id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
cyberagent/crello | 2023-09-14T08:33:47.000Z | [
"task_categories:unconditional-image-generation",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cdla-permissive-2.0",
"graphic design",
"design templates",
"arxiv:2... | cyberagent | null | null | 14 | 496 | 2023-02-03T01:31:45 | ---
annotations_creators:
- no-annotation
language:
- en
language_creators:
- found
license: cdla-permissive-2.0
multilinguality:
- monolingual
pretty_name: crello
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- graphic design
- design templates
task_categories:
- unconditional-image-generation
task_i... | 29,774 | [
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0.0026... |
hippocrates/qa_train | 2023-10-03T03:42:29.000Z | [
"region:us"
] | hippocrates | null | null | 0 | 496 | 2023-10-02T00:47:31 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: valid
path: data/valid-*
dataset_info:
features:
- name: id
dtype: string
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
- name: text
dtype... | 686 | [
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arampacha/rsicd | 2022-04-11T15:34:07.000Z | [
"region:us"
] | arampacha | null | null | 3 | 495 | 2022-04-11T15:31:49 | Entry not found | 15 | [
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-0.06036376953125,
0.03790... |
izumi-lab/llm-japanese-dataset | 2023-07-04T15:25:14.000Z | [
"size_categories:1M<n<10M",
"language:ja",
"license:cc-by-sa-4.0",
"arxiv:2305.12720",
"region:us"
] | izumi-lab | null | null | 69 | 495 | 2023-04-30T06:13:24 | ---
license: cc-by-sa-4.0
language:
- ja
size_categories:
- 1M<n<10M
---
# llm-japanese-dataset
LLM構築用の日本語インストラクション(チャット)データセット
主に，英語で構築されたLLMモデルなどに対して，チャット(Instruction)応答タスクに関してLoRAなどでチューニングするために使用できます．
※様々な公開言語資源を利用させていただきました．関係各位にはこの場を借りて御礼申し上げます．
## updates
5/15にAlpaca datasetがNCにライセンス変更されたことに対応し，安心してご利用いただけるよ... | 2,057 | [
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-0.07220458984375,
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0.01... |
yentinglin/traditional_mandarin_instructions | 2023-10-07T08:45:00.000Z | [
"task_categories:conversational",
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:100K<n<1M",
"language:zh",
"license:cc-by-nc-4.0",
"arxiv:2305.13711",
"arxiv:2104.09864",
"region:us"
] | yentinglin | null | null | 14 | 495 | 2023-08-10T06:23:46 | ---
license: cc-by-nc-4.0
task_categories:
- conversational
- text-generation
- text2text-generation
language:
- zh
pretty_name: Traditional Chinese Instruction-tuning Set
size_categories:
- 100K<n<1M
---
# Language Models for Taiwanese Culture
<p align="center">
✍️ <a href="https://huggingface.co/spaces/yentinglin/... | 10,461 | [
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-0.035675048828125,
-0.031494140625,
0.013... |
m3hrdadfi/recipe_nlg_lite | 2021-07-03T09:34:56.000Z | [
"region:us"
] | m3hrdadfi | RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation - Lite version
The dataset we publish contains 7,198 cooking recipes (>7K).
It's processed in more careful way and provides more samples than any other dataset in the area. | @misc{RecipeNLGLite,
author = {Mehrdad Farahani},
title = {RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation (Lite)},
year = 2021,
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {url{https://github.com/m3hrdadfi/reci... | 3 | 494 | 2022-03-02T23:29:22 | # RecipeNLG: A Cooking Recipes Dataset
RecipeNLG: A Cooking Recipes Dataset for Semi-Structured Text Generation - Lite version
The dataset contains `7,198` cooking recipes (`>7K`).
It's processed in more careful way and provides more samples than any other dataset in the area.
## How to use
```bash
pip install git+... | 5,394 | [
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0.06341552734375,
-0.0167999267578125,
-0.04058837890625,
-0.01416015625,
0.0126... |
intfloat/multilingual_cc_news | 2023-04-23T08:19:06.000Z | [
"size_categories:100M<n<1B",
"language:en",
"language:zh",
"language:fr",
"language:de",
"language:af",
"language:ar",
"region:us"
] | intfloat | \
Multilingual CC-News dataset.
This is the processed version from https://huggingface.co/datasets/CloverSearch/cc-news-mutlilingual. | null | 3 | 493 | 2023-03-22T08:25:34 | ---
size_categories:
- 100M<n<1B
language:
- en
- zh
- fr
- de
- af
- ar
---
### Dataset Summary
This dataset is based on [CloverSearch/cc-news-mutlilingual](https://huggingface.co/datasets/CloverSearch/cc-news-mutlilingual).
We add a script to support access multilingual CC-News dataset with HuggingFace datasets AP... | 1,325 | [
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0.025161743... |
IlyaGusev/gazeta | 2023-02-12T00:01:45.000Z | [
"task_categories:summarization",
"annotations_creators:expert-generated",
"annotations_creators:found",
"language_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ru",
"license:unknown",
"arx... | IlyaGusev | null | @InProceedings{10.1007/978-3-030-59082-6_9,
author="Gusev, Ilya",
editor="Filchenkov, Andrey and Kauttonen, Janne and Pivovarova, Lidia",
title="Dataset for Automatic Summarization of Russian News",
booktitle="Artificial Intelligence and Natural Language",
year="2020",
publisher="Springer Intern... | 13 | 492 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
- found
language_creators:
- expert-generated
- found
task_categories:
- summarization
language:
- ru
size_categories:
- 10K<n<100K
license:
- unknown
multilinguality:
- monolingual
source_datasets:
- original
paperswithcode_id: gazeta
---
# Dataset Card for Gazeta
## Tabl... | 10,136 | [
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mattmdjaga/human_parsing_dataset | 2023-09-11T09:07:44.000Z | [
"task_categories:image-segmentation",
"task_ids:semantic-segmentation",
"size_categories:10K<n<100K",
"region:us"
] | mattmdjaga | null | null | 10 | 491 | 2023-03-30T17:59:37 | ---
size_categories:
- 10K<n<100K
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
dataset_info:
features:
- name: image
dtype: image
- name: mask
dtype: image
splits:
- name: train
num_bytes: 5892290030.116
num_examples: 17706
download_size: 5893438158
dataset_size:... | 4,015 | [
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0.0322265625,
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-0.0732421875,
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0.0221710... |
crystina-z/mbert-mrtydi-corpus | 2022-02-01T22:09:24.000Z | [
"region:us"
] | crystina-z | null | null | 0 | 490 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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-0.0604248046875,
0.0379028... |
nchlt | 2023-01-25T14:41:21.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:af",
"language:nr",
"language:nso",
"langu... | null | The development of linguistic resources for use in natural language processingis of utmost importance for the continued growth of research anddevelopment in the field, especially for resource-scarce languages. In this paper we describe the process and challenges of simultaneouslydevelopingmultiple linguistic resources ... | @inproceedings{eiselen2014developing,
title={Developing Text Resources for Ten South African Languages.},
author={Eiselen, Roald and Puttkammer, Martin J},
booktitle={LREC},
pages={3698--3703},
year={2014}
} | 4 | 489 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- af
- nr
- nso
- ss
- tn
- ts
- ve
- xh
- zu
license:
- cc-by-2.5
multilinguality:
- multilingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recogni... | 9,022 | [
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0.02... |
medalpaca/medical_meadow_medqa | 2023-04-06T16:59:02.000Z | [
"task_categories:question-answering",
"language:en",
"language:zh",
"medical",
"region:us"
] | medalpaca | null | null | 29 | 488 | 2023-04-06T16:56:15 | ---
task_categories:
- question-answering
language:
- en
- zh
tags:
- medical
---
# Dataset Card for MedQA
## Dataset Description
- **Paper:**
### Dataset Summary
This is the data and baseline source code for the paper: Jin, Di, et al. "What Disease does this Patient Have? A Large-scale Open Domain Question Answe... | 1,766 | [
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0.0123... |
allocine | 2023-01-25T14:26:09.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:fr",
"license:mit",
"region:us"
] | null | Allocine Dataset: A Large-Scale French Movie Reviews Dataset.
