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 |
|---|---|---|---|---|---|---|---|---|---|
Ryukijano/eurosat | 2023-07-19T12:23:14.000Z | [
"region:us"
] | Ryukijano | null | null | null | 0 | 88 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
dtype:
class_label:
names:
'0': AnnualCrop
'1': Forest
'2': HerbaceousVegetation
'3': Highway
'4': Industrial
'5': Pasture
'6': PermanentCrop
'... |
codefuse-ai/Evol-instruction-66k | 2023-09-10T02:45:52.000Z | [
"license:cc-by-nc-sa-4.0",
"region:us"
] | codefuse-ai | null | null | null | 45 | 88 | ---
license: cc-by-nc-sa-4.0
viewer: false
---
# Dataset Card for CodeFuse-Evol-instruction-66k
<div align='center'>
[[中文]](#chinese) [[English]](#english)
</div>
<a id="english"></a>
## Dataset Description
Evol-instruction-66k data is based on the method mentioned in the paper "WizardCode... |
euclaise/stage1 | 2023-09-26T17:49:46.000Z | [
"license:cc-by-sa-4.0",
"region:us"
] | euclaise | null | null | null | 0 | 88 | ---
license: cc-by-sa-4.0
dataset_info:
features:
- name: source
dtype: string
- name: prompt
dtype: string
- name: completion
dtype: string
splits:
- name: train
num_bytes: 827191765.0
num_examples: 49017
download_size: 477329322
dataset_size: 827191765.0
configs:
- config_name: def... |
lchakkei/OpenOrca-Traditional-Chinese | 2023-10-10T15:37:20.000Z | [
"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... | lchakkei | null | null | null | 1 | 88 | ---
language:
- zh
license: mit
size_categories:
- 10M<n<100M
task_categories:
- conversational
- text-classification
- token-classification
- table-question-answering
- question-answering
- zero-shot-classification
- summarization
- feature-extraction
- text-generation
- text2text-generation
pretty_name: OpenOrca-Chin... |
boardsec/yara_dataset_v4 | 2023-09-17T01:52:10.000Z | [
"region:us"
] | boardsec | null | null | null | 0 | 88 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: Chunk
dtype: string
- name: yara_rule
dtype: string
- name: cleaned_yara_rule
dtype: string
splits:
- name: train
num_bytes: 36039
num_examples: 67
download_size: 1... |
qgyd2021/cppe-5 | 2023-09-28T08:30:29.000Z | [
"task_categories:object-detection",
"size_categories:100M<n<1B",
"license:apache-2.0",
"object detection",
"region:us"
] | qgyd2021 | CPPE - 5 (Medical Personal Protective Equipment) is a new challenging dataset with the goal
to allow the study of subordinate categorization of medical personal protective equipments,
which is not possible with other popular data sets that focus on broad level categories. | @misc{dagli2021cppe5,
title={CPPE-5: Medical Personal Protective Equipment Dataset},
author={Rishit Dagli and Ali Mustufa Shaikh},
year={2021},
eprint={2112.09569},
archivePrefix={arXiv},
primaryClass={cs.CV}
} | null | 0 | 88 | ---
license: apache-2.0
task_categories:
- object-detection
tags:
- object detection
size_categories:
- 100M<n<1B
---
## cppe-5
我正在 transformers 上练习 [object-detection](https://huggingface.co/docs/transformers/tasks/object_detection)
我在 Kaggle 上执行代码，因为那上面提供免费的GPU, 可是它访问不到 google drive，因此我复制了这个数据集[cppe-5](https://huggi... |
sehyun66/Finnhub-News | 2023-10-02T16:51:29.000Z | [
"finance",
"region:us"
] | sehyun66 | null | null | null | 2 | 88 | ---
dataset_info:
- config_name: clean
features:
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dtype: int64
- name: image
dtype: string
- name: related
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- name: source
dtype: string
- name: summary
dtype: string
- name: url
dtype: string
- name: id
dtype: int64
- name: category
dtype: ... |
Nicolas-BZRD/DOLE_opendata | 2023-09-29T14:52:42.000Z | [
"size_categories:1K<n<10K",
"language:fr",
"license:odc-by",
"legal",
"region:us"
] | Nicolas-BZRD | null | null | null | 0 | 88 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: id
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 86993000
num_examples: 4120
download_size: 36263044
dataset_size: 86993000
license: odc-by
... |
kewu93/pixel_500 | 2023-10-06T09:31:47.000Z | [
"region:us"
] | kewu93 | null | null | null | 0 | 88 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
splits:
- name: train
num_bytes: 5863021.833333333
num_examples: 500
- name: val
num... |
vishnupriyavr/wiki-movie-plots-with-summaries-faiss-embeddings | 2023-10-08T16:02:50.000Z | [
"region:us"
] | vishnupriyavr | null | null | null | 0 | 88 | ---
dataset_info:
features:
- name: Release Year
dtype: int64
- name: Title
dtype: string
- name: Cast
dtype: string
- name: Wiki Page
dtype: string
- name: Plot
dtype: string
- name: plot_length
dtype: int64
- name: text
dtype: string
- name: embeddings
sequence: float... |
SetFit/amazon_reviews_multi_en | 2022-04-13T19:06:11.000Z | [
"license:apache-2.0",
"region:us"
] | SetFit | null | null | null | 1 | 87 | ---
license: apache-2.0
---
|
generalization/newsgroups_Full-p_1 | 2022-09-09T05:18:22.000Z | [
"region:us"
] | generalization | null | null | null | 0 | 87 | Entry not found |
beki/privy | 2023-04-25T21:45:06.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:monolingual",
"size_categories:100K<n<200K",
"size_categories:300K<n<400K",
"language:en",
"license:mit",
"pii-detection",
"region:us"
] | beki | null | null | null | 8 | 87 | ---
language:
- en
license:
- mit
multilinguality:
- monolingual
size_categories:
- 100K<n<200K
- 300K<n<400K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
tags:
- pii-detection
train-eval-index:
- config: privy-small
task: token-classification
task_id: entity_extraction
splits:
... |
lewtun/music_genres | 2022-11-02T10:27:30.000Z | [
"region:us"
] | lewtun | null | null | null | 0 | 87 | ---
dataset_info:
features:
- name: audio
dtype: audio
- name: song_id
dtype: int64
- name: genre_id
dtype: int64
- name: genre
dtype: string
splits:
- name: test
num_bytes: 1978321742.996
num_examples: 5076
- name: train
