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 |
|---|---|---|---|---|---|---|---|---|---|
ryanc/music_align | 2023-08-29T02:50:52.000Z | [
"region:us"
] | ryanc | null | null | null | 0 | 140 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: caption
dtype: string
- name: audio
dtype: audio
splits:
- name: train
num_bytes: 16132095937.715
num_examples: 8537
download_size: 1862624886
dataset_size: 16132095937... |
atmallen/sloppy_addition_both_labels_1.0 | 2023-10-05T17:49:40.000Z | [
"region:us"
] | atmallen | null | null | null | 0 | 140 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
- split: test
path: data/test-*
dataset_info:
features:
- name: statement
dtype: string
- name: alice_label
dtype: bool
- name: bob_label
dtype: bool
- ... |
result-kand2-sdxl-wuerst-karlo/980edb53 | 2023-10-04T18:22:22.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 140 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 156
num_examples: 10
download_size: 1319
dataset_size: 156
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "980edb5... |
result-kand2-sdxl-wuerst-karlo/f7f54a55 | 2023-10-04T18:43:41.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 140 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 141
num_examples: 10
download_size: 1325
dataset_size: 141
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "f7f54a5... |
gnad10 | 2023-01-25T14:31:03.000Z | [
"task_categories:text-classification",
"task_ids:topic-classification",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-from-One-Million-Posts-Corpus",
"language:de",
"license:cc-by-nc-sa-4.0... | null | This dataset is intended to advance topic classification for German texts. A classifier that is efffective in
English may not be effective in German dataset because it has a higher inflection and longer compound words.
The 10kGNAD dataset contains 10273 German news articles from an Austrian online newspaper categorized... | null | null | 3 | 139 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- de
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-from-One-Million-Posts-Corpus
task_categories:
- text-classification
task_ids:
- topic-classification
pretty_name: ... |
imagenet_sketch | 2023-04-05T13:45:57.000Z | [
"task_categories:image-classification",
"task_ids:multi-class-image-classification",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|imagenet-1k",
"language:en",
"license:unknown",
"arxiv:... | null | ImageNet-Sketch data set consists of 50000 images, 50 images for each of the 1000 ImageNet classes.
We construct the data set with Google Image queries "sketch of __", where __ is the standard class name.
We only search within the "black and white" color scheme. We initially query 100 images for every class,
and then m... | @inproceedings{wang2019learning,
title={Learning Robust Global Representations by Penalizing Local Predictive Power},
author={Wang, Haohan and Ge, Songwei and Lipton, Zachary and Xing, Eric P},
booktitle={Advances in Neural Information Processing Systems},
pages={10506--10518},
y... | null | 5 | 139 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|imagenet-1k
task_categories:
- image-classification
task_ids:
- multi-class-image-classification
paperswithcode_id: imagen... |
bigbio/gad | 2022-12-22T15:25:28.000Z | [
"multilinguality:momolingual",
"language:en",
"license:cc-by-4.0",
"region:us"
] | bigbio | A corpus identifying associations between genes and diseases by a semi-automatic
annotation procedure based on the Genetic Association Database | @article{Bravo2015,
doi = {10.1186/s12859-015-0472-9},
url = {https://doi.org/10.1186/s12859-015-0472-9},
year = {2015},
month = feb,
publisher = {Springer Science and Business Media {LLC}},
volume = {16},
number = {1},
author = {{\`{A}}lex Bravo and Janet Pi{\~{n}}ero and N{\'{u}}ria Queralt-Rosinach a... | null | 0 | 139 | ---
language:
- en
bigbio_language:
- English
license: cc-by-4.0
multilinguality: momolingual
bigbio_license_shortname: CC_BY_4p0
pretty_name: GAD
homepage: https://geneticassociationdb.nih.gov/
bigbio_pubmed: true
bigbio_public: true
bigbio_tasks:
- TEXT_CLASSIFICATION
paperswithcode_id: gad
---
# Dataset Car... |
tomekkorbak/detoxify-pile-chunk3-400000-450000 | 2022-10-03T18:51:21.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 139 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-450000-500000 | 2022-10-03T19:48:41.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 139 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-500000-550000 | 2022-10-04T17:42:07.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 139 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-550000-600000 | 2022-10-04T17:46:16.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 139 | Entry not found |
yangwang825/reuters-21578 | 2023-05-19T02:04:58.000Z | [
"task_categories:text-classification",
"language:en",
"region:us"
] | yangwang825 | null | null | null | 0 | 139 | ---
task_categories:
- text-classification
language:
- en
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype:
class_label:
names:
'0': acq
'1': crude
'2': earn
'3': grain
'4': interest
'5'... |
YeungNLP/ultrachat | 2023-06-19T02:52:43.000Z | [
"region:us"
] | YeungNLP | null | null | null | 12 | 139 | Entry not found |
eliolio/dialogsum-noniid | 2023-06-28T19:51:13.000Z | [
"region:us"
] | eliolio | null | null | null | 0 | 139 | Entry not found |
hiroshi-matsuda-rit/filtered_mc4 | 2023-08-28T08:52:06.000Z | [
"multilinguality:multilingual",
"license:odc-by",
"arxiv:1910.10683",
"region:us"
] | hiroshi-matsuda-rit | The mC4 dataset to which arbitrary filters can be applied.