This is a dataset for binary sentiment classification, made of user reviews scraped from Allocine.fr.
It contains 100k positive and 100k negative reviews divided into 3 balanced splits: train (160k reviews), val (20k) and test (20k). | @misc{blard2019allocine,
author = {Blard, Theophile},
title = {french-sentiment-analysis-with-bert},
year = {2020},
publisher = {GitHub},
journal = {GitHub repository},
howpublished={\\url{https://github.com/TheophileBlard/french-sentiment-analysis-with-bert}},
} | 6 | 487 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- fr
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
paperswithcode_id: allocine
pretty_name: Allociné
dataset... | 9,087 | [
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-0.0648193359375,
-0.059661865234375,
0.001877784729003... |
rcds/wikipedia-for-mask-filling | 2023-03-08T12:22:02.000Z | [
"task_categories:fill-mask",
"annotations_creators:other",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"region:us"
] | rcds | \ | null | 0 | 487 | 2023-01-23T15:14:48 | ---
annotations_creators:
- other
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- multilingual
paperswithcode_id: null
pretty_name: "wikipedia pages chunked for fill-mask"
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- fill-mask
---
# preprocessed versio... | 3,995 | [
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0.03436279... |
symanto/autextification2023 | 2023-10-06T13:08:55.000Z | [
"task_categories:text-classification",
"size_categories:10K<n<100K",
"source_datasets:multi_eurlex",
"source_datasets:xsum",
"source_datasets:csebuetnlp/xlsum",
"source_datasets:mlsum",
"source_datasets:amazon_polarity",
"source_datasets:https://sinai.ujaen.es/investigacion/recursos/coah",
"source_d... | symanto | null | null | 0 | 487 | 2023-10-06T12:12:51 | ---
license: cc-by-nc-sa-4.0
task_categories:
- text-classification
language:
- en
- es
pretty_name: AuTexTification 2023
size_categories:
- 10K<n<100K
source_datasets:
- multi_eurlex
- xsum
- csebuetnlp/xlsum
- mlsum
- amazon_polarity
- https://sinai.ujaen.es/investigacion/recursos/coah
- https://sinai.ujaen.es/invest... | 4,390 | [
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0.04449462890... |
assin | 2023-01-25T14:26:50.000Z | [
"task_categories:text-classification",
"task_ids:text-scoring",
"task_ids:natural-language-inference",
"task_ids:semantic-similarity-scoring",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
... | null | The ASSIN (Avaliação de Similaridade Semântica e INferência textual) corpus is a corpus annotated with pairs of sentences written in
Portuguese that is suitable for the exploration of textual entailment and paraphrasing classifiers. The corpus contains pairs of sentences
extracted from news articles written in Europea... | @inproceedings{fonseca2016assin,
title={ASSIN: Avaliacao de similaridade semantica e inferencia textual},
author={Fonseca, E and Santos, L and Criscuolo, Marcelo and Aluisio, S},
booktitle={Computational Processing of the Portuguese Language-12th International Conference, Tomar, Portugal},
pages={13--15},
yea... | 8 | 486 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- text-scoring
- natural-language-inference
- semantic-similarity-scoring
pa... | 9,005 | [
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0.02951049804... |
crystina-z/mbert-mrtydi | 2022-02-01T22:10:30.000Z | [
"region:us"
] | crystina-z | null | null | 0 | 486 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ashraq/fashion-product-images-small | 2022-11-01T20:25:52.000Z | [
"region:us"
] | ashraq | null | null | 10 | 486 | 2022-11-01T20:22:50 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: gender
dtype: string
- name: masterCategory
dtype: string
- name: subCategory
dtype: string
- name: articleType
dtype: string
- name: baseColour
dtype: string
- name: season
dtype: string
- name: year
dtype: fl... | 867 | [
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reciprocate/vicuna-fair-eval | 2023-06-15T14:47:39.000Z | [
"region:us"
] | reciprocate | null | null | 0 | 486 | 2023-06-15T14:47:33 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: selected
dtype: string
- name: rejected
dtype: string
splits:
- name: train
num_bytes: 180638
num_examples: 66
download_size: 116978
dataset_size: 180638
---
# Dataset Card for "vicuna_fair_eval"
[More Information need... | 429 | [
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kyujinpy/KoCoT_2000 | 2023-10-10T13:19:00.000Z | [
"task_categories:text-generation",
"task_categories:text-classification",
"size_categories:1k<n<5k",
"language:en",
"license:cc-by-4.0",
"arxiv:2305.14045",
"region:us"
] | kyujinpy | null | null | 9 | 486 | 2023-09-22T16:41:36 | ---
license: cc-by-4.0
task_categories:
- text-generation
- text-classification
language:
- en
size_categories:
- 1k<n<5k
---
# KoCoT-Collection
Using DeepL dataset, translation about [kaist-CoT](https://huggingface.co/datasets/kaist-ai/CoT-Collection).
---
# Original Dataset Card for Dataset Name
## Dataset Descr... | 1,487 | [
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kyujinpy/KOR-OpenOrca-Platypus | 2023-10-24T06:54:44.000Z | [
"task_categories:conversational",
"task_categories:text-classification",
"task_categories:token-classification",
"task_categories:table-question-answering",
"task_categories:question-answering",
"task_categories:zero-shot-classification",
"task_categories:summarization",
"task_categories:feature-extra... | kyujinpy | null | null | 3 | 485 | 2023-10-09T14:23:30 | ---
language:
- ko
license: cc-by-nc-4.0
size_categories:
- 10K<n<50K
task_categories:
- conversational
- text-classification
- token-classification
- table-question-answering
- question-answering
- zero-shot-classification
- summarization
- feature-extraction
- text-generation
- text2text-generation
pretty_name: OpenO... | 12,951 | [
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swahili_news | 2023-01-25T14:45:11.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:sw",
"license:cc-by-4.0",
"region:us"
] | null | Swahili is spoken by 100-150 million people across East Africa. In Tanzania, it is one of two national languages (the other is English) and it is the official language of instruction in all schools. News in Swahili is an important part of the media sphere in Tanzania.
News contributes to education, technology, and the... | @dataset{davis_david_2020_5514203,
author = {Davis David},
title = {Swahili : News Classification Dataset},
month = dec,
year = 2020,
note = {{The news version contains both train and test sets.}},
publisher = {Zenodo},
version = {0.2},
doi = {10.5281... | 2 | 484 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- sw
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
pretty_name: 'Swahili : News Classification D... | 6,133 | [
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CALM/arwiki | 2022-08-01T16:37:23.000Z | [
"multilinguality:monolingual",
"language:ar",
"license:unknown",
"region:us"
] | CALM | null | null | 1 | 484 | 2022-03-02T23:29:22 | ---
pretty_name: Wikipedia Arabic dumps dataset.
language:
- ar
license:
- unknown
multilinguality:
- monolingual
---
# Arabic Wiki Dataset
## Dataset Summary
This dataset is extracted using [`wikiextractor`](https://github.com/attardi/wikiextractor) tool, from [Wikipedia Arabic pages](https://dumps.wikimedia.org/arw... | 1,498 | [
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nlpaueb/finer-139 | 2022-10-23T05:05:03.000Z | [
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:en",
"license:cc-by-sa-4.0",
"arxiv:2203.06482",
"region:us"
] | nlpaueb | FiNER-139 is a named entity recognition dataset consisting of 10K annual
and quarterly English reports (filings) of publicly traded companies
downloaded from the U.S. Securities and Exchange Commission (SEC)
annotated with 139 XBRL tags in the IOB2 format. | @inproceedings{loukas-etal-2022-finer,
title = "{FiNER: Financial Numeric Entity Recognition for XBRL Tagging}",
author = "Loukas, Lefteris and
Fergadiotis, Manos and
Chalkidis, Ilias and
Spyropoulou, Eirini and
Malakasiotis, Prodromos and
Androutsopoulos, Ion and
Palioura... | 12 | 484 | 2022-03-04T10:00:23 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: FiNER-139
size_categories:
- 1M<n<10M
source_datasets: []
task_categories:
- structure-prediction
- named-entity-recognition
- entity-extraction
task_ids:... | 9,551 | [
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0... |
squad_adversarial | 2022-11-18T21:47:43.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:extended|squad",
"language:en",
"license:mit",
"region:us"
] | null | Here are two different adversaries, each of which uses a different procedure to pick the sentence it adds to the paragraph:
AddSent: Generates up to five candidate adversarial sentences that don't answer the question, but have a lot of words in common with the question. Picks the one that most confuses the model.