num_bytes: 7844298868.902
num_examples: 19909
do... |
taesiri/imagenet-hard | 2023-06-16T18:50:51.000Z | [
"task_categories:image-classification",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"OOD",
"ImageNet",
"Out Of Distribution",
"arxiv:2304.05538",
"region:us"
] | taesiri | null | null | null | 7 | 87 | ---
dataset_info:
features:
- name: image
dtype: image
- name: label
sequence: int64
- name: origin
dtype: string
- name: english_label
sequence: string
splits:
- name: validation
num_bytes: 1771418938.94
num_examples: 10980
download_size: 6380094503
dataset_size: 1771418938.94... |
tiedong/goat | 2023-05-25T22:14:53.000Z | [
"task_categories:question-answering",
"size_categories:1M<n<10M",
"language:en",
"license:apache-2.0",
"region:us"
] | tiedong | null | null | null | 16 | 87 | ---
license: apache-2.0
task_categories:
- question-answering
language:
- en
size_categories:
- 1M<n<10M
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- **Point of Contact:**
### Dataset Summary
The dataset.json file contains ~1.7 m... |
factored/fr-crawler-private-mlm | 2023-08-18T21:00:58.000Z | [
"region:us"
] | factored | null | null | null | 0 | 87 | ---
dataset_info:
features:
- name: text
dtype: string
- name: labels
dtype:
class_label:
names:
'0': Data Engineer
'1': Data Analyst
'2': Data Scientist
'3': Machine Learning Engineer
'4': Software Engineer
'5': Analytics Engineer
... |
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 | null | 17 | 87 | ---
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... |
abacusai/LongChat-Lines | 2023-07-28T03:14:01.000Z | [
"region:us"
] | abacusai | null | null | null | 9 | 87 | ---
configs:
- config_name: default
data_files:
- split: '100'
path: data/100-*
- split: '150'
path: data/150-*
- split: '175'
path: data/175-*
- split: '200'
path: data/200-*
- split: '250'
path: data/250-*
- split: '300'
path: data/300-*
- split: '400'
path: data/400-*
- ... |
C-MTEB/AFQMC | 2023-07-28T13:39:01.000Z | [
"region:us"
] | C-MTEB | null | null | null | 0 | 87 | ---
configs:
- config_name: default
data_files:
- split: test
path: data/test-*
- split: train
path: data/train-*
- split: validation
path: data/validation-*
dataset_info:
features:
- name: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype:
class_l... |
pankajmathur/lima_unchained_v1 | 2023-08-25T22:18:57.000Z | [
"region:us"
] | pankajmathur | null | null | null | 1 | 87 | An attempt to unchained Llama2 by using only 780 filtered dataset from [GAIR/lima](https://huggingface.co/datasets/GAIR/lima). |
heegyu/aulm-0809 | 2023-08-22T03:33:28.000Z | [
"region:us"
] | heegyu | null | null | null | 2 | 87 | ---
dataset_info:
features:
- name: conversations
list:
- name: from
dtype: string
- name: value
dtype: string
splits:
- name: train
num_bytes: 704591219
num_examples: 171404
download_size: 311285345
dataset_size: 704591219
---
공개 한국어 Instruction 데이터를 포멧을 통일하고 병합한 데이터
| Dat... |
yzhuang/autotree_automl_100000_electricity_sgosdt_l256_dim7_d3_sd0 | 2023-09-07T21:52:00.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 87 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
kewu93/three_styles_prompted_250_512x512 | 2023-09-21T23:53:43.000Z | [
"region:us"
] | kewu93 | null | null | null | 0 | 87 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: val
path: data/val-*
dataset_info:
features:
- name: image
dtype: image
- name: text
dtype: string
- name: style_class
dtype: string
splits:
- name: train
num_bytes: 17235209.8
num_ex... |
kili-technology/plastic_in_river | 2022-10-21T07:13:58.000Z | [
"task_categories:object-detection",
"size_categories:1K<n<10K",
"source_datasets:original",
"other-object-detection",
"region:us"
] | kili-technology | This dataset contains photos of rivers on which there may be waste. The waste items are annotated
through bounding boxes, and are assigned to one of the 4 following categories: plastic bottle, plastic bag,
another plastic waste, or non-plastic waste. Note that some photos may not contain any waste. | null | null | 13 | 86 | ---
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- object-detection
task_ids: []
pretty_name: Plastic in river
tags:
- other-object-detection
---
# Plastic in river
This dataset is an export of the annotated assets from the [Kili's Community Challenge - Plastic in River dataset](https://kili... |
albertxu/CrosswordQA | 2022-10-29T23:45:36.000Z | [
"task_categories:question-answering",
"task_ids:open-domain-qa",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"language:en",
"license:unknown",
"region:us"
] | albertxu | null | null | null | 3 | 86 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
task_categories:
- question-answering
task_ids:
- open-domain-qa
---
# Dataset Card for CrosswordQA
## Table of Contents
- [Dataset Description](#dataset-de... |
roszcz/internship-midi-data-science | 2023-02-28T07:34:05.000Z | [
"region:us"
] | roszcz | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: notes
struct:
- name: end
sequence: float64
- name: pitch
sequence: int64
- name: start
sequence: float64
- name: velocity
sequence: int64
- name: control_changes
struct:
- name: number
sequence: int64
- name: time
... |
Arabic-Clip/ImageCaptions-7M-Translations-Arabic | 2023-07-17T09:13:49.000Z | [
"region:us"
] | Arabic-Clip | null | null | null | 0 | 86 | Entry not found |
Arjun-G-Ravi/Python-codes | 2023-08-12T07:43:19.000Z | [
"task_categories:text-generation",
"task_categories:text2text-generation",
"size_categories:10K<n<100K",
"language:en",
"license:mit",
"code",
"region:us"
] | Arjun-G-Ravi | null | null | null | 2 | 86 | ---
license: mit
task_categories:
- text-generation
- text2text-generation
language:
- en
tags:
- code
pretty_name: Python codes dataset
size_categories:
- 10K<n<100K
---
# Dataset Card for Dataset Name
Please note that this dataset maynot be perfect and may contain a very small quantity of non python codes. But the q... |