The original description is below:
===
A colossal, cleaned version of Common Crawl's web crawl corpus.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's mC4 dataset by AllenAI. | @article{2019t5,
author = {Colin Raffel and Noam Shazeer and Adam Roberts and Katherine Lee and Sharan Narang and Michael Matena and Yanqi Zhou and Wei Li and Peter J. Liu},
title = {Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
journal = {arXiv e-prints},
year = {2... | null | 0 | 139 | ---
pretty_name: filtered-mc4
license:
- odc-by
multilinguality:
- multilingual
---
# Dataset Card for filtered-mc4
See original [mC4 dataset](https://huggingface.co/datasets/mc4) descriptions.
You can apply any regular expression to the mC4 dataset like this:
```python
from datasets import load_dataset
dataset = ... |
samlhuillier/sql-create-context-spider-intersect | 2023-09-21T00:17:19.000Z | [
"region:us"
] | samlhuillier | null | null | null | 0 | 139 | Entry not found |
bloyal/oas-paired-sequence-data | 2023-09-28T21:26:27.000Z | [
"task_categories:fill-mask",
"language:en",
"license:cc-by-4.0",
"region:us"
] | bloyal | Paired heavy and light chain antibody sequences for multiple species. | @article{Olsen_Boyles_Deane_2022,
title={Observed Antibody Space: A diverse database of cleaned, annotated, and translated unpaired and paired antibody sequences},
volume={31}, rights={© 2021 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.},
ISSN={1469-896X}, DOI={10... | null | 0 | 139 | ---
pretty_name: OAS paired sequences
language: en
task_categories:
- fill-mask
license: cc-by-4.0
---
# Dataset Card for OAS Paired Sequence Data
## Dataset Description
- **Homepage:**
- https://opig.stats.ox.ac.uk/webapps/oas/oas_paired/
## Dataset Summary
Paired heavy- and light-chain sequence information from... |
hynky/czech-justice-summ-alpaca-long | 2023-09-10T21:24:17.000Z | [
"region:us"
] | hynky | null | null | null | 0 | 139 | ---
dataset_info:
features:
- name: output
dtype: string
- name: instruction
dtype: string
splits:
- name: train
num_bytes: 26403302
num_examples: 4560
download_size: 12636847
dataset_size: 26403302
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
#... |
djscrave/tsh | 2023-09-16T11:04:10.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:fr",
"license:openrail",
"chemistry",
"region:us"
] | djscrave | null | null | null | 0 | 139 | ---
configs:
- config_name: default
data_files:
- split: train
path: "train.csv"
- split: validation
path: "validation.csv"
- split: test
path: "test.csv"
license: openrail
task_categories:
- text-classification
language:
- fr
tags:
- chemistry
size_categories:
- 1K<n<10K
--- |
mac_morpho | 2023-01-25T14:34:31.000Z | [
"task_categories:token-classification",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:pt",
"license:cc-by-4.0",
"region:us"
] | null | Mac-Morpho is a corpus of Brazilian Portuguese texts annotated with part-of-speech tags.
Its first version was released in 2003 [1], and since then, two revisions have been made in order
to improve the quality of the resource [2, 3].
The corpus is available for download split into train, development and test sections.
... | @article{fonseca2015evaluating,
title={Evaluating word embeddings and a revised corpus for part-of-speech tagging in Portuguese},
author={Fonseca, Erick R and Rosa, Joao Luis G and Aluisio, Sandra Maria},
journal={Journal of the Brazilian Computer Society},
volume={21},
number={1},
pages={2},
year={2015},... | null | 4 | 138 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- part-of-speech
pretty_name: Mac-Morpho
dataset_info:
features:
- na... |
allegro/klej-dyk | 2022-10-26T09:01:41.000Z | [
"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:cc-by-sa-3.0",
"region:us"
] | allegro | null | null | null | 1 | 138 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- cc-by-sa-3.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- open-domain-qa
pretty_name: Did you know?
---
# klej-dyk
## Descriptio... |
mozilla-foundation/common_voice_1_0 | 2023-07-29T15:59:56.000Z | [
"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 | 2 | 138 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
license:
- cc0-1.0
multilinguality:
- multilingual
size_categories:
br:
- 1K<n<10K
ca:
- 10K<n<100K
cnh:
- 1K<n<10K
cv:
- 1K<n<10K
cy:
- 10K<n<100K
de:
- 100K<n<1M
en:
- 100K<n<1M
eo:
- 1K<n<10K
et:
- n<1K
f... |
tomekkorbak/detoxify-pile-chunk3-700000-750000 | 2022-10-04T17:50:07.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-600000-650000 | 2022-10-04T17:51:35.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-750000-800000 | 2022-10-04T22:48:41.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-850000-900000 | 2022-10-04T23:55:21.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-650000-700000 | 2022-10-04T18:03:56.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1100000-1150000 | 2022-10-04T23:49:53.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1050000-1100000 | 2022-10-04T23:53:15.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1000000-1050000 | 2022-10-04T23:58:45.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 138 | Entry not found |
inverse-scaling/NeQA | 2022-10-08T12:40:09.000Z | [
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-sa-4.0",
"region:us"
] | inverse-scaling | null | null | null | 0 | 138 | ---
language:
- en
size_categories:
- 10K<n<100K
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: NeQA - Can Large Language Models Understand Negation in Multi-choice Questions?