AddOn... | @inproceedings{jia-liang-2017-adversarial,
title = "Adversarial Examples for Evaluating Reading Comprehension Systems",
author = "Jia, Robin and
Liang, Percy",
booktitle = "Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing",
month = sep,
year = "2017",
... | 5 | 483 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- found
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- extended|squad
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: null
pretty_name: '''Adversarial Examples for ... | 8,536 | [
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0.018... |
wmt17 | 2023-04-05T13:43:57.000Z | [
"task_categories:translation",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:translation",
"size_categories:10M<n<100M",
"source_datasets:extended|europarl_bilingual",
"source_datasets:extended|news_commentary",
"source_datasets:extended|setimes",
"source_datasets... | null | null | @InProceedings{bojar-EtAl:2017:WMT1,
author = {Bojar, Ond\v{r}ej and Chatterjee, Rajen and Federmann, Christian and Graham, Yvette and Haddow, Barry and Huang, Shujian and Huck, Matthias and Koehn, Philipp and Liu, Qun and Logacheva, Varvara and Monz, Christof and Negri, Matteo and Post, Ma... | 1 | 483 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- cs
- de
- en
- fi
- lv
- ru
- tr
- zh
license:
- unknown
multilinguality:
- translation
size_categories:
- 10M<n<100M
source_datasets:
- extended|europarl_bilingual
- extended|news_commentary
- extended|setimes
- extended|un_multi
task_cat... | 10,203 | [
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0.0152... |
ai4bharat/IndicCOPA | 2022-12-15T11:34:32.000Z | [
"task_categories:multiple-choice",
"task_ids:multiple-choice-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:extended|xcopa",
"language:as",
"language:bn",
"language:en",
"language:go... | ai4bharat | \ | \ | 1 | 483 | 2022-09-20T08:18:35 | ---
annotations_creators:
- expert-generated
language:
- as
- bn
- en
- gom
- gu
- hi
- kn
- mai
- ml
- mr
- ne
- or
- pa
- sa
- sat
- sd
- ta
- te
- ur
language_creators:
- expert-generated
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: IndicXCOPA
size_categories:
- 1K<n<10K
source_datasets:
- exten... | 2,892 | [
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0.0049... |
laion/gpt4v-emotion-dataset | 2023-10-27T01:06:16.000Z | [
"region:us"
] | laion | null | null | 2 | 483 | 2023-10-15T18:25:14 | ---
dataset_info:
features:
- name: caption
dtype: string
- name: link
dtype: string
- name: message_id
dtype: string
- name: timestamp
dtype: string
splits:
- name: train
num_bytes: 204134
num_examples: 96
download_size: 111233
dataset_size: 204134
configs:
- config_name: defa... | 557 | [
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-0.042327880859375... |
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 ... | 2 | 479 | 2022-03-02T23:29:22 | ---
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
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jxie/slurp | 2023-10-25T04:31:33.000Z | [
"region:us"
] | jxie | null | null | 0 | 479 | 2023-10-25T04:13:20 | ---
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: audio
dtype: audio
- name: transcription
dtype: string
splits:
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num_bytes: ... | 720 | [
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Cohere/wikipedia-22-12 | 2023-02-22T15:58:09.000Z | [
"region:us"
] | Cohere | null | null | 26 | 477 | 2023-01-13T21:52:20 | This dataset contains a pre-processed version from Wikipedia suitable for semantic search.
You can load the dataset like this:
```python
from datasets import load_dataset
lang = 'en'
data = load_dataset(f"Cohere/wikipedia-22-12", lang, split='train', streaming=True)
for row in data:
print(row)
break
```
This w... | 3,872 | [
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Critiquers/gsm8k_pairwise | 2023-08-23T19:29:20.000Z | [
"region:us"
] | Critiquers | null | null | 1 | 476 | 2023-08-23T19:29:16 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: selected
dtype: string
- name: rejected
dtype: string
splits:
- name: train
num_bytes: 411013
num_examples: 512
download_size: 234406
dataset_size: 411013
---
# Dataset Card for "gsm8k_pairwise"
[More Information neede... | 428 | [
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IlyaGusev/gpt_roleplay_realm | 2023-05-21T12:43:08.000Z | [
"task_categories:text-generation",
"task_categories:conversational",
"size_categories:1K<n<10K",
"language:ru",
"language:en",
"license:cc-by-4.0",
"gpt-4",
"fictional",
"role-play",
"gpt-3.5",
"art",
"region:us"
] | IlyaGusev | null | null | 42 | 474 | 2023-05-06T23:21:10 | ---
dataset_info:
features:
- name: name
dtype: string
- name: context
dtype: string
- name: greeting
dtype: string
- name: example_dialogue
list:
- name: content
dtype: string
- name: role
dtype: string
- name: topics
sequence: string
- name: dialogues
list:
... | 10,192 | [
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SetFit/amazon_counterfactual_en | 2022-02-11T13:03:45.000Z | [
"arxiv:2104.06893",
"region:us"
] | SetFit | null | null | 0 | 473 | 2022-03-02T23:29:22 | # Amazon Counterfactual Statements
This dataset is the *en-ext* split from [SetFit/amazon_counterfactual](https://huggingface.co/datasets/SetFit/amazon_counterfactual). As the original test set is rather small (1333 examples), a different split was created with 50-50 for training & testing.
The dataset is describ... | 591 | [
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bigbio/ddi_corpus | 2022-12-22T15:44:31.000Z | [
"multilinguality:monolingual",
"language:en",
"license:cc-by-nc-4.0",
"region:us"
] | bigbio | The DDI corpus has been manually annotated with drugs and pharmacokinetics and pharmacodynamics interactions. It contains 1025 documents from two different sources: DrugBank database and MedLine. | @article{HERREROZAZO2013914,
title = {
The DDI corpus: An annotated corpus with pharmacological substances and
drug-drug interactions
},
author = {
María Herrero-Zazo and Isabel Segura-Bedmar and Paloma Martínez and Thierry
Declerck
},
year = 2013,
journal = {Journa... | 2 | 473 | 2022-11-13T22:08:08 |
---
language:
- en
bigbio_language:
- English
license: cc-by-nc-4.0
multilinguality: monolingual
bigbio_license_shortname: CC_BY_NC_4p0
pretty_name: DDI Corpus
homepage: https://github.com/isegura/DDICorpus
bigbio_pubmed: True
bigbio_public: True
bigbio_tasks:
- NAMED_ENTITY_RECOGNITION
- RELATION_EXTRACTION
---
... | 1,404 | [
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minh21/cpgQA-v1.0-unique-context | 2023-08-30T13:16:37.000Z | [
"region:us"
] | minh21 | null | null | 0 | 473 | 2023-08-30T13:05:48 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: title
dtype: string
- name: id
dtype: int64
- name: question
dtype: string
- name: answer_text
dtype: string
- name: answer_start
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celikmus/mayo_clinic_symptoms_and_diseases_v1 | 2023-07-16T19:37:52.000Z | [
"language:en",
"region:us"
] | celikmus | null | null | 6 | 470 | 2023-03-21T21:31:15 | ---
language: en
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 1321926
num_examples: 1058
download_size: 626009
dataset_size: 1321926
---
# Dataset Card for "mayo_clinic_symptoms_and_diseases_v1"
[More Information needed](h... | 424 | [