yzhuang/autotree_pmlb_100000_banana_sgosdt_l256_dim10_d3_sd0 | 2023-09-07T17:16:23.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_pmlb_100000_clean2_sgosdt_l256_dim10_d3_sd0 | 2023-09-08T01:58:08.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_automl_100000_california_sgosdt_l256_dim8_d3_sd0 | 2023-09-08T03:18:22.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_pmlb_100000_Hill_Valley_with_noise_sgosdt_l256_dim10_d3_sd0 | 2023-09-08T06:27:42.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_pmlb_100000_Hill_Valley_without_noise_sgosdt_l256_dim10_d3_sd0 | 2023-09-08T06:58:08.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_pmlb_100000_magic_sgosdt_l256_dim10_d3_sd0 | 2023-09-08T16:34:51.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
yzhuang/autotree_pmlb_100000_twonorm_sgosdt_l256_dim10_d3_sd0 | 2023-09-08T17:38:59.000Z | [
"region:us"
] | yzhuang | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: input_x
sequence:
sequence: float32
- name: input_y
sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
- name: status
sequence:
sequence: flo... |
hakanssonjesper/dataset-llama | 2023-10-01T16:39:18.000Z | [
"region:us"
] | hakanssonjesper | null | null | null | 0 | 86 | ---
dataset_info:
features:
- name: instruction
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 65284594.45526487
num_examples: 45592
- name: validation
num_bytes: 16322580.544735134
num_examples: 11399
download_size: 38476271
dataset_size: 81607175.0
... |
cornell_movie_dialog | 2023-04-05T10:02:37.000Z | [
"language:en",
"region:us"
] | null | This corpus contains a large metadata-rich collection of fictional conversations extracted from raw movie scripts:
- 220,579 conversational exchanges between 10,292 pairs of movie characters
- involves 9,035 characters from 617 movies
- in total 304,713 utterances
- movie metadata included:
- genres
- release y... | @InProceedings{Danescu-Niculescu-Mizil+Lee:11a,
author={Cristian Danescu-Niculescu-Mizil and Lillian Lee},
title={Chameleons in imagined conversations:
A new approach to understanding coordination of linguistic style in dialogs.},
booktitle={Proceedings of the
Workshop on Cognitive Modeling and Co... | null | 11 | 85 | ---
language:
- en
paperswithcode_id: cornell-movie-dialogs-corpus
pretty_name: Cornell Movie-Dialogs Corpus
dataset_info:
features:
- name: movieID
dtype: string
- name: movieTitle
dtype: string
- name: movieYear
dtype: string
- name: movieIMDBRating
dtype: string
- name: movieNoIMDBVotes
... |
un_multi | 2023-06-01T14:59:54.000Z | [
"task_categories:translation",
"annotations_creators:found",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"language:ar",
"language:de",
"language:en",
"language:es",
"language:fr",
"language:ru",
"language:zh",
"license... | null | This is a collection of translated documents from the United Nations. This corpus is available in all 6 official languages of the UN, consisting of around 300 million words per language | @inproceedings{eisele-chen-2010-multiun,
title = "{M}ulti{UN}: A Multilingual Corpus from United Nation Documents",
author = "Eisele, Andreas and
Chen, Yu",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = ... | null | 2 | 85 | ---
annotations_creators:
- found
language_creators:
- found
language:
- ar
- de
- en
- es
- fr
- ru
- zh
license:
- unknown
multilinguality:
- multilingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: multiun
pretty_name: Multilingual Corpus fr... |
SetFit/go_emotions | 2022-09-08T15:41:33.000Z | [
"region:us"
] | SetFit | null | null | null | 4 | 85 | # GoEmotions
This dataset is a port of the official [`go_emotions` dataset](https://huggingface.co/datasets/go_emotions) on the Hub. It only contains the `simplified` subset as these are the only fields we need for text classification. |
laion/laion-coco | 2022-10-23T18:55:09.000Z | [
"license:cc-by-4.0",
"region:us"
] | laion | null | null | null | 38 | 85 | ---
license: cc-by-4.0
---
# LAION COCO: 600M SYNTHETIC CAPTIONS FROM LAION2B-EN
by: Christoph Schuhmann, Andreas Köpf, Richard Vencu, Theo Coombes, Romain Beaumont, 10 Oct, 2022
Author: Christoph Schuhmann, Andreas Köpf , Theo Coombes, Richard Vencu, Benjamin Trom , Romain Beaumont
We present LAION-COCO, the world’s... |
LLukas22/NLQuAD | 2022-12-23T13:04:58.000Z | [
"task_ids:extractive-qa",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:cc-by-3.0",
"region:us"
] | LLukas22 | null | null | null | 1 | 85 | ---
pretty_name: NLQuAD
language:
- en
license:
- cc-by-3.0
size_categories:
- 10K<n<100K
multilinguality:
- monolingual
task_ids:
- extractive-qa
dataset_info:
features:
- name: title
dtype: string
- name: date
dtype: string
- name: paragraphs
list:
- name: context
dtype: string
- nam... |
ai4bharat/naamapadam | 2023-05-24T17:09:03.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"multilinguality:multilingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:as",
"language:bn",
"language:gu",
"lang... | ai4bharat | \ | \ | null | 2 | 85 | ---
annotations_creators:
- machine-generated
language_creators:
- machine-generated
language:
- as
- bn
- gu
- hi
- kn
- ml
- mr
- or
- pa
- ta
- te
license:
- cc0-1.0
multilinguality:
- multilingual
pretty_name: naamapadam
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- token-classification... |
changpt/ko-lima-vicuna | 2023-06-14T07:47:51.000Z | [
"task_categories:text-generation",
"size_categories:n<1K",
"language:ko",
"license:cc-by-2.0",
"KoLima",
"region:us"
] | changpt | null | null | null | 16 | 85 | ---
license: cc-by-2.0
task_categories:
- text-generation
language:
- ko
size_categories:
- n<1K
pretty_name: KoLima(vicuna)
tags:
- KoLima
---
# Ko Lima Vicuna Dataset
GPT4 API를 사용하여 [lima_vicuna_format 데이터](https://huggingface.co/datasets/64bits/lima_vicuna_format)를 한국어로 재생성한 데이터셋입니다.