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
train-eval-index:
- ... |
tobiolatunji/afrispeech-200 | 2023-05-20T23:29:22.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-nc-sa-4.0",
"regio... | tobiolatunji | AFRISPEECH-200 is a 200hr Pan-African speech corpus for clinical and general domain English accented ASR;
a dataset with 120 African accents from 13 countries and 2,463 unique African speakers.
Our goal is to raise awareness for and advance Pan-African English ASR research,
especially for the clinical domain. | TBD | null | 8 | 138 | ---
pretty_name: AfriSpeech-200
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- en
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids: []
da... |
KETI-AIR/coco | 2023-03-22T11:45:13.000Z | [
"task_categories:object-detection",
"size_categories:100K<n<1M",
"language:en",
"license:apache-2.0",
"region:us"
] | KETI-AIR | COCO is a large-scale object detection, segmentation, and
captioning dataset.
Note:
* Some images from the train and validation sets don't have annotations.
* Coco 2014 and 2017 uses the same images, but different train/val/test splits
* The test split don't have any annotations (only images).
* Coco defines 91 cla... | @article{DBLP:journals/corr/LinMBHPRDZ14,
author = {Tsung{-}Yi Lin and
Michael Maire and
Serge J. Belongie and
Lubomir D. Bourdev and
Ross B. Girshick and
James Hays and
Pietro Perona and
Deva Ramanan and
... | null | 0 | 138 | ---
license: apache-2.0
task_categories:
- object-detection
language:
- en
size_categories:
- 100K<n<1M
pretty_name: Coco
---
# Coco dataset loader based on tensorflow dataset coco
## Object Detection
```python
import os
from datasets import load_dataset
from PIL import Image, ImageFont, ImageDraw, ImageColor
def c... |
Thaweewat/databricks-dolly-15k-th | 2023-05-09T16:15:52.000Z | [
"task_categories:question-answering",
"task_categories:summarization",
"size_categories:10K<n<100K",
"language:th",
"license:cc-by-sa-3.0",
"instruction-finetuning",
"region:us"
] | Thaweewat | null | null | null | 1 | 138 | ---
license: cc-by-sa-3.0
task_categories:
- question-answering
- summarization
tags:
- instruction-finetuning
language:
- th
size_categories:
- 10K<n<100K
---
# Summary
This is a Thai 🇹🇭-instructed dataset translated from `databricks-dolly-15k` using Google Cloud Translation.
`databricks-dolly-15k` is an open-sourc... |
shumpei2525/fine_tuning521k-ja | 2023-07-02T18:06:01.000Z | [
"license:mit",
"region:us"
] | shumpei2525 | null | null | null | 10 | 138 | ---
license: mit
---
# fine_tuning521k-ja
This data is a dataset for fine-tuning the local language model (LLM). It consists of the translation of "ign_clean_instruct_dataset_500k" and "GPTeacher." Please feel free to use it. This dataset contains data such as Q&A, contextualized questions, role plays. Please contact ... |
chats-bug/input_tools_plans | 2023-09-12T10:40:23.000Z | [
"region:us"
] | chats-bug | null | null | null | 1 | 138 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: prompt
dtype: string
splits:
- name: train
num_bytes: 29938684.365363304
num_examples: 10107
- name: test
num_bytes: 7485411.634636695... |
joey234/affixal_negation | 2023-10-10T22:44:14.000Z | [
"task_categories:text-classification",
"size_categories:1K<n<10K",
"language:en",
"license:apache-2.0",
"region:us"
] | joey234 | null | null | null | 0 | 138 | ---
license: apache-2.0
task_categories:
- text-classification
language:
- en
pretty_name: e
size_categories:
- 1K<n<10K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
- This dataset contain... |
tomekkorbak/detoxify-pile-chunk3-800000-850000 | 2022-10-04T22:47:07.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 137 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-900000-950000 | 2022-10-04T23:47:24.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 137 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-950000-1000000 | 2022-10-04T22:55:50.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 137 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1150000-1200000 | 2022-10-04T23:45:42.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 137 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1200000-1250000 | 2022-10-04T23:47:33.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 137 | Entry not found |
BelleGroup/train_0.5M_CN | 2023-04-03T08:11:22.000Z | [
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
"language:zh",
"license:gpl-3.0",
"region:us"
] | BelleGroup | null | null | null | 68 | 137 | ---
license: gpl-3.0
task_categories:
- text2text-generation
language:
- zh
size_categories:
- 100K<n<1M
---
## 内容
包含约50万条由[BELLE](https://github.com/LianjiaTech/BELLE)项目生成的中文指令数据。
## 样例
```
{
"instruction": "给定一个文字输入，将其中的所有数字加1。\n“明天的会议在9点开始，记得准时到达。”\n",
"input": "",
"output": "“明天的会议在10点开始，记得准时到达。”"
}
```
###... |
CM/codexglue_code2text_ruby | 2023-04-22T01:52:59.000Z | [
"region:us"
] | CM | null | null | null | 0 | 137 | ---
dataset_info:
features:
- name: id
dtype: int32
- name: repo
dtype: string
- name: path
dtype: string