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nampdn-ai/tiny-codes | 2023-09-30T04:14:36.000Z | [
"task_categories:text-generation",
"size_categories:1M<n<10M",
"language:en",
"license:mit",
"arxiv:2306.11644",
"arxiv:2305.07759",
"doi:10.57967/hf/0937",
"region:us"
] | nampdn-ai | null | null | 131 | 469 | 2023-07-16T07:26:18 | ---
license: mit
task_categories:
- text-generation
language:
- en
pretty_name: Tiny Codes
size_categories:
- 1M<n<10M
---
# Reasoning with Language and Code
This synthetic dataset is a collection of **1.6 millions short and clear code snippets** that can help LLM models learn how to reason with both natural and progr... | 3,657 | [
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segments/sidewalk-semantic | 2023-07-10T08:09:07.000Z | [
"task_categories:image-segmentation",
"task_ids:semantic-segmentation",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"size_categories:n<1K",
"source_datasets:original",
"license:cc-by-nc-4.0",
"region:us"
] | segments | null | null | 20 | 468 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- expert-generated
license: cc-by-nc-4.0
multilinguality: []
pretty_name: sidewalk-semantic
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
---
# Dataset Card for s... | 4,257 | [
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ignmilton/ign_clean_instruct_dataset_500k | 2023-06-13T07:45:51.000Z | [
"task_categories:question-answering",
"task_categories:conversational",
"size_categories:100K<n<1M",
"language:en",
"license:apache-2.0",
"code",
"region:us"
] | ignmilton | null | null | 18 | 468 | 2023-06-12T07:12:30 | ---
license: apache-2.0
task_categories:
- question-answering
- conversational
language:
- en
tags:
- code
pretty_name: ign_500k
size_categories:
- 100K<n<1M
---
This dataset contains ~508k prompt-instruction pairs with high quality responses. It was synthetically created from a subset of Ultrachat prompts. It does n... | 406 | [
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0... |
google_wellformed_query | 2022-11-18T20:04:48.000Z | [
"task_categories:text-classification",
"task_ids:text-scoring",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended",
"language:en",
"license:cc-by-sa-4.0",
"arxiv:1808.09419",
"region:us"
] | null | Google's query wellformedness dataset was created by crowdsourcing well-formedness annotations for 25,100 queries from the Paralex corpus. Every query was annotated by five raters each with 1/0 rating of whether or not the query is well-formed. | @misc{faruqui2018identifying,
title={Identifying Well-formed Natural Language Questions},
author={Manaal Faruqui and Dipanjan Das},
year={2018},
eprint={1808.09419},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 8 | 467 | 2022-03-02T23:29:22 | ---
task_categories:
- text-classification
multilinguality:
- monolingual
task_ids:
- text-scoring
language:
- en
annotations_creators:
- crowdsourced
source_datasets:
- extended
size_categories:
- 10K<n<100K
license:
- cc-by-sa-4.0
paperswithcode_id: null
pretty_name: GoogleWellformedQuery
language_creators:
- found
d... | 5,387 | [
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0.026... |
rcds/swiss_judgment_prediction | 2023-06-14T11:59:24.000Z | [
"task_categories:text-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:de",
"language:fr",
"language:it",
"language:en",
"license:cc-by-sa-4.0",
"judgement-prediction",
... | rcds | Swiss-Judgment-Prediction is a multilingual, diachronic dataset of 85K Swiss Federal Supreme Court (FSCS) cases annotated with the respective binarized judgment outcome (approval/dismissal), posing a challenging text classification task. We also provide additional metadata, i.e., the publication year, the legal area an... | @InProceedings{niklaus-etal-2021-swiss,
author = {Niklaus, Joel
and Chalkidis, Ilias
and Stürmer, Matthias},
title = {Swiss-Court-Predict: A Multilingual Legal Judgment Prediction Benchmark},
booktitle = {Proceedings of the 2021 Natural Legal Language Processing Workshop},
year =... | 11 | 466 | 2022-03-02T23:29:22 | ---
pretty_name: Swiss-Judgment-Prediction
annotations_creators:
- found
language_creators:
- found
language:
- de
- fr
- it
- en
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids: []
tags:
- judgement-predic... | 19,945 | [
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0... |
EleutherAI/pile-deduped-pythia-random-sampled | 2023-08-25T07:26:47.000Z | [
"region:us"
] | EleutherAI | null | null | 2 | 466 | 2023-03-29T13:15:01 | ---
dataset_info:
features:
- name: Index
dtype: int64
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dtype: float64
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KShivendu/dbpedia-entities-openai-1M | 2023-07-07T08:35:48.000Z | [
"size_categories:1M<n<10M",
"language:en",
"license:mit",
"region:us"
] | KShivendu | null | null | 8 | 465 | 2023-06-20T22:29:43 | ---
license: mit
dataset_info:
features:
- name: _id
dtype: string
- name: title
dtype: string
- name: text
dtype: string
- name: openai
sequence: float32
splits:
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num_bytes: 12383152
num_examples: 1000000
download_size: 12383152
dataset_size: 1000000
language:
- e... | 944 | [
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BeIR/msmarco-qrels | 2022-10-23T06:05:55.000Z | [
"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 | 1 | 464 | 2022-06-05T17:26:07 | ---
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:
... | 13,988 | [
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opus_rf | 2023-06-01T14:59:53.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:sv",
"license:unknown",
"region:us"
] | null | RF is a tiny parallel corpus of the Declarations of the Swedish Government and its translations. | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 0 | 463 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- expert-generated
language:
- de
- en
- es
- fr
- sv
license:
- unknown
multilinguality:
- multilingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: OpusRf
dataset_info:
- config... | 6,435 | [
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0.02653503... |
vietgpt/the_pile_openwebtext2 | 2023-07-15T09:20:18.000Z | [
"language:en",
"region:us"
] | vietgpt | null | null | 1 | 463 | 2023-04-11T19:24:36 | ---
language: en
dataset_info:
features:
- name: title
dtype: string
- name: text
dtype: string
- name: reddit_scores
sequence: int32
splits:
- name: train
num_bytes: 68786199155
num_examples: 17103059
download_size: 42444568964
dataset_size: 68786199155
---
# Dataset Card for "the_p... | 470 | [
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yangwang825/sst2-textfooler | 2023-10-09T22:09:14.000Z | [
"region:us"
] | yangwang825 | null | null | 0 | 463 | 2023-10-09T21:11:56 | # Stanford Sentiment Treebank - Binary | 38 | [
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gsarti/clean_mc4_it | 2022-10-23T09:01:21.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"source_datasets:extended",
"language:it",
"license:odc-by",
"arxiv:1910.10683",
"arxiv:2203.03759",
"region:us"
] | gsarti | A thoroughly cleaned version of the Italian portion of the multilingual
colossal, cleaned version of Common Crawl's web crawl corpus (mC4) by AllenAI.
Based on Common Crawl dataset: "https://commoncrawl.org".