GPT4 사용시 프롬프트는 "단순 번역이 아닌, 원... |
sharmaarushi17/HPCPerfOpt-MCQA | 2023-09-22T05:30:21.000Z | [
"license:cc",
"region:us"
] | sharmaarushi17 | null | null | null | 0 | 85 | ---
license: cc
pretty_name: HPCPerfOpt (HPC Performance Optimization Benchmark) # Example: SQuAD
# configs:
# - mcq-single
# - mcq-multiple
# - rodinia-chatgpt-mcq
# dataset_info:
# # features:
# # - name: {feature_name_0} # Example: id
# # dtype: {feature_dtype_0} # Example: int32
# #... |
izumi-lab/wikipedia-ja-20230720 | 2023-07-29T03:05:36.000Z | [
"language:ja",
"license:cc-by-sa-3.0",
"region:us"
] | izumi-lab | null | null | null | 2 | 85 | ---
dataset_info:
features:
- name: curid
dtype: string
- name: title
dtype: string
- name: text
dtype: string
splits:
- name: train
num_bytes: 3653518687
num_examples: 1362415
download_size: 2130533065
dataset_size: 3653518687
license: cc-by-sa-3.0
language:
- ja
---
# Dataset Card ... |
vlsp-2023-vllm/grade_12_exams | 2023-09-30T08:28:29.000Z | [
"region:us"
] | vlsp-2023-vllm | null | null | null | 0 | 85 | ---
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: metadata
struct:
- name: grade
dtype: int64
- name: language
dtype: string
- name: subject
dtype: string
- name: choices
struct:
- name: label
sequence: string
... |
serbog/all_job_listings_cleaned | 2023-09-14T23:53:19.000Z | [
"region:us"
] | serbog | null | null | null | 0 | 85 | ---
dataset_info:
features:
- name: job_id
dtype: string
- name: description
dtype: string
- name: title
dtype: string
- name: creationdate
dtype: int64
- name: name
dtype: string
- name: location_codes
sequence: string
splits:
- name: train
num_bytes: 2991442359
num_ex... |
tim9510019/llama2_QA_Economics_230915 | 2023-10-10T01:30:51.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:mit",
"finance",
"region:us"
] | tim9510019 | null | null | null | 2 | 85 | ---
dataset_info:
features:
- name: Question
dtype: string
- name: input
dtype: string
- name: Answer
dtype: string
- name: Source
dtype: int64
- name: Date
dtype: timestamp[ns]
- name: Type
dtype: int64
- name: Prompt
dtype: int64
- name: QuestionTokenNum
dtype: int64
... |
jimregan/clarinpl_sejmsenat | 2023-01-22T13:37:24.000Z | [
"task_categories:other",
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:other",
"region:us"
] | jimregan | A collection of 97 hours of parliamentary speeches published on the ClarinPL website
Note that in order to limit the required storage for preparing this dataset, the audio
is stored in the .wav format and is not converted to a float32 array. To convert the audio
file to a float32 array, please make use of the `.map()`... | @article{marasek2014system,
title={System for automatic transcription of sessions of the {P}olish {S}enate},
author={Marasek, Krzysztof and Kor{\v{z}}inek, Danijel and Brocki, {\L}ukasz},
journal={Archives of Acoustics},
volume={39},
number={4},
pages={501--509},
year={2014}
} | null | 1 | 84 | ---
annotations_creators:
- expert-generated
language:
- pl
license:
- other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
- automatic-speech-recognition
task_ids: []
---
# Dataset Card for ClarinPL Sejm/Senat Speech Corpus
## Table of Contents
- [Data... |
asapp/slue | 2022-09-26T23:08:10.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"task_categories:text-classification",
"task_categories:token-classification",
"task_ids:sentiment-analysis",
"task_ids:named-entity-recognition",
"annotations_creators:expert-generated",
"language_creators:found",... | asapp | Spoken Language Understanding Evaluation (SLUE) benchmark. There are two subsets: (i) SLUE-VoxPopuli which has ASR and NER tasks and (ii) SLUE-VoxCeleb which has ASR and SA tasks. | @inproceedings{shon2022slue,
title={Slue: New benchmark tasks for spoken language understanding evaluation on natural speech},
author={Shon, Suwon and Pasad, Ankita and Wu, Felix and Brusco, Pablo and Artzi, Yoav and Livescu, Karen and Han, Kyu J},
booktitle={ICASSP 2022-2022 IEEE International Conference on Acou... | null | 3 | 84 | ---
annotations_creators:
- expert-generated
language:
- en
language_creators:
- found
license:
- cc0-1.0
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: slue
pretty_name: SLUE (Spoken Language Understanding Evaluation benchmark)
size_categories:
- 10K<n<100K
source_datasets:
- original
tags: []
task_cate... |
bond005/sberdevices_golos_100h_farfield | 2022-10-27T04:23:04.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:10K<n<100k",
"source_datasets:extended",
"language:... | bond005 | null | null | null | 0 | 84 | ---
pretty_name: Golos
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- ru
license:
- other
multilinguality:
- monolingual
paperswithcode_id: golos
size_categories:
- 10K<n<100k
source_datasets:
- extended
task_categories:
- automatic-speech-recognition
- audio-c... |
fahamu/ioi | 2022-11-28T03:58:50.000Z | [
"license:mit",
"doi:10.57967/hf/0142",
"region:us"
] | fahamu | null | null | null | 2 | 84 | ---
license: mit
---
# Dataset Release: Indirect Object Identification
`mecha_ioi` is a pair of datasets tailored for the Indirect Object Identification task, where sentences are generated from the following set of templates:
- BABA
```
baba_templates = [
"Then, {B} and {A} went to the {PLACE}. {B} gave a {OBJEC... |
cjvt/sloleks | 2022-12-21T14:42:09.000Z | [
"license:cc-by-sa-4.0",
"region:us"
] | cjvt | Sloleks is a reference morphological lexicon of Slovene that was developed to be used in various NLP applications and language manuals. \
It contains Slovene lemmas, their inflected or derivative word forms and the corresponding grammatical description. In addition to the approx. 100,000 entries already available in S... | @misc{sloleks3,
title = {Morphological lexicon Sloleks 3.0},
author = {{\v C}ibej, Jaka and Gantar, Kaja and Dobrovoljc, Kaja and Krek, Simon and Holozan, Peter and Erjavec, Toma{\v z} and Romih, Miro and Arhar Holdt, {\v S}pela and Krsnik, Luka and Robnik-{\v S}ikonja, Marko},
url = {http://hdl.handle.net/... | null | 0 | 84 | ---
license: cc-by-sa-4.0
---
# Dataset Card for Sloleks 3
**Important**: this is a minimal script for processing Sloleks 3. Most notably, some word form properties (accentuation, pronounciation) and frequencies are not exposed here.