- name: func_name
dtype: string
- name: original_string
dtype: string
- name: language
dtype: string
- name: code
dtype: string
- name: code_tokens
sequence: string... |
open-phi/programming_books_llama | 2023-10-04T18:02:56.000Z | [
"region:us"
] | open-phi | null | null | null | 5 | 137 | ---
dataset_info:
features:
- name: topic
dtype: string
- name: outline
sequence: string
- name: concepts
sequence: string
- name: queries
sequence: string
- name: context
sequence: string
- name: markdown
dtype: string
- name: model
dtype: string
splits:
- name: train
... |
onestop_qa | 2023-01-25T14:42:12.000Z | [
"task_categories:question-answering",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"source_datasets:extended|onestop_english",
"language:en",
"lic... | null | OneStopQA is a multiple choice reading comprehension dataset annotated according to the STARC (Structured Annotations for Reading Comprehension) scheme. The reading materials are Guardian articles taken from the [OneStopEnglish corpus](https://github.com/nishkalavallabhi/OneStopEnglishCorpus). Each article comes in thr... | @inproceedings{starc2020,
author = {Berzak, Yevgeni and Malmaud, Jonathan and Levy, Roger},
title = {STARC: Structured Annotations for Reading Comprehension},
booktitle = {ACL},
year = {2020},
publisher = {Association for Computational Linguistics}
} | null | 4 | 136 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
- extended|onestop_english
task_categories:
- question-answering
task_ids:
- multiple-choice-qa
paperswithcode_... |
the_pile_books3 | 2023-10-09T09:06:14.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",... | null | This dataset is Shawn Presser's work and is part of EleutherAi/The Pile dataset. This dataset contains all of bibliotik in plain .txt form, aka 197,000 books processed in exactly the same way as did for bookcorpusopen (a.k.a. books1). seems to be similar to OpenAI's mysterious "books2" dataset referenced in their paper... | @article{pile,
title={The {P}ile: An 800GB Dataset of Diverse Text for Language Modeling},
author={Gao, Leo and Biderman, Stella and Black, Sid and Golding, Laurence and Hoppe, Travis and Foster, Charles and Phang, Jason and He, Horace and Thite, Anish and Nabeshima, Noa and Presser, Shawn and Leahy, Connor},
... | null | 119 | 136 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: Books3
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
viewer: f... |
GEM/web_nlg | 2022-10-24T15:31:09.000Z | [
"task_categories:table-to-text",
"annotations_creators:unknown",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-nc-4.0",
"data-to-text",
"region:us"
] | GEM | WebNLG is a bi-lingual dataset (English, Russian) of parallel DBpedia triple sets
and short texts that cover about 450 different DBpedia properties. The WebNLG data
was originally created to promote the development of RDF verbalisers able to
generate short text and to handle micro-planning (i.e., sentence segmentation ... | @inproceedings{castro-ferreira20:bilin-bi-direc-webnl-shared,
title={The 2020 Bilingual, Bi-Directional WebNLG+ Shared Task Overview and Evaluation Results (WebNLG+ 2020)},
author={Castro Ferreira, Thiago and
Gardent, Claire and
Ilinykh, Nikolai and
van der Lee, Chris and
Mille, Simon ... | null | 2 | 136 | ---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- en
license:
- cc-by-nc-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- table-to-text
task_ids: []
pretty_name: web_nlg
tags:
- data-to-text
---
# Dataset Card for GEM/web_nlg
## Datase... |
ChristophSchuhmann/improved_aesthetics_6plus | 2022-08-10T11:30:40.000Z | [
"region:us"
] | ChristophSchuhmann | null | null | null | 21 | 136 | Entry not found |
arbml/alpagasus_cleaned_ar | 2023-09-06T17:22:31.000Z | [
"region:us"
] | arbml | null | null | null | 0 | 136 | ---
dataset_info:
features:
- name: instruction_en
dtype: string
- name: output_en
dtype: string
- name: instruction
dtype: string
- name: output
dtype: string
- name: index
dtype: int64
splits:
- name: train
num_bytes: 9824184
num_examples: 9229
download_size: 5541315
da... |
EleutherAI/drop | 2023-08-30T10:16:05.000Z | [
"region:us"
] | EleutherAI | DROP is a QA dataset which tests comprehensive understanding of paragraphs. In
this crowdsourced, adversarially-created, 96k question-answering benchmark, a
system must resolve multiple references in a question, map them onto a paragraph,
and perform discrete operations over them (such as addition, counting, or sorting... | @misc{dua2019drop,
title={DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs},
author={Dheeru Dua and Yizhong Wang and Pradeep Dasigi and Gabriel Stanovsky and Sameer Singh and Matt Gardner},
year={2019},
eprint={1903.00161},
archivePrefix={arXiv},
primaryClass=... | null | 0 | 136 | Entry not found |
minh21/cpgQA-v1.0-unique-context-test-10-percent-validation-10-percent | 2023-09-09T11:37:51.000Z | [
"region:us"
] | minh21 | null | null | null | 0 | 136 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: title
dtype: string
- name: id
dtype: int64