This is the processed version of Google's mC4 dataset by AllenAI, with further cleaning
detailed in the repo... | @article{JMLR:v21:20-074,
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 = {Journal of Machine Learn... | 6 | 462 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- it
license:
- odc-by
multilinguality:
- monolingual
size_categories:
tiny:
- 1M<n<10M
small:
- 10M<n<100M
medium:
- 10M<n<100M
large:
- 10M<n<100M
full:
- 100M<n<1B
source_datasets:
- extended
task_categories:
- text-ge... | 9,902 | [
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embedding-data/QQP_triplets | 2022-08-02T03:14:14.000Z | [
"task_categories:sentence-similarity",
"task_ids:semantic-similarity-classification",
"language:en",
"license:mit",
"region:us"
] | embedding-data | null | null | 3 | 462 | 2022-07-08T03:15:59 | ---
license: mit
language:
- en
paperswithcode_id: embedding-data/QQP_triplets
pretty_name: QQP_triplets
task_categories:
- sentence-similarity
- paraphrase-mining
task_ids:
- semantic-similarity-classification
---
# Dataset Card for "QQP_triplets"
## Table of Contents
- [Dataset Description](#dataset-description)
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detection-datasets/fashionpedia | 2022-09-22T13:22:02.000Z | [
"task_categories:object-detection",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"object-detection",
"fashion",
"computer-vision",
"arxiv:2004.12276",
"region:us"
] | detection-datasets | null | null | 25 | 462 | 2022-09-22T10:33:24 | ---
pretty_name: Fashionpedia
task_categories:
- object-detection
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
tags:
- object-detection
- fashion
- computer-vision
paperswithcode_id: fashionpedia
---
# Dataset Card for Fashionpedia
## Tab... | 5,214 | [
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voiceintelligenceresearch/MOCKS | 2023-10-27T15:55:12.000Z | [
"annotations_creators:expert-generated",
"multilinguality:multilingual",
"language:en",
"language:de",
"language:es",
"language:fr",
"language:it",
"license:cc-by-4.0",
"license:mpl-2.0",
"region:us"
] | voiceintelligenceresearch | Multilingual Open Custom Keyword Spotting Testset (MOCKS) is a comprehensive
audio testset for evaluation and benchmarking Open-Vocabulary Keyword Spotting (OV-KWS) models. | @inproceedings{pudo23_interspeech,
author={Mikołaj Pudo and Mateusz Wosik and Adam Cieślak and Justyna Krzywdziak and Bożena Łukasiak and Artur Janicki},
title={{MOCKS} 1.0: Multilingual Open Custom Keyword Spotting Testset},
year={2023},
booktitle={Proc. Interspeech 2023},
} | 0 | 462 | 2023-02-20T13:40:22 | ---
annotations_creators:
- expert-generated
language:
- en
- de
- es
- fr
- it
license:
- cc-by-4.0
- mpl-2.0
multilinguality:
- multilingual
dataset_info:
- config_name: config
features:
- name: audio_id
dtype: string
- name: audio
dtype:
audio:
sampling_rate: 16000
- name: text
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ywchoi/pubmed_abstract_0 | 2022-09-13T00:53:42.000Z | [
"region:us"
] | ywchoi | null | null | 1 | 461 | 2022-09-13T00:52:06 | Entry not found | 15 | [
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opus_ubuntu | 2023-06-01T14:59:53.000Z | [
"task_categories:translation",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"size_categories:1K<n<10K",
"size_categories:n<1K",
"source_datasets:original",
"language:ace",
"l... | null | A parallel corpus of Ubuntu localization files. Source: https://translations.launchpad.net
244 languages, 23,988 bitexts
total number of files: 30,959
total number of tokens: 29.84M
total number of sentence fragments: 7.73M | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 1 | 460 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- found
language:
- ace
- af
- ak
- am
- an
- ang
- ar
- ary
- as
- ast
- az
- ba
- bal
- be
- bem
- ber
- bg
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-... | 8,982 | [
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opus_dgt | 2023-06-01T14:59:53.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:bg",
"language:cs",
"language:da",
"language:de",... | null | A collection of translation memories provided by the JRC. Source: https://ec.europa.eu/jrc/en/language-technologies/dgt-translation-memory
25 languages, 299 bitexts
total number of files: 817,410
total number of tokens: 2.13G
total number of sentence fragments: 113.52M | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 1 | 458 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
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license:
- unknown
multilinguality:
- multilingual
size_categories:
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- 10K<n<100K
- 1M<n<10M
source_datasets:
- o... | 7,872 | [
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open-source-metrics/model-repos-stats | 2023-07-03T01:35:17.000Z | [
"region:us"
] | open-source-metrics | null | null | 5 | 458 | 2022-09-26T15:54:28 | ---
dataset_info:
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Fazzie/Teyvat | 2022-12-13T02:09:42.000Z | [
"task_categories:text-to-image",
"annotations_creators:no-annotation",
"language_creators:found",
"source_datasets:original",
"language:en",
"license:unknown",
"region:us"
] | Fazzie | Teyvat is the first small-scale text-to-image prompt dataset for Genshin impact. | null | 18 | 458 | 2022-11-16T03:47:33 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
source_datasets:
- original
task_categories:
- text-to-image
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
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num_bytes: 71202
num_examples:... | 2,379 | [
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miam | 2023-06-01T14:59:51.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_categories:text-classification",
"task_ids:dialogue-modeling",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:mult... | null | Multilingual dIalogAct benchMark is a collection of resources for training, evaluating, and
analyzing natural language understanding systems specifically designed for spoken language. Datasets
are in English, French, German, Italian and Spanish. They cover a variety of domains including
spontaneous speech, scripted sce... | @unpublished{
anonymous2021cross-lingual,
title={Cross-Lingual Pretraining Methods for Spoken Dialog},
author={Anonymous},
journal={OpenReview Preprint},
year={2021},
url{https://openreview.net/forum?id=c1oDhu_hagR},
note={anonymous preprint under review}
} | 3 | 456 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- de
- en
- es
- fr
- it
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
- text-classification
task_ids:
- dialogu... | 15,693 | [
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potsawee/wiki_bio_gpt3_hallucination | 2023-05-29T23:14:09.000Z | [
"task_categories:text-classification",
"size_categories:n<1K",
"language:en",
"license:cc-by-sa-3.0",
"arxiv:2303.08896",
"region:us"
] | potsawee | null | null | 9 | 455 | 2023-03-18T18:05:21 | ---
license: cc-by-sa-3.0
task_categories:
- text-classification
language:
- en
size_categories:
- n<1K
dataset_info:
features:
- name: gpt3_text
dtype: string
- name: wiki_bio_text
dtype: string
- name: gpt3_sentences
sequence: string
- name: annotation
sequence: string
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zxvix/squad_text_new | 2023-10-23T08:59:56.000Z | [
"region:us"
] | zxvix | null | null | 0 | 454 | 2023-10-20T12:37:52 | ---
configs:
- config_name: default
data_files:
- split: annotated
path: data/annotated-*
- split: augmented
path: data/augmented-*
- split: augmented_2
path: data/augmented_2-*
dataset_info:
features:
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shibing624/AdvertiseGen | 2023-05-12T07:25:00.000Z | [
"task_categories:text-generation",
"language:zh",
"license:cc-by-4.0",
"text-generation",
"e-commerce advertise",
"region:us"
] | shibing624 | null | null | 15 | 453 | 2023-03-28T02:42:56 | ---
license: cc-by-4.0
language:
- zh
tags:
- text-generation
- e-commerce advertise
pretty_name: AdvertiseGen
task_categories:
- text-generation
---
# Dataset Card for AdvertiseGen
- **formal url:** https://www.luge.ai/#/luge/dataDetail?id=9
## Dataset Description
数据集介绍
AdvertiseGen是电商广告文案生成数据集。
AdvertiseGen以商品网页... | 1,262 | [
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pvduy/arena_synth | 2023-08-02T16:02:03.000Z | [
"region:us"
] | pvduy | null | null | 0 | 453 | 2023-08-02T16:01:59 | ---
dataset_info:
features:
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splits:
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num_bytes: 53190421
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num_bytes: 14269380
num_examples: 8000
download_size: 36514341
dataset_size: 674... | 495 | [
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shunk031/MSCOCO | 2023-10-30T14:06:39.000Z | [
"task_categories:image-segmentation",
"task_categories:object-detection",
"task_categories:other",
"task_ids:instance-segmentation",
"task_ids:semantic-segmentation",
"task_ids:panoptic-segmentation",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"s... | shunk031 | 0 | 453 | 2023-09-09T08:15:05 | ---
annotations_creators:
- crowdsourced
language:
- en
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: MSCOCO
size_categories: []
source_datasets:
- original
tags:
- image-captioning
- object-detection
- keypoint-detection
- stuff-segmentation
- panoptic-segmentation
task_ca... | 8,349 | [
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mdd | 2023-06-01T14:59:51.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:dialogue-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"licen... | null | The Movie Dialog dataset (MDD) is designed to measure how well
models can perform at goal and non-goal orientated dialog
centered around the topic of movies (question answering,