Please see the [CLARIN repository](https://www.clarin.si/repository/xmlui/handle/11... |
tasksource/babi_nli | 2023-06-05T09:05:59.000Z | [
"task_categories:text-classification",
"task_ids:natural-language-inference",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:bsd",
"logical reasoning",
"nli"... | tasksource | bAbi tasks recasted as natural language inference. | null | null | 1 | 84 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
license: bsd
multilinguality:
- monolingual
pretty_name: babi_nli
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- natural-language-inference
tags:
- logical reasoning
... |
Aeala/ShareGPT_Vicuna_unfiltered | 2023-06-01T07:03:50.000Z | [
"language:en",
"license:apache-2.0",
"region:us"
] | Aeala | null | null | null | 10 | 84 | ---
license: apache-2.0
language:
- en
---
## Dataset Card
This is a reupload of [this dataset](https://huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered) that was further cleaned by gozfarb. |
C-MTEB/STSB | 2023-07-28T13:40:47.000Z | [
"region:us"
] | C-MTEB | null | null | null | 0 | 84 | ---
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: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: int32
split... |
lavita/ChatDoctor-HealthCareMagic-100k | 2023-09-09T07:40:38.000Z | [
"region:us"
] | lavita | null | null | null | 0 | 84 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
dataset_info:
features:
- name: instruction
dtype: string
- name: input
dtype: string
- name: output
dtype: string
splits:
- name: train
num_bytes: 126454896
num_examples: 112165
download_size: 70... |
LabHC/moji | 2023-09-28T09:12:22.000Z | [
"task_categories:text-classification",
"language:en",
"region:us"
] | LabHC | null | null | null | 0 | 84 | ---
task_categories:
- text-classification
language:
- en
dataset_info:
features:
- name: text
dtype: string
- name: label
dtype: int64
- name: sa
dtype: int64
splits:
- name: train
num_bytes: 128596235
num_examples: 1613790
- name: test
num_bytes: 35731728
num_examples: 448276... |
phongmt184172/python_data_27k | 2023-10-05T02:30:02.000Z | [
"region:us"
] | phongmt184172 | null | null | null | 0 | 84 | ---
dataset_info:
features:
- name: id
dtype: int64
- name: text
dtype: string
- name: label
dtype: string
splits:
- name: train
num_bytes: 39244063.17425801
num_examples: 19056
- name: test
num_bytes: 8410618.912870996
num_examples: 4084
- name: val
num_bytes: 8410618.91... |
dmrau/trec_dl20 | 2023-10-09T08:28:56.000Z | [
"license:unknown",
"region:us"
] | dmrau | null | null | null | 0 | 84 | ---
license: unknown
configs:
- config_name: default
data_files:
- split: queries
path: data/queries-*
- split: corpus
path: data/corpus-*
dataset_info:
features:
- name: _id
dtype: string
- name: text
dtype: string
- name: title
dtype: string
splits:
- name: queries
num_bytes:... |
deepset/germandpr | 2023-04-06T13:59:37.000Z | [
"task_categories:question-answering",
"task_categories:text-retrieval",
"task_ids:extractive-qa",
"task_ids:closed-domain-qa",
"multilinguality:monolingual",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"arxiv:2104.12741",
"region:us"
] | deepset | We take GermanQuAD as a starting point and add hard negatives from a dump of the full German Wikipedia following the approach of the DPR authors (Karpukhin et al., 2020). The format of the dataset also resembles the one of DPR. GermanDPR comprises 9275 question/answer pairs in the training set and 1025 pairs in the tes... | @misc{möller2021germanquad,
title={GermanQuAD and GermanDPR: Improving Non-English Question Answering and Passage Retrieval},
author={Timo Möller and Julian Risch and Malte Pietsch},
year={2021},
eprint={2104.12741},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | null | 7 | 83 | ---
language:
- de
multilinguality:
- monolingual
source_datasets:
- original
task_categories:
- question-answering
- text-retrieval
task_ids:
- extractive-qa
- closed-domain-qa
thumbnail: >-
https://thumb.tildacdn.com/tild3433-3637-4830-a533-353833613061/-/resize/720x/-/format/webp/germanquad.jpg
license: cc-by-4.0
... |
philschmid/germeval18 | 2022-02-28T17:14:55.000Z | [
"region:us"
] | philschmid | null | null | null | 2 | 83 | Entry not found |
pmc/open_access | 2023-03-14T17:29:59.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:en",
"license:cc0-1.0",
"license:cc-by-4.0",
"license:cc-b... | pmc | The PMC Open Access Subset includes more than 3.4 million journal articles and preprints that are made available under
license terms that allow reuse.
Not all articles in PMC are available for text mining and other reuse, many have copyright protection, however articles
in the PMC Open Access Subset are made availabl... | PMC Open Access Subset [Internet]. Bethesda (MD): National Library of Medicine. 2003 - [cited YEAR MONTH DAY]. Available from https://www.ncbi.nlm.nih.gov/pmc/tools/openftlist/ | null | 11 | 83 | ---
annotations_creators:
- no-annotation
language_creators:
- expert-generated
language:
- en
license:
- cc0-1.0
- cc-by-4.0
- cc-by-sa-4.0
- cc-by-nd-4.0
- cc-by-nc-4.0
- cc-by-nc-sa-4.0
- cc-by-nc-nd-4.0
- other
- unknown
multilinguality:
- monolingual
size_categories:
- 1M<n<10M
source_datasets:
- original
task_cat... |
facebook/pmd | 2022-08-09T23:51:39.000Z | [
"task_categories:image-to-text",
"task_ids:image-captioning",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"arxiv:2112.04482",
"arxiv:2111.11431",
"region:us... | facebook | Introduced in FLAVA paper, Public Multimodal Dataset (PMD) is a collection of publicly-available image-text pairs datasets. PMD in total contains 70M image-text pairs with 68M unique images. The dataset contains pairs from Conceptual Captions, Conceptual Captions 12M, WIT, Localized Narratives, RedCaps, COCO, SBU Capti... | @inproceedings{singh2022flava,
title={Flava: A foundational language and vision alignment model},
author={Singh, Amanpreet and Hu, Ronghang and Goswami, Vedanuj and Couairon, Guillaume and Galuba, Wojciech and Rohrbach, Marcus and Kiela, Douwe},
booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision... | null | 26 | 83 | ---
annotations_creators:
- found
language_creators:
- found
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- image-to-text
task_ids:
- image-captioning
paperswithcode_id: pmd
pretty_name: PMD
extra_gated_prompt: |
By click... |
Hello-SimpleAI/HC3-Chinese | 2023-01-21T13:11:49.000Z | [
"task_categories:text-classification",