- name: question
dtype: string
- name: answe... |
result-kand2-sdxl-wuerst-karlo/ac298fb2 | 2023-10-04T23:40:46.000Z | [
"region:us"
] | result-kand2-sdxl-wuerst-karlo | null | null | null | 0 | 136 | ---
dataset_info:
features:
- name: result
dtype: string
- name: id
dtype: int64
splits:
- name: train
num_bytes: 165
num_examples: 10
download_size: 1316
dataset_size: 165
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
---
# Dataset Card for "ac298fb... |
FinanceInc/auditor_sentiment | 2022-07-21T19:03:51.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"region:us"
] | FinanceInc | null | null | null | 10 | 135 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- en
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
- sentiment-classification
paperswithcode_id: null
pretty_name: Audi... |
tomekkorbak/detoxify-pile-chunk3-1250000-1300000 | 2022-10-05T00:28:11.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 135 | Entry not found |
santhosh/english-malayalam-names | 2023-04-06T09:26:40.000Z | [
"task_categories:text2text-generation",
"size_categories:10M<n<100M",
"language:en",
"language:ml",
"license:cc-by-sa-4.0",
"malayalam",
"region:us"
] | santhosh | null | null | null | 1 | 135 | ---
license: cc-by-sa-4.0
task_categories:
- text2text-generation
language:
- en
- ml
tags:
- malayalam
size_categories:
- 10M<n<100M
---
# English Malayalam names
This dataset has 27814162 person names both in English and Malayalam.
The source for this dataset is various election roles published by Government.
P... |
mstz/gisette | 2023-04-17T10:55:16.000Z | [
"task_categories:tabular-classification",
"language:en",
"gisette",
"tabular_classification",
"binary_classification",
"region:us"
] | mstz | null | @misc{misc_gisette_170,
author = {Guyon,Isabelle, Gunn,Steve, Ben-Hur,Asa & Dror,Gideon},
title = {{Gisette}},
year = {2008},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: \\url{10.24432/C5HP5B}}
} | null | 0 | 135 | ---
language:
- en
tags:
- gisette
- tabular_classification
- binary_classification
pretty_name: Gisette
task_categories: # Full list at https://github.com/huggingface/hub-docs/blob/main/js/src/lib/interfaces/Types.ts
- tabular-classification
configs:
- gisette
---
# Gisette
The [Gisette dataset](https://archive-beta.... |
C-MTEB/T2Reranking | 2023-07-28T07:29:52.000Z | [
"region:us"
] | C-MTEB | null | null | null | 0 | 135 | ---
configs:
- config_name: default
data_files:
- split: dev
path: data/dev-*
dataset_info:
features:
- name: query
dtype: string
- name: positive
sequence: string
- name: negative
sequence: string
splits:
- name: dev
num_bytes: 206865573
num_examples: 6129
download_size: 12029... |
gwlms/germeval2014 | 2023-07-31T16:08:59.000Z | [
"license:cc-by-4.0",
"region:us"
] | gwlms | # Introduction
The GermEval 2014 NER Shared Task is an event that makes available CC-licensed German data with NER annotation with the
goal of significantly advancing the state of the art in German NER and to push the field of NER towards nested
representations of named entities.
The GermEval 2014 NER Shared Task b... | @inproceedings{benikova14:_germev_named_entit_recog_shared_task,
added-at = {2017-04-03T19:29:52.000+0000},
address = {Hildesheim, Germany},
author = {Benikova, Darina and Biemann, Chris and Kisselew, Max and Pad\'o, Sebastian},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2132d938a7afe8639e78156fb9d756b20... | null | 0 | 135 | ---
viewer: false
license: cc-by-4.0
dataset_info:
features:
- name: tokens
sequence: string
- name: ner_tags
sequence:
class_label:
names:
'0': O
'1': B-LOC
'2': I-LOC
'3': B-LOCderiv
'4': I-LOCderiv
'5': B-LOCpart
'6': I... |
sarahpann/MATH | 2023-09-23T03:06:46.000Z | [
"region:us"
] | sarahpann | null | null | null | 0 | 135 | Entry not found |
mtc/swisstext23-20min-annotation-data | 2023-08-25T08:22:10.000Z | [
"region:us"
] | mtc | null | null | null | 0 | 135 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: int64
- name: titleHeader
dtype: string
- name: title
dtype: string
- name: lead
dtype: string
- name: article
dtype: string
- name: summary
dtype: stri... |
TaylorAI/pubmed_commercial | 2023-08-26T07:32:30.000Z | [
"region:us"
] | TaylorAI | null | null | null | 11 | 135 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1300000-1350000 | 2022-10-05T00:06:32.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 134 | Entry not found |
mitclinicalml/clinical-ie | 2022-12-01T16:34:20.000Z | [
"arxiv:2205.12689",
"arxiv:2010.02010",
"arxiv:1806.04185",
"region:us"
] | mitclinicalml | null | @inproceedings{agrawal2022large,
title={Large Language Models are Few-Shot Clinical Information Extractors},
author={Monica Agrawal and Stefan Hegselmann and Hunter Lang and Yoon Kim and David Sontag},
booktitle = {Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing},
... | null | 18 | 134 | ---
{}
---
Below, we provide access to the datasets used in and created for the EMNLP 2022 paper [Large Language Models are Few-Shot Clinical Information Extractors](https://arxiv.org/abs/2205.12689).