recommendation and discussion). | @misc{dodge2016evaluating,
title={Evaluating Prerequisite Qualities for Learning End-to-End Dialog Systems},
author={Jesse Dodge and Andreea Gane and Xiang Zhang and Antoine Bordes and Sumit Chopra and Alexander Miller and Arthur Szlam and Jason Weston},
year={2016},
eprint={1511.06931},
a... | 3 | 452 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- cc-by-3.0
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- dialogue-modeling
paperswithcode_id: mdd
pretty_name: Mov... | 7,314 | [
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Dahoas/prompted_hf_cot_gsm8k | 2023-10-16T10:36:06.000Z | [
"region:us"
] | Dahoas | null | null | 0 | 449 | 2023-10-12T10:20:39 | ---
dataset_info:
features:
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dtype: string
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num_bytes: 3184819
num_examples: 1319
- name: va... | 596 | [
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llm-book/ner-wikipedia-dataset | 2023-07-25T17:19:14.000Z | [
"task_categories:token-classification",
"size_categories:1K<n<10K",
"language:ja",
"license:cc-by-sa-3.0",
"region:us"
] | llm-book | null | @inproceedings{omi-2021-wikipedia,
title = "Wikipediaを用いた日本語の固有表現抽出のデータセットの構築",
author = "近江 崇宏",
booktitle = "言語処理学会第27回年次大会",
year = "2021",
url = "https://anlp.jp/proceedings/annual_meeting/2021/pdf_dir/P2-7.pdf",
} | 0 | 448 | 2023-04-15T10:43:21 | ---
language:
- ja
license:
- cc-by-sa-3.0
size_categories:
- 1K<n<10K
task_categories:
- token-classification
---
# Dataset Card for llm-book/ner-wikipedia-dataset
書籍『大規模言語モデル入門』で使用する、ストックマーク株式会社により作成された「Wikipediaを用いた日本語の固有表現抽出データセット」(Version 2.0)です。
Githubリポジトリ[stockmarkteam/ner-wikipedia-dataset](https://github.c... | 707 | [
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euirim/goodwiki | 2023-09-11T04:56:26.000Z | [
"task_categories:text-generation",
"task_categories:summarization",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"region:us"
] | euirim | null | null | 21 | 448 | 2023-09-09T08:31:30 | ---
license: mit
task_categories:
- text-generation
- summarization
language:
- en
pretty_name: GoodWiki
size_categories:
- 10K<n<100K
---
# GoodWiki Dataset
GoodWiki is a 179 million token dataset of English Wikipedia articles collected on **September 4, 2023**, that have been marked as [Good](https://en.wikipedia.o... | 10,447 | [
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ai4bharat/IndicQA | 2023-06-20T03:03:32.000Z | [
"task_categories:question-answering",
"task_ids:closed-domain-qa",
"annotations_creators:expert-generated",
"language_creators:found",
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"language:as",
"language:bn",
"language:gu",
"language:hi",
"language:kn",
... | ai4bharat | \ | \ | 1 | 447 | 2022-09-15T04:52:16 | ---
annotations_creators:
- expert-generated
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
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- ta
- te
language_creators:
- found
license:
- cc-by-4.0
multilinguality:
- multilingual
pretty_name: IndicQA
size_categories:
- n<1K
source_datasets:
- original
tags: []
task_categories:
- question-answering
task_ids:
... | 2,826 | [
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KETI-AIR/kor_corpora | 2021-09-16T07:32:28.000Z | [
"region:us"
] | KETI-AIR | null | null | 0 | 445 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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vietgpt/wikipedia_vi | 2023-09-16T05:11:18.000Z | [
"task_categories:text-generation",
"size_categories:1M<n<10M",
"language:vi",
"LM",
"region:us"
] | vietgpt | null | null | 4 | 445 | 2023-02-21T20:39:38 | ---
dataset_info:
features:
- name: id
dtype: int64
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splits:
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num_bytes: 1053551922.960177
num_examples: 1284930
download_size: 569515706
dataset_size:... | 632 | [
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sradc/chunked-shuffled-wikipedia20220301en-bookcorpusopen | 2023-07-17T20:33:04.000Z | [
"language:en",
"region:us"
] | sradc | null | null | 1 | 445 | 2023-05-03T17:40:58 | ---
language: en
dataset_info:
features:
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dtype: string
splits:
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num_bytes: 26076989556
num_examples: 33536113
download_size: 17380043798
dataset_size: 26076989556
---
# Dataset Card for "wikipedia20220301en-bookcorpusopen-chunked-shuffled"
```
num_examples: 33.5 milli... | 1,266 | [
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TrainingDataPro/email-spam-classification | 2023-09-14T16:37:38.000Z | [
"task_categories:text-classification",
"language:en",
"license:cc-by-nc-nd-4.0",
"finance",
"code",
"region:us"
] | TrainingDataPro | null | null | 1 | 445 | 2023-07-25T12:09:29 | ---
license: cc-by-nc-nd-4.0
task_categories:
- text-classification
language:
- en
tags:
- finance
- code
---
# Email Spam Classification
The dataset consists of a collection of emails categorized into two major classes: **spam** and **not spam**. It is designed to facilitate the development and evaluation of spam de... | 2,566 | [
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0.019775390625,
0.002033233642578125,
0.0134735107421875,
-0.01383209228515625,
-0.026092529296875,
0.011199951171875,
0.0709228515625,
-0.03924560546875,
-0.06414794921875,
-0.07073974609375,
0.00... |
opus_wikipedia | 2023-06-01T14:59:51.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ar",
"language:bg",
"language:cs",
"language:de",
"language:el",
"language:... | null | This is a corpus of parallel sentences extracted from Wikipedia by Krzysztof Wołk and Krzysztof Marasek. Please cite the following publication if you use the data: Krzysztof Wołk and Krzysztof Marasek: Building Subject-aligned Comparable Corpora and Mining it for Truly Parallel Sentence Pairs., Procedia Technology, 18,... | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 4 | 443 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
- bg
- cs
- de
- el
- en
- es
- fa
- fr
- he
- hu
- it
- nl
- pl
- pt
- ro
- ru
- sl
- tr
- vi
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 100K<n<1M
- 10K<n<100K
source_datasets:
- original
task_categories:
- translati... | 6,867 | [
[
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0.0207061767578125,
0.0285186767578125,
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0.0323486328125,
0.023345947265625,
-0.042083740234375,
-0.06427001953125,
-0.03582763671875,
0.0439453... |
embedding-data/sentence-compression | 2022-08-02T03:02:47.000Z | [
"task_categories:sentence-similarity",
"task_ids:semantic-similarity-classification",
"language:en",
"license:mit",
"region:us"
] | embedding-data | null | null | 10 | 442 | 2022-07-07T22:58:31 | ---
license: mit
language:
- en
paperswithcode_id: embedding-data/sentence-compression
pretty_name: sentence-compression
task_categories:
- sentence-similarity
- paraphrase-mining
task_ids:
- semantic-similarity-classification
---
# Dataset Card for "sentence-compression"
## Table of Contents
- [Dataset Description]... | 4,878 | [
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0.0263214111328125,
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0... |
skytnt/anime-segmentation | 2022-10-03T01:35:40.000Z | [
"task_categories:image-segmentation",
"task_ids:semantic-segmentation",
"size_categories:10K<n<100K",
"source_datasets:original",
"license:cc0-1.0",
"region:us"
] | skytnt | A segmentation dataset for anime character | null | 18 | 441 | 2022-09-30T05:27:06 | ---
annotations_creators: []
language: []
language_creators: []
license:
- cc0-1.0
multilinguality: []
pretty_name: Anime Segmentation
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
---
## Dataset Description
A segmentation da... | 1,797 | [
[
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0.01059722900390625,
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0.055419921875,
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-0.0665283203125,
-0.031402587890625,
0.00405... |
Multimodal-Fatima/FGVC_Aircraft_train | 2023-05-04T05:30:31.000Z | [
"region:us"
] | Multimodal-Fatima | null | null | 0 | 441 | 2022-11-13T05:05:42 | ---
dataset_info:
features:
- name: image
dtype: image
- name: family
dtype:
class_label:
names:
'0': A300
'1': A310
'2': A320
'3': A330
'4': A340
'5': A380
'6': ATR-42
'7': ATR-72
'8': An-12
... | 6,827 | [
[
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0.021514892578125,
-0.0611572265625,
-0.032135009765625,
-0.0364990234375,... |
nlpai-lab/openassistant-guanaco-ko | 2023-06-01T10:44:35.000Z | [
"task_categories:text-generation",
"task_categories:question-answering",
"task_categories:summarization",
"size_categories:1K<n<10K",
"language:ko",
"license:apache-2.0",
"region:us"
] | nlpai-lab | null | null | 4 | 441 | 2023-06-01T06:54:34 | ---
license: apache-2.0
task_categories:
- text-generation
- question-answering
- summarization
language:
- ko
size_categories:
- 1K<n<10K
---
### Dataset Summary
Korean translation of Guanaco via the DeepL API
Note: There are cases where multilingual data has been converted to monolingual data during batch translat... | 779 | [
[
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-0.0389404296875,
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0.04632568359375,
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-0.07769775390625,
-0.035614013671875,
... |
cfq | 2023-04-05T09:42:18.000Z | [
"task_categories:question-answering",
"task_categories:other",
"task_ids:open-domain-qa",
"task_ids:closed-domain-qa",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:en",
... | null | The CFQ dataset (and it's splits) for measuring compositional generalization.
