d4d01 | 2023-09-18T17:02:52.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 682 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 176
num_examples: 10
download_size: 1328
dataset_size: 176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "4e6d4d0... |
result-kand2-sdxl-wuerst-karlo/9bc865b4 | 2023-09-18T17:00:59.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 681 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 188
num_examples: 10
download_size: 1354
dataset_size: 188
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "9bc865b... |
result-kand2-sdxl-wuerst-karlo/b6ea8c05 | 2023-09-18T17:02:55.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 681 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 176
num_examples: 10
download_size: 1328
dataset_size: 176
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "b6ea8c0... |
movie_rationales | 2023-04-05T10:09:59.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | null | The movie rationale dataset contains human annotated rationales for movie
reviews. | @unpublished{eraser2019,
title = {ERASER: A Benchmark to Evaluate Rationalized NLP Models},
author = {Jay DeYoung and Sarthak Jain and Nazneen Fatema Rajani and Eric Lehman and Caiming Xiong and Richard Socher and Byron C. Wallace}
}
@InProceedings{zaidan-eisner-piatko-2008:nips,
author = {Omar F. Zaidan ... | null | 2 | 680 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: MovieRationales
dataset_info:
features:
... |
nickrosh/Evol-Instruct-Code-80k-v1 | 2023-07-11T02:05:26.000Z | [
"license:cc-by-nc-sa-4.0",
"arxiv:2306.08568",
"region:us"
] | nickrosh | null | null | null | 83 | 678 | ---
license: cc-by-nc-sa-4.0
---
Open Source Implementation of Evol-Instruct-Code as described in the [WizardCoder Paper](https://arxiv.org/pdf/2306.08568.pdf).
Code for the intruction generation can be found on Github as [Evol-Teacher](https://github.com/nickrosh/evol-teacher).
|
lmqg/qg_squad | 2022-12-02T18:51:10.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:squad",
"language:en",
"license:cc-by-4.0",
"question-generation",
"arxiv:2210.03992",
"arxiv:1705.00106",
"region:us"
] | lmqg | [SQuAD](https://rajpurkar.github.io/SQuAD-explorer/) evaluation set for the question generation (QG) models. The split
of test and development set follows the ["Neural Question Generation"](https://arxiv.org/abs/1705.00106) work and is
compatible with the [leader board](https://paperswithcode.com/sota/question-genera... | @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... | null | 4 | 675 | ---
license: cc-by-4.0
pretty_name: SQuAD for question generation
language: en
multilinguality: monolingual
size_categories: 10K<n<100K
source_datasets: squad
task_categories:
- text-generation
task_ids:
- language-modeling
tags:
- question-generation
---
# Dataset Card for "lmqg/qg_squad"
## Dataset Description
- **... |
mteb/twentynewsgroups-clustering | 2022-09-27T19:13:51.000Z | [
"language:en",
"region:us"
] | mteb | null | null | null | 0 | 671 | ---
language:
- en
--- |
kmfoda/booksum | 2022-11-30T12:03:43.000Z | [
"license:bsd-3-clause",
"arxiv:2105.08209",
"region:us"
] | kmfoda | null | null | null | 25 | 670 | ---
license:
- bsd-3-clause
train-eval-index:
- config: kmfoda--booksum
task: summarization
task_id: summarization
splits:
eval_split: test
col_mapping:
chapter: text
summary_text: target
---
# BOOKSUM: A Collection of Datasets for Long-form Narrative Summarization
Authors: [Wojciech Kryściński](ht... |
ceyda/smithsonian_butterflies | 2022-07-13T09:32:27.000Z | [
"task_categories:image-classification",
"task_ids:multi-label-image-classification",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"license:cc0-1.0",
"region:us"
] | ceyda | null | null | null | 6 | 670 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- expert-generated
license:
- cc0-1.0
multilinguality:
- monolingual
pretty_name: Smithsonian Butterflies
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- image-classification
task_ids:
- multi-label-image-classificatio... |
juletxara/xcopa_mt | 2023-07-21T10:19:22.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:extended|copa",
"language:en",
"license:cc-by-4.0",
"region:us"
] | juletxara | XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele ... | @article{ponti2020xcopa,