"task_categories:question-answering",
"task_categories:sentence-similarity",
"task_categories:zero-shot-classification",
"size_categories:10K<n<100K",
"language:en",
"language:zh",
"license:cc-by-sa-4.0",
"ChatGPT",
"SimpleAI",
"Detection",
"OOD",
"arxi... | Hello-SimpleAI | Human ChatGPT Comparison Corpus (HC3) Chinese Version | \ | null | 101 | 83 | ---
task_categories:
- text-classification
- question-answering
- sentence-similarity
- zero-shot-classification
language:
- en
- zh
tags:
- ChatGPT
- SimpleAI
- Detection
- OOD
size_categories:
- 10K<n<100K
license: cc-by-sa-4.0
---
# Human ChatGPT Comparison Corpus (HC3)
We propose the first human-ChatGPT compariso... |
IlyaGusev/librusec | 2023-03-20T16:03:43.000Z | [
"task_categories:text-generation",
"size_categories:100K<n<1M",
"language:ru",
"region:us"
] | IlyaGusev | null | null | null | 4 | 83 | ---
dataset_info:
features:
- name: id
dtype: uint64
- name: text
dtype: string
splits:
- name: train
num_bytes: 125126513109
num_examples: 223256
download_size: 34905399148
dataset_size: 125126513109
task_categories:
- text-generation
language:
- ru
size_categories:
- 100K<n<1M
---
# Lib... |
sanagnos/processed_gpt_dataset_big | 2023-04-06T20:05:27.000Z | [
"region:us"
] | sanagnos | null | null | null | 0 | 83 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: special_tokens_mask
sequence: int8
splits:
- name: train
num_bytes: 23584245444.0
num_examples: 3831099
download_size: 6899066299
dataset_size: 23584245444.0
---
# Dataset Card... |
enesxgrahovac/the-feynman-lectures-on-physics | 2023-04-07T20:56:25.000Z | [
"region:us"
] | enesxgrahovac | null | null | null | 3 | 83 | ---
dataset_info:
features:
- name: book_volume
dtype: string
- name: book_title
dtype: string
- name: chapter_number
dtype: string
- name: chapter_title
dtype: string
- name: section_number
dtype: string
- name: section_title
dtype: string
- name: section_text
dtype: string
... |
heegyu/OIG-small-chip2-ko | 2023-04-19T13:25:41.000Z | [
"size_categories:100K<n<1M",
"language:ko",
"language:en",
"license:apache-2.0",
"region:us"
] | heegyu | null | null | null | 7 | 83 | ---
license: apache-2.0
language:
- ko
- en
size_categories:
- 100K<n<1M
---
# Dataset Card for "OIG-small-chip2-ko"
- 210282 items
- Original Dataset: OIG-small-chip2 dataset from https://laion.ai/blog/oig-dataset/
- Translated by Google Translate API
example
```
{
"user": "Is there a good way to clean up my credit ... |
Sp1786/multiclass-sentiment-analysis-dataset | 2023-06-25T08:01:27.000Z | [
"task_categories:text-classification",
"task_categories:translation",
"size_categories:10K<n<100K",
"language:en",
"license:apache-2.0",
"code",
"region:us"
] | Sp1786 | null | null | null | 0 | 83 | ---
license: apache-2.0
task_categories:
- text-classification
- translation
language:
- en
tags:
- code
pretty_name: multiclass-sentiment-analysis-dataset
size_categories:
- 10K<n<100K
---
# Dataset Card for Dataset Name
## Dataset Description
- **Homepage:**
- **Repository:**
- **Paper:**
- **Leaderboard:**
- *... |
Dewa/Dog_Emotion_Dataset_v2 | 2023-07-28T18:47:48.000Z | [
"task_categories:image-classification",
"size_categories:1K<n<10K",
"license:creativeml-openrail-m",
"region:us"
] | Dewa | null | null | null | 1 | 83 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: label
dtype: int64
- name: emotion
dtype: string
- name: image
dtype: image
splits:
- name: train
num_bytes: 128018890.4
num_exa... |
adalbertojunior/ICD_dataset | 2023-09-13T21:59:45.000Z | [
"region:us"
] | adalbertojunior | null | null | null | 0 | 83 | ---
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: text
dtype: string
- name: label
sequence: string
splits:
- name: train
num_bytes: 41841... |
tyzhu/eval_tag_squad_v0 | 2023-09-21T15:52:30.000Z | [
"region:us"
] | tyzhu | null | null | null | 0 | 83 | ---
dataset_info:
features:
- name: id
dtype: string
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
- name: inputs
dtype: string
- ... |
LeStoe11/geeks4geeks_fixed | 2023-09-27T18:21:59.000Z | [
"region:us"
] | LeStoe11 | null | null | null | 0 | 83 | Entry not found |
chirunder/tictactoe_images | 2023-09-27T16:13:15.000Z | [
"region:us"
] | chirunder | null | null | null | 0 | 83 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: image
dtype: image
- name: winner
dtype: string
- name: is_valid
dtype: bool
- name: text
dtype: string
splits:
- name: train
... |
veezbo/akkadian_english_corpus | 2023-09-30T21:32:28.000Z | [
"task_categories:text-generation",
"size_categories:1K<n<10K",
"language:en",
"license:mit",
"region:us"
] | veezbo | null | null | null | 1 | 83 | ---
license: mit
task_categories:
- text-generation
language:
- en
pretty_name: English-translated Akkadian Corpus
size_categories:
- 1K<n<10K
---
# Akkadian English Corpus
This dataset is a cleaned English-translated Akkadian language dataset. This dataset can and has been used for text generation tasks, for example ... |
kor_hate | 2023-01-25T14:33:47.000Z | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ko",
"license:cc-b... | null | Human-annotated Korean corpus collected from a popular domestic entertainment news aggregation platform
for toxic speech detection. Comments are annotated for gender bias, social bias and hate speech. | @inproceedings{moon-etal-2020-beep,
title = "{BEEP}! {K}orean Corpus of Online News Comments for Toxic Speech Detection",
author = "Moon, Jihyung and
Cho, Won Ik and
Lee, Junbum",
booktitle = "Proceedings of the Eighth International Workshop on Natural Language Processing for Social Media",
... | null | 3 | 82 | ---
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- found
language:
- ko
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classification
paperswithcode_id: korean-hat... |
AI-Sweden/SuperLim | 2022-10-21T15:25:24.000Z | [
"task_categories:question-answering",
"task_categories:text-classification",
"task_categories:other",
"multilinguality:monolingual",
"language:sv",
"region:us"
] | AI-Sweden | \ | \ | null | 2 | 82 | ---
language:
- sv
multilinguality:
- monolingual
pretty_name: SuperLim
task_categories:
- question-answering
- text-classification
- sequence-modeling
- other
---
# Dataset Card for SuperLim
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summ... |
tau/mrqa | 2022-03-21T19:26:55.000Z | [
"region:us"
] | tau | The MRQA 2019 Shared Task focuses on generalization in question answering.