# Task #1: Clinical Sense Disambiguation
For Task #1, we use the original annotations from the [Clinical Acronym Sens... |
Achitha/tamil_eng_data | 2023-02-12T18:52:26.000Z | [
"task_categories:translation",
"size_categories:1K<n<10K",
"language:ta",
"language:en",
"region:us"
] | Achitha | The data contains roughly one and half hours of audio and transcripts in Tamil language. | @misc{simpledata_1,
title = {Whisper model for tamil-to-eng translation},
publisher = {Achitha},
year = {2022},
}
@misc{simpledata_2,
title = {Fine-tuning whisper model},
publisher = {Achitha},
year = {2022},
} | null | 0 | 134 | ---
task_categories:
- translation
language:
- ta
- en
size_categories:
- 1K<n<10K
--- |
vgaraujov/wmt13 | 2023-07-04T08:17:47.000Z | [
"region:us"
] | vgaraujov | null | @InProceedings{bojar-EtAl:2013:WMT,
author = {Bojar, Ond\v{r}ej and Buck, Christian and Callison-Burch, Chris and Federmann, Christian and Haddow, Barry and Koehn, Philipp and Monz, Christof and Post, Matt and Soricut, Radu and Specia, Lucia},
title = {Findings of the 2013 {Workshop on Stat... | null | 0 | 134 | Entry not found |
minskiter/weibo | 2023-07-22T13:49:08.000Z | [
"size_categories:1K<n<10K",
"language:zh",
"license:apache-2.0",
"social",
"region:us"
] | minskiter | The Weibo NER dataset is a Chinese Named Entity Recognition dataset
drawn from the social media website Sina Weibo. | @inproceedings{peng-dredze-2015-named,
title = "Named Entity Recognition for {C}hinese
Social Media with Jointly Trained Embeddings",
author = "Peng, Nanyun and Dredze, Mark",
booktitle = "Proceedings of the 2015 Conference on
Empirical Methods in Natural Language Processing",
month =... | null | 0 | 134 | ---
license: apache-2.0
dataset_info:
features:
- name: text
sequence: string
- name: labels
sequence:
class_label:
names:
'0': O
'1': B-PER.NAM
'2': I-PER.NAM
'3': E-PER.NAM
'4': S-PER.NAM
'5': B-ORG.NAM
'6': I-ORG.NAM
... |
tomekkorbak/detoxify-pile-chunk3-1500000-1550000 | 2022-10-04T23:53:18.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 133 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1400000-1450000 | 2022-10-04T23:57:23.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 133 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1550000-1600000 | 2022-10-05T00:02:47.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 133 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1350000-1400000 | 2022-10-05T00:06:19.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 133 | Entry not found |
sdadas/ppc | 2022-12-29T11:30:31.000Z | [
"task_categories:text-classification",
"task_ids:semantic-similarity-classification",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:pl",
"license:cc-by-nc-sa-4.0",
"region:us"
] | sdadas | null | null | null | 0 | 133 | ---
language:
- pl
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
task_categories:
- text-classification
task_ids:
- semantic-similarity-classification
pretty_name: Polish Paraphrase Corpus
dataset_info:
features:
- name: sentence_A
dtype: string
- name: sentence_B
d... |
DFKI-SLT/kbp37 | 2023-04-27T13:04:14.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:other",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other",
"language:en",
"license:other",
"relation extraction",
"arxiv:1508... | DFKI-SLT | KBP37 is a revision of MIML-RE annotation dataset, provided by Gabor Angeli et al. (2014). They use both the 2010 and