title={{XCOPA: A} Multilingual Dataset for Causal Commonsense Reasoning},
author={Edoardo M. Ponti, Goran Glava\v{s}, Olga Majewska, Qianchu Liu, Ivan Vuli\'{c} and Anna Korhonen},
journal={arXiv preprint},
year={2020},
url={https://ducdauge.github.io/files/xcopa.pdf}
}
@inproceedi... | null | 0 | 670 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: XCOPA MT
size_categories:
- unknown
source_datasets:
- extended|copa
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_id: ... |
result-kand2-sdxl-wuerst-karlo/908725e5 | 2023-09-19T00:19:24.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 669 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 161
num_examples: 10
download_size: 1318
dataset_size: 161
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "908725e... |
xiyuez/red-dot-design-award-product-description | 2023-07-07T18:32:48.000Z | [
"task_categories:text-generation",
"size_categories:10k<n<100K",
"language:en",
"license:odc-by",
"region:us"
] | xiyuez | null | null | null | 4 | 668 | ---
license: odc-by
task_categories:
- text-generation
language:
- en
pretty_name: Red Dot Design Award Dataset
size_categories:
- 10k<n<100K
---
# Red Dot Design Award Dataset
This dataset contains information about the products that have won the Red Dot Design Award, a prestigious international design competition. ... |
yair-elboher/text-toy | 2023-10-06T09:35:55.000Z | [
"region:us"
] | yair-elboher | null | null | null | 0 | 668 | ---
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 10849
num_examples: 9
- name: validation
num_bytes: 8180
num_examples: 4
download_size: 30926
dataset_size: 19029
configs:
- config_name: default
data_files:
- split: train
path: data/train-... |
GEM/e2e_nlg | 2022-10-24T15:30:18.000Z | [
"task_categories:table-to-text",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"data-to-text",
"region:us"
] | GEM | The E2E dataset is designed for a limited-domain data-to-text task --
generation of restaurant descriptions/recommendations based on up to 8 different
attributes (name, area, price range etc.). | @inproceedings{e2e_cleaned,
address = {Tokyo, Japan},
title = {Semantic {Noise} {Matters} for {Neural} {Natural} {Language} {Generation}},
url = {https://www.aclweb.org/anthology/W19-8652/},
booktitle = {Proceedings of the 12th {International} {Conference} on {Natural} {Language} {Generation} ({INLG} 2019)},
autho... | null | 2 | 667 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
pretty_name: e2e_nlg
tags:
- data-to-text
---
# Dataset Card for GEM/e2e_nlg
## Dataset D... |
ywchoi/pubmed_abstract_0 | 2022-09-13T00:53:42.000Z | [
"region:us"
] | ywchoi | null | null | null | 1 | 667 | Entry not found |
result-kand2-sdxl-wuerst-karlo/9e7f6f37 | 2023-09-19T00:24:03.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 667 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 152
num_examples: 10
download_size: 1303
dataset_size: 152
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "9e7f6f3... |
EleutherAI/the_pile_deduplicated | 2022-12-02T23:49:09.000Z | [
"region:us"
] | EleutherAI | null | null | null | 39 | 666 | Entry not found |
lmsys/mt_bench_human_judgments | 2023-07-20T18:28:15.000Z | [
"task_categories:conversational",
"task_categories:question-answering",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"arxiv:2306.05685",
"region:us"
] | lmsys | null | null | null | 32 | 666 | ---
dataset_info:
features:
- name: question_id
dtype: int64
- name: model_a
dtype: string
- name: model_b
dtype: string
- name: winner
dtype: string
- name: judge
dtype: string
- name: conversation_a
list:
- name: content
dtype: string
- name: role
dtype: strin... |
result-kand2-sdxl-wuerst-karlo/e87ec3b2 | 2023-09-19T00:21:50.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 666 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 153
num_examples: 10
download_size: 1306
dataset_size: 153
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "e87ec3b... |
result-kand2-sdxl-wuerst-karlo/ad45b2bb | 2023-09-19T01:34:46.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 664 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 188
num_examples: 10
download_size: 1388
dataset_size: 188
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ad45b2b... |
keremberke/chest-xray-classification | 2023-01-18T09:25:27.000Z | [
"task_categories:image-classification",