An effective question answering system should do more than merely
interpolate from the training set to answer test examples drawn
from the same distribution: it should also be able to extrapolate
to out-of-distribution examples — a significantly... | @inproceedings{fisch2019mrqa,
title={{MRQA} 2019 Shared Task: Evaluating Generalization in Reading Comprehension},
author={Adam Fisch and Alon Talmor and Robin Jia and Minjoon Seo and Eunsol Choi and Danqi Chen},
booktitle={Proceedings of 2nd Machine Reading for Reading Comprehension (MRQA) Workshop at EMNL... | null | 0 | 82 | Entry not found |
nlpaueb/multi_eurlex | 2022-10-25T10:29:13.000Z | [
"task_categories:text-classification",
"task_ids:multi-label-classification",
"task_ids:topic-classification",
"annotations_creators:found",
"language_creators:found",
"language_creators:machine-generated",
"multilinguality:multilingual",
"size_categories:10K<n<100K",
"source_datasets:extended|multi... | nlpaueb | An non-parallel version of the MultiEURLEX datasets released by Chalkidis et al. (2021).
MultiEURLEX comprises 65k EU laws in 23 official EU languages (some low-ish resource).
Each EU law has been annotated with EUROVOC concepts (labels) by the Publication Office of EU.
As with the English EURLEX, the goal is to predi... | @InProceedings{xenouleas-etal-2022-realistic-multieurlex,
author = {Xenouleas, Stratos
and Tsoukara, Alexia
and Panagiotakis, Giannis
and Chalkidis, Ilias
and Androutsopoulos, Ion},
title = {Realistic Zero-Shot Cross-Lingual Transfer in Legal Topic Cla... | null | 4 | 82 | ---
pretty_name: Non-Parallel MultiEURLEX (incl. Translations)
annotations_creators:
- found
language_creators:
- found
- machine-generated
language:
- en
- de
- fr
- el
- sk
license:
- cc-by-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10K<n<100K
source_datasets:
- extended|multi_eurlex
task_categories:
... |
TheGreatRambler/mm2_level | 2022-11-11T08:07:34.000Z | [
"task_categories:other",
"task_categories:object-detection",
"task_categories:text-retrieval",
"task_categories:token-classification",
"task_categories:text-generation",
"multilinguality:multilingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"language:multilingual",
"license:cc-b... | TheGreatRambler | null | null | null | 5 | 82 | ---
language:
- multilingual
license:
- cc-by-nc-sa-4.0
multilinguality:
- multilingual
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- other
- object-detection
- text-retrieval
- token-classification
- text-generation
task_ids: []
pretty_name: Mario Maker 2 levels
tags:
- text-mining
---
... |
ciempiess/ciempiess_test | 2023-08-11T19:19:33.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:es",
"license:cc-by-sa-4.0",
"ciempiess",
"spanish",
"mexican spanish",
"test set... | ciempiess | The CIEMPIESS TEST Corpus is a gender balanced corpus destined to test acoustic models for the speech recognition task. The corpus was manually transcribed and it contains audio recordings from 10 male and 10 female speakers. The CIEMPIESS TEST is one of the three corpora included at the LDC's \"CIEMPIESS Experimentati... | @misc{carlosmenaciempiesstest2022,
title={CIEMPIESS TEST CORPUS: Audio and Transcripts of Mexican Spanish Broadcast Conversations.},
ldc_catalog_no={LDC2019S07},
DOI={https://doi.org/10.35111/xdx5-n815},
author={Hernandez Mena, Carlos Daniel},
journal={Linguistic Data Consortium, Philadel... | null | 0 | 82 | ---
annotations_creators:
- expert-generated
language:
- es
language_creators:
- other
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: 'CIEMPIESS TEST CORPUS: Audio and Transcripts of Mexican Spanish Broadcast Conversations.'
size_categories:
- 1K<n<10K
source_datasets:
- original
tags:
- ciempiess
... |
lewtun/titanic | 2022-12-15T17:59:50.000Z | [
"kaggle",
"region:us"
] | lewtun | null | null | null | 0 | 82 | ---
tags:
- kaggle
dataset_info:
features:
- name: PassengerId
dtype: int64
- name: Survived
dtype: int64
- name: Pclass
dtype: int64
- name: Name
dtype: string
- name: Sex
dtype: string
- name: Age
dtype: float64
- name: SibSp
dtype: int64
- name: Parch
dtype: int64
... |
metaeval/strategy-qa | 2023-02-09T14:56:34.000Z | [
"region:us"
] | metaeval | null | null | null | 2 | 82 | Entry not found |
edarchimbaud/earnings-forecast-stocks | 2023-10-07T23:14:13.000Z | [
"task_categories:tabular-regression",
"language:en",
"license:mit",
"region:us"
] | edarchimbaud | null | null | null | 2 | 82 | ---
language:
- en
license: mit
task_categories:
- tabular-regression
dataset_info:
features:
- name: symbol
dtype: string
- name: date
dtype: string
- name: id
dtype: int64
- name: fiscal_end
dtype: string
- name: consensus_eps_forecast
dtype: float64
- name: high_eps_forecast
dty... |
edarchimbaud/short-interest-stocks | 2023-10-07T23:16:33.000Z | [
"task_categories:tabular-regression",
"language:en",
"license:mit",
"region:us"
] | edarchimbaud | null | null | null | 1 | 82 | ---
language:
- en
license: mit
task_categories:
- tabular-regression
dataset_info:
features:
- name: symbol
dtype: string
- name: date
dtype: string
- name: id
dtype: int64
- name: settlement_date
dtype: timestamp[ns]
- name: interest
dtype: float64
- name: avg_daily_share_volume
... |
edarchimbaud/timeseries-1m-stocks | 2023-10-10T10:03:14.000Z | [
"task_categories:tabular-regression",
"language:en",
"license:mit",
"region:us"
] | edarchimbaud | null | null | null | 1 | 82 | ---
language:
- en
license: mit
task_categories:
- tabular-regression
dataset_info:
features:
- name: symbol
dtype: string
- name: datetime
dtype: timestamp[ns]
- name: open
dtype: float64
- name: high
dtype: float64
- name: low
dtype: float64
- name: close
dtype: float64
- name:... |
clarin-knext/trec-covid-pl-qrels | 2023-06-07T08:11:44.000Z | [
"language:pl",
"arxiv:2305.19840",
"region:us"
] | clarin-knext | null | null | null | 0 | 82 | ---
language:
- pl
---
Part of **BEIR-PL: Zero Shot Information Retrieval Benchmark for the Polish Language**.