2013 KBP official document collections, as well as a July 2013 dump of Wikipedia as the text corpus for annotation.
There are 33811 sentences been annotated. Zhang and Wang made several refinements:
1... | @article{DBLP:journals/corr/ZhangW15a,
author = {Dongxu Zhang and
Dong Wang},
title = {Relation Classification via Recurrent Neural Network},
journal = {CoRR},
volume = {abs/1508.01006},
year = {2015},
url = {http://arxiv.org/abs/1508.01006},
eprinttype = {arXiv},
e... | null | 0 | 133 | ---
annotations_creators:
- other
language:
- en
language_creators:
- found
license:
- other
multilinguality:
- monolingual
pretty_name: KBP37 is an English Relation Classification dataset
size_categories:
- 10K<n<100K
source_datasets:
- extended|other
tags:
- relation extraction
task_categories:
- text-classification
... |
patomp/thai-mscoco-2014-captions | 2023-05-02T15:52:54.000Z | [
"region:us"
] | patomp | null | null | null | 0 | 133 | ---
dataset_info:
features:
- name: image
dtype: image
- name: filepath
dtype: string
- name: sentids
list: int32
- name: filename
dtype: string
- name: imgid
dtype: int32
- name: split
dtype: string
- name: sentences_tokens
list:
list: string
- name: sentences_raw
... |
PNLPhub/digikala-sentiment-analysis | 2023-09-03T06:49:27.000Z | [
"region:us"
] | PNLPhub | null | null | null | 1 | 133 | ---
dataset_info:
features:
- name: Text
dtype: string
- name: Score
dtype: int64
- name: Suggestion
dtype: int64
splits:
- name: train
num_bytes: 1026393
num_examples: 2282
- name: validation
num_bytes: 234807
num_examples: 489
- name: test
num_bytes: 228949
num_exam... |
shiroyasha13/llama_text_to_sql_dataset | 2023-08-29T11:47:05.000Z | [
"region:us"
] | shiroyasha13 | null | null | null | 5 | 133 | Entry not found |
godoyj/wikilingua | 2023-09-08T17:36:48.000Z | [
"task_categories:summarization",
"language:pt",
"region:us"
] | godoyj | null | null | null | 0 | 133 | ---
language:
- pt
task_categories:
- summarization
--- |
amitness/mlrs-pos-mt | 2023-09-26T16:27:07.000Z | [
"region:us"
] | amitness | null | null | null | 0 | 133 | ---
dataset_info:
features:
- name: pos_tags
sequence:
class_label:
names:
'0': ADJ
'1': ADV
'2': COMP
'3': CONJ_CORD
'4': CONJ_SUB
'5': DEF
'6': FOC
'7': FUT
'8': GEN
'9': GEN_DEF
'10': G... |
edarchimbaud/news-stocks | 2023-10-10T03:52:18.000Z | [
"region:us"
] | edarchimbaud | null | null | null | 3 | 132 | ---
dataset_info:
features:
- name: symbol
dtype: string
- name: body
dtype: string
- name: publisher
dtype: string
- name: publish_time
dtype: timestamp[ns, tz=GMT]
- name: title
dtype: string
- name: url
dtype: string
- name: uuid
dtype: string
splits:
- name: train
... |
mmenendezg/pneumonia_x_ray | 2023-06-21T23:07:12.000Z | [
"region:us"
] | mmenendezg | null | null | null | 1 | 132 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': normal
'1': pneumonia
splits:
- name: train
num_bytes: 126684250.689
num_examples: 4187
- name: validation
num_bytes: 27444182.485
num_examples: 1045... |
alayaran/bodo-monolingual-dataset | 2023-09-16T16:13:42.000Z | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:brx",
"license:mit",
"region:us"
] | alayaran | null | null | null | 0 | 132 | ---
language:
- brx
license: mit
size_categories:
- 100K<n<1M
task_categories:
- text-generation
pretty_name: bodo-monolingual
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 130783128
num_examples: 474703
- name: test
num_bytes: 4109084
num_examples: 14... |
hippocrates/DDI_RE | 2023-10-04T19:08:58.000Z | [
"region:us"
] | hippocrates | null | null | null | 0 | 132 | Entry not found |
eurlex | 2022-11-18T20:01:34.000Z | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"legal-topic-classification",
"re... | null | EURLEX57K contains 57k legislative documents in English from EUR-Lex portal, annotated with EUROVOC concepts. | @inproceedings{chalkidis-etal-2019-large,
title = "Large-Scale Multi-Label Text Classification on {EU} Legislation",
author = "Chalkidis, Ilias and Fergadiotis, Emmanouil and Malakasiotis, Prodromos and Androutsopoulos, Ion",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Comp... | null | 4 | 131 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
paperswithcode_id: eurlex57k
pretty_name: the EUR-Lex... |
pragmeval | 2023-06-01T14:59:54.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"lice... | null | Evaluation of language understanding with a 11 datasets benchmark focusing on discourse and pragmatics | @misc{sileo2019discoursebased,
title={Discourse-Based Evaluation of Language Understanding},
author={Damien Sileo and Tim Van-de-Cruys and Camille Pradel and Philippe Muller},
year={2019},
eprint={1907.08672},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | null | 3 | 131 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
- 1K<n<10K
- n<1K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
pretty_name: pragmeval
dataset_info:
- c... |
maastrichtlawtech/bsard | 2023-09-26T15:28:00.000Z | [
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:document-retrieval",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:fr",
"license:cc-by-nc-sa-4... | maastrichtlawtech | The Belgian Statutory Article Retrieval Dataset (BSARD) is a French native dataset for studying legal information retrieval.