See https://arxiv.org/abs/1912.09713.pdf for background.
Example usage:
data = datasets.load_dataset('cfq/mcd1') | @inproceedings{Keysers2020,
title={Measuring Compositional Generalization: A Comprehensive Method on
Realistic Data},
author={Daniel Keysers and Nathanael Sch\"{a}rli and Nathan Scales and
Hylke Buisman and Daniel Furrer and Sergii Kashubin and
Nikola Momchev and Danila Sinopalnikov and... | 2 | 440 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Compositional Freebase Questions
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- question-answering
- other
task_ids:
- open-domain-... | 11,384 | [
[
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-0.061370849609375,
-0.034454345703125,
0.009... |
togethercomputer/RedPajama-Data-V2 | 2023-10-31T12:03:06.000Z | [
"task_categories:text-generation",
"language:en",
"language:de",
"language:fr",
"language:es",
"language:it",
"arxiv:2302.03169",
"arxiv:2302.13971",
"arxiv:2204.02311",
"arxiv:2112.06905",
"arxiv:1910.10683",
"arxiv:2305.13169",
"arxiv:2306.01116",
"arxiv:2112.11446",
"region:us"
] | togethercomputer | RedPajama V2: an Open Dataset for Training Large Language Models | null | 125 | 440 | 2023-10-26T01:15:21 | ---
task_categories:
- text-generation
language:
- en
- de
- fr
- es
- it
pretty_name: Red Pajama V2 Dataset
---
### Getting Started
RedPajama-V2 is an open dataset for training large language models. The dataset includes over 100B text
documents coming from 84 CommonCrawl snapshots and processed using
th... | 39,714 | [
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0.04443359375,
0.05780029296875,
-0.04248046875,
-0.04766845703125,
-0.055877685546875,
0.0098037719... |
QingyiSi/Alpaca-CoT | 2023-09-14T08:52:10.000Z | [
"language:en",
"language:zh",
"language:ml",
"license:apache-2.0",
"Instruction",
"Cot",
"region:us"
] | QingyiSi | null | null | 517 | 438 | 2023-03-25T14:58:30 | ---
language:
- en
- zh
- ml
tags:
- Instruction
- Cot
license: apache-2.0
datasets:
- dataset1
- dataset2
---
# Instruction-Finetuning Dataset Collection (Alpaca-CoT)
This repository will continuously collect various instruction tuning datasets. And we standardize different datasets into the same format, which... | 8,261 | [
[
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0.036834716796875,
-0.04803466796875,
-0.060150146484375,
-0.03765869140625,
0.00393676... |
NathanGavenski/CartPole-v1 | 2023-11-01T18:24:38.000Z | [
"size_categories:10M<n<100M",
"license:mit",
"Imitation Learning",
"Expert Trajectory",
"region:us"
] | NathanGavenski | null | null | 2 | 438 | 2023-10-24T17:30:02 | ---
license: mit
tags:
- Imitation Learning
- Expert Trajectory
pretty_name: CartPole-v1 Expert Dataset
size_categories:
- 10M<n<100M
---
# CartPole-v1 - Imitation Learning Datasets
This is a dataset created by [Imitation Learning Datasets](https://github.com/NathanGavenski/IL-Datasets) project.
It was created by us... | 1,358 | [
[
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-0.03872680... |
brwac | 2022-11-03T16:16:00.000Z | [
"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:1M<n<10M",
"source_datasets:original",
"language:pt",
... | null | The BrWaC (Brazilian Portuguese Web as Corpus) is a large corpus constructed following the Wacky framework,
which was made public for research purposes. The current corpus version, released in January 2017, is composed by
3.53 million documents, 2.68 billion tokens and 5.79 million types. Please note that this resource... | @inproceedings{wagner2018brwac,
title={The brwac corpus: A new open resource for brazilian portuguese},
author={Wagner Filho, Jorge A and Wilkens, Rodrigo and Idiart, Marco and Villavicencio, Aline},
booktitle={Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)},... | 8 | 437 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- pt
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: brwac
p... | 5,598 | [
[
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0.0240936279296875,
0.041259765625,
-0.03717041015625,
-0.07452392578125,
-0.041900634765625,
0... |
german_legal_entity_recognition | 2023-01-25T14:30:49.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:n<1K",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"region:us"
] | null | \ | @inproceedings{leitner2019fine,
author = {Elena Leitner and Georg Rehm and Julian Moreno-Schneider},
title = {{Fine-grained Named Entity Recognition in Legal Documents}},
booktitle = {Semantic Systems. The Power of AI and Knowledge
Graphs. Proceedings of the 15th International Conference
... | 1 | 437 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- de
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
paperswithcode_id: legal-documents-entity-recognitio... | 12,063 | [
[
-0.03363037109375,
-0.033477783203125,
0.0205535888671875,
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-0.036041259765625,
0.034027099609375,
0.037628173828125,
-0.03375244140625,
-0.08905029296875,
-0.05438232421875,
... |
juletxara/xquad_xtreme | 2022-10-12T08:43:41.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:multilingual",
"size_categories:unknown",
"source_datasets:extended|squad",
"language:en",
"language:es",
"language:de",
"language:el",
... | juletxara | XQuAD (Cross-lingual Question Answering Dataset) is a benchmark dataset for evaluating cross-lingual question answering
performance. The dataset consists of a subset of 240 paragraphs and 1190 question-answer pairs from the development set
of SQuAD v1.1 (Rajpurkar et al., 2016) together with their professional translat... | @article{Artetxe:etal:2019,
author = {Mikel Artetxe and Sebastian Ruder and Dani Yogatama},
title = {On the cross-lingual transferability of monolingual representations},
journal = {CoRR},
volume = {abs/1910.11856},
year = {2019},
archivePrefix = {arXiv},
eprin... | 5 | 436 | 2022-05-30T10:49:17 | ---
pretty_name: XQuAD-XTREME
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
- es
- de
- el
- hi
- th
- ru
- tr
- ar
- vi
- zh
- ro
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- unknown
source_datasets:
- extended|squad
task_categories:
- quest... | 10,143 | [
[
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0.0478515625,
0.033538818359375,
-0.071533203125,
-0.05548095703125,
-0.030853271484375,
0.029... |
iohadrubin/wikitext-103-raw-v1 | 2022-08-14T13:41:10.000Z | [
"region:us"
] | iohadrubin | null | null | 2 | 435 | 2022-08-14T13:40:34 | Entry not found | 15 | [
[
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0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
peoples_daily_ner | 2023-01-25T14:42:22.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:zh",
"license:unknown",
"region:us"
] | null | People's Daily NER Dataset is a commonly used dataset for Chinese NER, with
text from People's Daily (人民日报), the largest official newspaper.