"roboflow",
"roboflow2huggingface",
"Biology",
"region:us"
] | keremberke | null | \ | null | 9 | 663 | ---
task_categories:
- image-classification
tags:
- roboflow
- roboflow2huggingface
- Biology
---
<div align="center">
<img width="640" alt="keremberke/chest-xray-classification" src="https://huggingface.co/datasets/keremberke/chest-xray-classification/resolve/main/thumbnail.jpg">
</div>
### Dataset Labels
```
['N... |
Biddls/Onion_News | 2023-03-25T12:57:47.000Z | [
"task_categories:summarization",
"task_categories:text2text-generation",
"task_categories:text-generation",
"task_categories:text-classification",
"language:en",
"license:mit",
"region:us"
] | Biddls | null | null | null | 1 | 661 | ---
license: mit
task_categories:
- summarization
- text2text-generation
- text-generation
- text-classification
language:
- en
pretty_name: OnionNewsScrape
---
## This is a dataset of Onion news articles:
Note
- The headers and body of the news article is split by a ' #~# ' token
- Lines with just the token had no ... |
result-kand2-sdxl-wuerst-karlo/4b9958b5 | 2023-09-19T02:29:31.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 661 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 167
num_examples: 10
download_size: 1331
dataset_size: 167
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "4b9958b... |
unitxt/data | 2023-10-03T13:07:44.000Z | [
"license:apache-2.0",
"region:us"
] | unitxt | null | null | null | 0 | 658 | ---
license: apache-2.0
---
|
yuchenlin/just-eval-instruct | 2023-10-07T06:44:23.000Z | [
"region:us"
] | yuchenlin | null | null | null | 2 | 656 | ---
configs:
- config_name: default
data_files:
- split: test
path: "test.jsonl"
- config_name: responses
data_files:
- split: gpt_4
path: "responses/gpt-4.json"
- split: gpt_3.5_turbo
path: "responses/gpt-3.5-turbo.json"
- split: vicuna_7b_v1.5
path: "responses/vicuna-7b-v1.5.json"
- ... |
openslr | 2023-06-01T14:59:55.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:af",
"language:bn",
"language:ca",
"language:en",
"language:es",
"language:eu",
"language... | null | OpenSLR is a site devoted to hosting speech and language resources, such as training corpora for speech recognition,
and software related to speech recognition. We intend to be a convenient place for anyone to put resources that
they have created, so that they can be downloaded publicly. | SLR32:
@inproceedings{van-niekerk-etal-2017,
title = {{Rapid development of TTS corpora for four South African languages}},
author = {Daniel van Niekerk and Charl van Heerden and Marelie Davel and Neil Kleynhans and Oddur Kjartansson
and Martin Jansche and Linne Ha},
booktitle = {Proc. Interspeech 2017}... | null | 11 | 655 | ---
pretty_name: OpenSLR
annotations_creators:
- found
language_creators:
- found
language:
- af
- bn
- ca
- en
- es
- eu
- gl
- gu
- jv
- km
- kn
- ml
- mr
- my
- ne
- si
- st
- su
- ta
- te
- tn
- ve
- xh
- yo
language_bcp47:
- en-GB
- en-IE
- en-NG
- es-CL
- es-CO
- es-PE
- es-PR
license:
- cc-by-sa-4.0
multilingual... |
conceptofmind/t0_submix_original | 2023-05-24T18:32:56.000Z | [
"region:us"
] | conceptofmind | null | null | null | 19 | 655 | ---
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: task_source
dtype: string
- name: task_name
dtype: string
- name: template_type
dtype: string
splits:
- name: train
num_bytes: 4602180562
num_examples: 1650308
download_size: 2738... |
BeIR/scifact | 2022-10-23T06:01:22.000Z | [
"task_categories:text-retrieval",
"task_ids:entity-linking-retrieval",
"task_ids:fact-checking-retrieval",
"multilinguality:monolingual",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | BeIR | null | null | null | 1 | 654 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: beir
pretty_name: BEIR Benchmark
size_categories:
msmarco:
- 1M<n<10M
trec-covid:
- 100k<n<1M
nfcorpus:
- 1K<n<10K
nq:
- 1M<n<10M
hotpotqa:
- 1M<n<10M
fiqa:
... |
chromadb/state_of_the_union | 2023-07-07T18:13:04.000Z | [
"region:us"
] | chromadb | null | null | null | 0 | 654 | ---
dataset_info:
features:
- name: id
dtype: string
- name: embedding
sequence: float64
- name: metadata
struct:
- name: source
dtype: string
- name: document
dtype: string
splits:
- name: data
num_bytes: 556545
num_examples: 42
download_size: 519613
dataset_size: 55... |
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