BSARD consists of more than 22,600 statutory articles from Belgian law and about 1,100 legal questions posed by Belgian citizens
and labeled by experienced jurists with relevant articles from t... | @inproceedings{louis-spanakis-2022-statutory,
title = "A Statutory Article Retrieval Dataset in {F}rench",
author = "Louis, Antoine and Spanakis, Gerasimos",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
y... | null | 2 | 131 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- fr
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
pretty_name: BSARD
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-retrieval
- text-classification
task_ids:
- document-retrieval
paperswithc... |
zeroshot/twitter-financial-news-topic | 2022-12-04T16:50:10.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:other",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:mit",
"twitter",
"finance",
"markets",
"stoc... | zeroshot | null | null | null | 16 | 131 | ---
annotations_creators:
- other
language:
- en
language_creators:
- other
license:
- mit
multilinguality:
- monolingual
pretty_name: twitter financial news
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- twitter
- finance
- markets
- stocks
- wallstreet
- quant
- hedgefunds
- markets
task_categories... |
tomekkorbak/detoxify-pile-chunk3-1450000-1500000 | 2022-10-04T23:56:05.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 131 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1600000-1650000 | 2022-10-04T23:57:39.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 131 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1650000-1700000 | 2022-10-05T00:01:13.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 131 | Entry not found |
dmayhem93/agieval-sat-math | 2023-06-18T17:32:05.000Z | [
"license:mit",
"arxiv:2304.06364",
"region:us"
] | dmayhem93 | null | null | null | 5 | 131 | ---
dataset_info:
features:
- name: query
dtype: string
- name: choices
sequence: string
- name: gold
sequence: int64
splits:
- name: test
num_bytes: 110388
num_examples: 220
download_size: 57002
dataset_size: 110388
license: mit
---
# Dataset Card for "agieval-sat-math"
Dataset ta... |
Globaly/first-dataset | 2023-09-11T15:39:29.000Z | [
"region:us"
] | Globaly | null | null | null | 0 | 131 | Entry not found |
open-source-metrics/pip | 2023-10-03T09:12:23.000Z | [
"region:us"
] | open-source-metrics | null | null | null | 0 | 130 | ---
dataset_info:
features:
- name: day
dtype: string
- name: num_downloads
dtype: int64
splits:
- name: transformers
num_bytes: 25454
num_examples: 1157
- name: peft
num_bytes: 5632
num_examples: 256
- name: diffusers
num_bytes: 10780
num_examples: 490
- name: pytorch_im... |
tomekkorbak/detoxify-pile-chunk3-1750000-1800000 | 2022-10-04T23:02:19.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 130 | Entry not found |
tomekkorbak/detoxify-pile-chunk3-1700000-1750000 | 2022-10-04T23:58:51.000Z | [
"region:us"
] | tomekkorbak | null | null | null | 0 | 130 | Entry not found |
Norod78/simpsons-blip-captions | 2022-11-09T16:27:19.000Z | [
"task_categories:text-to-image",
"annotations_creators:machine-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:n<1K",
"language:en",
"license:cc-by-nc-sa-4.0",
"region:us"
] | Norod78 | null | null | null | 2 | 130 | ---
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 51605730.0
num_examples: 755
download_size: 50553165
dataset_size: 51605730.0
pretty_name: 'Simpsons BLIP captions'
size_categories:
- n<1K
tags: []
task_categories:
- tex... |
mstz/magic | 2023-04-16T17:34:16.000Z | [
"task_categories:tabular-classification",
"size_categories:10K<n<100K",
"language:en",
"license:cc",
"magic",
"tabular_classification",
"binary_classification",
"UCI",
"region:us"
] | mstz | null | @misc{misc_magic_gamma_telescope_159,
author = {Bock,R.},
title = {{MAGIC Gamma Telescope}},
year = {2007},
howpublished = {UCI Machine Learning Repository},
note = {{DOI}: \\url{10.24432/C52C8B}}
} | null | 0 | 130 | ---
language:
- en
tags:
- magic
- tabular_classification
- binary_classification
- UCI
pretty_name: Magic
size_categories:
- 10K<n<100K
task_categories:
- tabular-classification
configs:
- magic
license: cc
---
# Magic
The [Magic dataset](https://archive.ics.uci.edu/ml/datasets/Magic) from the [UCI ML repository](http... |
conceptofmind/dialog_submix_original | 2023-04-28T22:41:37.000Z | [
"region:us"
] | conceptofmind | null | null | null | 12 | 130 | ---
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: 1024507265
num_examples: 553869
download_size: 58347... |
fujiki/japanese_alpaca_data | 2023-05-19T12:54:13.000Z | [
"language:ja",
"license:cc-by-nc-sa-4.0",
"region:us"
] | fujiki | null | null | null | 4 | 130 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 24733874
num_examples: 52002
download_size: 13849623
dataset_size: 24733874
license: cc-by-nc-sa-4.0
language:
- ja
pretty_name: jap... |
chansung/llama2-stories | 2023-09-30T21:15:48.000Z | [
"license:apache-2.0",
"region:us"
] | chansung | null | null | null | 2 | 130 | ---
license: apache-2.0
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: title
dtype: string
- name: image
dtype: string
- name: story
dtype: string
splits:
- name: train
num_bytes: 4113688
num_examples: 69
download_s... |
AdaptLLM/law-tasks | 2023-09-26T08:35:23.000Z | [
"arxiv:2309.09530",
"region:us"
] | AdaptLLM | null | null | null | 2 | 130 | ---
configs:
- config_name: SCOTUS
data_files:
- split: test
path: "scotus/test.json"
- config_name: CaseHOLD
data_files:
- split: test
path: "case_hold/test.json"
- config_name: UNFAIR_ToS
data_files:
- split: test
path: "unfair_tos/test.json"
---
# Adapting Large Language Models v... |
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