The dataset is in BIO scheme. Entity types are: PER (person), ORG (organization)
and LOC (location). | null | 6 | 434 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- zh
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: People's Daily NER
dataset_info:
... | 3,484 | [
[
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0.0272369384765625,
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-0.01934814453125,
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0.0496826171875,
0.046600341796875,
-0.05328369140625,
-0.07452392578125,
-0.0404052734375,
... |
Cohere/wikipedia-22-12-simple-embeddings | 2023-03-22T16:56:34.000Z | [
"task_categories:text-retrieval",
"task_ids:document-retrieval",
"multilinguality:multilingual",
"language:en",
"license:apache-2.0",
"region:us"
] | Cohere | null | null | 39 | 434 | 2023-01-13T23:25:25 | ---
language:
- en
multilinguality:
- multilingual
size_categories: []
source_datasets: []
tags: []
task_categories:
- text-retrieval
license:
- apache-2.0
task_ids:
- document-retrieval
---
# Wikipedia (simple English) embedded with cohere.ai `multilingual-22-12` encoder
We encoded [Wikipedia (simple English)](... | 3,843 | [
[
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-0.04962158203125,
0.01317596435546875,
0.0011091232299804688,
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-0.0236053466796875,
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0.044342041015625,
-0.0013570785522460938,
-0.038848876953125,
-0.06353759765625,
-0.04650878906... |
kaitchup/ultrachat-100k-flattened | 2023-10-19T15:13:49.000Z | [
"region:us"
] | kaitchup | null | null | 2 | 434 | 2023-10-19T15:07:12 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: text
dtype: string
splits:
- name: train
num_bytes: 632072903
num_examples: 100000
- name: test
num_bytes: 32563073
num_examples: ... | 811 | [
[
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0.046295166015625,
0.05987548828125,
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0.01081085205078125,
... |
igbo_monolingual | 2023-06-01T14:59:53.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
"task_ids:masked-language-modeling",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"size_categories:n<1K",
"source_datasets:original",... | null | A dataset is a collection of Monolingual Igbo sentences. | @misc{ezeani2020igboenglish,
title={Igbo-English Machine Translation: An Evaluation Benchmark},
author={Ignatius Ezeani and Paul Rayson and Ikechukwu Onyenwe and Chinedu Uchechukwu and Mark Hepple},
year={2020},
eprint={2004.00648},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 1 | 433 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ig
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
- n<1K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
paperswithcode_id: null
pre... | 8,968 | [
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-0.06658935546875,
-0.05828857421875,
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0.0283... |
HuggingFaceH4/testing_codealpaca_small | 2023-04-12T21:57:24.000Z | [
"region:us"
] | HuggingFaceH4 | null | null | 3 | 433 | 2023-04-12T21:57:20 | ---
dataset_info:
features:
- name: prompt
dtype: string
- name: completion
dtype: string
splits:
- name: train
num_bytes: 31503
num_examples: 100
- name: test
num_bytes: 29802
num_examples: 100
download_size: 44006
dataset_size: 61305
---
# Dataset Card for "testing_codealpaca_s... | 458 | [
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sordonia/my-wiki-latex_mmlu_from_valid_all | 2023-10-11T01:19:27.000Z | [
"region:us"
] | sordonia | null | null | 0 | 433 | 2023-10-10T20:52:48 | ---
dataset_info:
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dtype... | 729 | [
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vitaliy-sharandin/synthetic-fraud-detection | 2023-08-24T17:17:37.000Z | [
"region:us"
] | vitaliy-sharandin | null | null | 1 | 432 | 2023-08-24T17:13:00 | Entry not found | 15 | [
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mteb/mind_small | 2022-08-04T23:00:59.000Z | [
"region:us"
] | mteb | null | null | 0 | 431 | 2022-05-30T18:34:30 | The `test` split is the `validation` split of [MIND](https://msnews.github.io/). Labels for the original `test` split are unavailable.
Thus, we renamed it to test for consistency in the MTEB benchmark. | 201 | [
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ashraq/movielens_ratings | 2022-06-29T17:29:31.000Z | [
"region:us"
] | ashraq | null | null | 1 | 430 | 2022-06-24T17:20:41 | Entry not found | 15 | [
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jxie/flickr8k | 2023-06-25T22:25:03.000Z | [
"region:us"
] | jxie | null | null | 0 | 430 | 2023-06-25T19:09:16 | ---
dataset_info:
features:
- name: image
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splits:
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num_bytes: 826721431.0
num_exampl... | 687 | [
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german-nlp-group/german_common_crawl | 2023-10-03T14:50:28.000Z | [
"language:de",
"region:us"
] | german-nlp-group | German Only Extract from Common Crawl
This Dataset is for pretraining a German Language Model (Unsupervised) or tune a Multilingual Model specifically to German | @inproceedings{wenzek2020ccnet,
title={CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data},
author={Wenzek, Guillaume and Lachaux, Marie-Anne and Conneau, Alexis and Chaudhary, Vishrav and Guzm{\'a}n, Francisco and Joulin, Armand and Grave, {\'E}douard},
booktitle={Proceedings of The 12th Lan... | 7 | 429 | 2022-03-02T23:29:22 | ---
language:
- de
---
# Dataset Card for GermanCommonCrawl
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#da... | 4,982 | [
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JasiekKaczmarczyk/maestro-v1-sustain-masked | 2023-10-02T10:34:44.000Z | [
"region:us"
] | JasiekKaczmarczyk | null | null | 0 | 429 | 2023-10-02T08:08:58 | ---
dataset_info:
features:
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- name: source
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- name: pitch
sequence: int16
length: 128
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sequence: float32
length: 128
- name: duration
sequence: float32
length: 128
- name: velocity
sequence: int16
length... | 1,136 | [
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pcuenq/oxford-pets | 2022-08-06T16:01:34.000Z | [
"task_categories:image-classification",
"source_datasets:https://www.robots.ox.ac.uk/~vgg/data/pets/",
"license:cc-by-sa-4.0",
"pets",
"oxford",
"region:us"
] | pcuenq | null | null | 5 | 428 | 2022-08-06T15:59:02 | ---
tags:
- pets
- oxford
license: cc-by-sa-4.0
license_details: https://www.robots.ox.ac.uk/~vgg/data/pets/
pretty_name: Oxford-IIIT Pet Dataset (no annotations)
source_datasets: https://www.robots.ox.ac.uk/~vgg/data/pets/
task_categories:
- image-classification
---
# Oxford-IIIT Pet Dataset
Images from [The Oxford-... | 565 | [
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webis/Touche23-ValueEval | 2023-05-23T20:19:40.000Z | [
"task_categories:text-classification",
"task_categories:zero-shot-classification",
"task_ids:multi-label-classification",
"size_categories:1K<n<10K",
"language:en",
"license:cc-by-4.0",
"Human Values",
"Value Detection",
"Multi-Label",
"region:us"
] | webis | Dataset for Touch\u00E9 / SemEval 2023 Task 4; ValueEval: Identification of Human Values behind Arguments:
https://www.overleaf.com/6679855346wrdckzkdccxg
Based on the original Webis-ArgValues-22 (https://doi.org/10.5281/zenodo.5657249) dataset accompanying the paper
Identifying the Human Values behind Arguments (Kiese... | @Article{mirzakhmedova:2023a,
author = {Nailia Mirzakhmedova and Johannes Kiesel and Milad Alshomary and Maximilian Heinrich and Nicolas Handkeand Xiaoni Cai and Valentin Barriere and Doratossadat Dastgheib and Omid Ghahroodi and {Mohammad Ali} Sadraeiand Ehsaneddin Asgari and Lea Kawaletz and Henning Wachsmuth an... | 3 | 427 | 2023-04-17T09:17:07 | ---
license: cc-by-4.0
task_categories:
- text-classification
- zero-shot-classification
task_ids:
- multi-label-classification
language:
- en
tags:
- Human Values
- Value Detection
- Multi-Label
pretty_name: Human Value Detection Dataset
size_categories:
- 1K<n<10K
---
# The Touché23-ValueEval D... | 12,059 | [
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multi_re_qa | 2023-06-01T14:59:53.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"task_ids:open-domain-qa",
"annotations_creators:expert-generated",
"annotations_creators:found",
"language_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"size_categ... | null | MultiReQA contains the sentence boundary annotation from eight publicly available QA datasets including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, BioASQ, RelationExtraction, and TextbookQA. Five of these datasets, including SearchQA, TriviaQA, HotpotQA, NaturalQuestions, SQuAD, contain both training and te... | @misc{m2020multireqa,
title={MultiReQA: A Cross-Domain Evaluation for Retrieval Question Answering Models},
author={Mandy Guo and Yinfei Yang and Daniel Cer and Qinlan Shen and Noah Constant},
year={2020},
eprint={2005.02507},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 0 | 425 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
- found
language_creators:
- expert-generated
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
- 10K<n<100K
- 1K<n<10K
- 1M<n<10M
source_datasets:
- extended|other-BioASQ
- extended|other-DuoRC
- extended|other-HotpotQA
- ... | 9,327 | [
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