Link to arxiv: https://arxiv.org/pdf/2305.19840.pdf
Contact: konrad.wojtasik@pwr.edu.pl |
C-MTEB/ATEC | 2023-07-28T13:53:38.000Z | [
"region:us"
] | C-MTEB | null | null | null | 2 | 82 | ---
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: sentence1
dtype: string
- name: sentence2
dtype: string
- name: score
dtype: int32
split... |
tyzhu/squad_instruction_v1 | 2023-09-12T17:03:59.000Z | [
"region:us"
] | tyzhu | null | null | null | 0 | 82 | ---
dataset_info:
features:
- name: inputs
dtype: string
- name: targets
dtype: string
- name: question
dtype: string
- name: context
dtype: string
- name: answers
struct:
- name: answer_start
sequence: int64
- name: text
sequence: string
- name: id
dtype: strin... |
fiveflow/koquad_v2_polyglot_tkd | 2023-09-15T15:52:16.000Z | [
"region:us"
] | fiveflow | null | null | null | 0 | 82 | ---
dataset_info:
features:
- name: input_ids
sequence: int32
- name: attention_mask
sequence: int8
- name: labels
sequence: int64
splits:
- name: train
num_bytes: 7699047417
num_examples: 50000
download_size: 1305602573
dataset_size: 7699047417
---
# Dataset Card for "koquad_v2_poly... |
cawoylel/FulaSpeechCorpora | 2023-09-22T16:10:37.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:text-to-speech",
"task_categories:audio-classification",
"size_categories:100K<n<1M",
"language:ff",
"region:us"
] | cawoylel | null | null | null | 0 | 82 | ---
configs:
- config_name: default
data_files:
- split: pulaar
path: data/pulaar-*
- split: maacina
path: data/maacina-*
- split: liptako
path: data/liptako-*
- split: caka
path: data/caka-*
- split: bororro
path: data/bororro-*
- split: borgu
path: data/borgu-*
- split: pular
... |
notrichardren/azaria-mitchell-diff-filtered | 2023-10-03T04:33:20.000Z | [
"region:us"
] | notrichardren | null | null | null | 0 | 82 | ---
configs:
- config_name: default
data_files:
- split: cities
path: data/cities-*
- split: companies
path: data/companies-*
- split: animals
path: data/animals-*
- split: elements
path: data/elements-*
- split: inventions
path: data/inventions-*
- split: facts
path: data/facts-*
... |
code_x_glue_cc_code_completion_token | 2023-06-12T08:13:31.000Z | [
"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:10K<n<100K",
"source_datasets:original",
"language:code",
"l... | null | Predict next code token given context of previous tokens. Models are evaluated by token level accuracy.
Code completion is a one of the most widely used features in software development through IDEs. An effective code completion tool could improve software developers' productivity. We provide code completion evaluation... | @article{raychev2016probabilistic,
title={Probabilistic Model for Code with Decision Trees},
author={Raychev, Veselin and Bielik, Pavol and Vechev, Martin},
journal={ACM SIGPLAN Notices},
pages={731--747},
year={2016},
publisher={ACM New York, NY, USA}
}
@inproceedings{allamanis2013mining,
t... | null | 1 | 81 | ---
annotations_creators:
- found
language_creators:
- found
language:
- code
license:
- c-uda
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-generation
- fill-mask
task_ids:
- language-modeling
- masked-language-modeling
pretty_name: CodeXGlueCcCodeComp... |
kilt_wikipedia | 2023-04-05T10:08:59.000Z | [
"region:us"
] | null | KILT-Wikipedia: Wikipedia pre-processed for KILT. | @inproceedings{fb_kilt,
author = {Fabio Petroni and
Aleksandra Piktus and
Angela Fan and
Patrick Lewis and
Majid Yazdani and
Nicola De Cao and
James Thorne and
Yacine Jernite and
... | null | 10 | 81 | ---
paperswithcode_id: null
pretty_name: KiltWikipedia
dataset_info:
features:
- name: kilt_id
dtype: string
- name: wikipedia_id
dtype: string
- name: wikipedia_title
dtype: string
- name: text
sequence:
- name: paragraph
dtype: string
- name: anchors
sequence:
- name: par... |
GEM/schema_guided_dialog | 2022-10-24T15:30:26.000Z | [
"task_categories:conversational",
"annotations_creators:crowd-sourced",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-sa-4.0",
"dialog-response-generation",
"arxiv:1909.05855",
"arxiv:2004.15006",
"a... | GEM | The Schema-Guided Dialogue (SGD) dataset contains 18K multi-domain task-oriented
dialogues between a human and a virtual assistant, which covers 17 domains
ranging from banks and events to media, calendar, travel, and weather. The
language presents in the datset is only English. The SGD dataset provides a
challenging t... | @inproceedings{rastogi2020towards,
title={Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset},
author={Rastogi, Abhinav and Zang, Xiaoxue and Sunkara, Srinivas and Gupta, Raghav and Khaitan, Pranav},
booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
... | null | 3 | 81 | ---
annotations_creators:
- crowd-sourced
language_creators:
- unknown
language:
- en
license:
- cc-by-sa-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: schema_guided_dialog
tags:
- dialog-response-generation
---
# Datas... |
iohadrubin/mtop | 2022-01-01T20:54:04.000Z | [
"region:us"
] | iohadrubin | null | 0 | 81 | Entry not found | ||
katanaml/cord | 2022-03-06T15:02:45.000Z | [
"region:us"
] | katanaml | https://huggingface.co/datasets/katanaml/cord | @article{park2019cord,
title={CORD: A Consolidated Receipt Dataset for Post-OCR Parsing},
author={Park, Seunghyun and Shin, Seung and Lee, Bado and Lee, Junyeop and Surh, Jaeheung and Seo, Minjoon and Lee, Hwalsuk}
booktitle={Document Intelligence Workshop at Neural Information Processing Systems}
year={2019}
} | null | 1 | 81 | # CORD: A Consolidated Receipt Dataset for Post-OCR Parsing
CORD dataset is cloned from [clovaai](https://github.com/clovaai/cord) GitHub repo
- Box coordinates are normalized against image width/height
- Labels with very few occurrences are replaced with O:
```
replacing_labels = ['menu.etc', 'menu.itemsubtotal',
... |
truongpdd/vietnamese_story | 2022-09-23T04:44:26.000Z | [
"region:us"
] | truongpdd | null | null | null | 0 | 81 | Entry not found |
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