author stringlengths 2 29 ⌀ | cardData null | citation stringlengths 0 9.58k ⌀ | description stringlengths 0 5.93k ⌀ | disabled bool 1
class | downloads float64 1 1M ⌀ | gated bool 2
classes | id stringlengths 2 108 | lastModified stringlengths 24 24 | paperswithcode_id stringlengths 2 45 ⌀ | private bool 2
classes | sha stringlengths 40 40 | siblings list | tags list | readme_url stringlengths 57 163 | readme stringlengths 0 977k |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
yuningm | null | @misc{https://doi.org/10.48550/arxiv.2205.06207,
doi = {10.48550/ARXIV.2205.06207},
url = {https://arxiv.org/abs/2205.06207},
author = {Mao, Yuning and Zhong, Ming and Han, Jiawei},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
t... | CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation.
CiteSum contains TLDR summaries for scientific papers from their citation texts without human annotation,
making it around 30 times larger than the previous human-curated dataset SciTLDR. | false | 10 | false | yuningm/citesum | 2022-10-25T10:39:26.000Z | citesum | false | 38139de09992c33d51f53531bbf3d575ca3e2e27 | [] | [
"arxiv:2205.06207",
"language:en",
"license:cc-by-nc-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:summarization"
] | https://huggingface.co/datasets/yuningm/citesum/resolve/main/README.md | ---
language:
- en
license: cc-by-nc-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- summarization
paperswithcode_id: citesum
---
# CiteSum
## Description
CiteSum: Citation Text-guided Scientific Extreme Summarization and Low-resource Domain Adaptation.... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-183be059-9075194 | 2022-06-29T20:26:38.000Z | null | false | bf7670076120164edc138d6394f6ea6820907de4 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:conll2003"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-183be059-9075194/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- conll2003
eval_info:
task: entity_extraction
model: dslim/bert-base-NER
metrics: []
dataset_name: conll2003
dataset_config: conll2003
dataset_split: test
col_mapping:
tokens: tokens
tags: ner_tags
---
# Dataset Card for AutoTrain Eva... |
SerdarHelli | null | null | null | false | 5 | false | SerdarHelli/SegmentationOfTeethPanoramicXRayImages | 2022-10-29T20:05:26.000Z | null | false | da4e9f4db86e259f783e89a50fd8f811dfe3f257 | [] | [
"size_categories:n<1K",
"task_categories:image-segmentation",
"task_ids:semantic-segmentation",
"tags:teeth-segmentation",
"tags:dental-imaging",
"tags:medical-imaging"
] | https://huggingface.co/datasets/SerdarHelli/SegmentationOfTeethPanoramicXRayImages/resolve/main/README.md | ---
size_categories:
- n<1K
task_categories:
- image-segmentation
task_ids:
- semantic-segmentation
tags:
- teeth-segmentation
- dental-imaging
- medical-imaging
train-eval-index:
- config: plain_text
task: semantic_segmentation
task_id: semantic_segmentation
splits:
train_split: train
eval_split: test
... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-87e7c3be-9085195 | 2022-06-29T21:11:33.000Z | null | false | 51da51ef377f004e18152d6e02ed1e31eb2466d9 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:clinc_oos"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-87e7c3be-9085195/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- clinc_oos
eval_info:
task: multi_class_classification
model: dbounds/roberta-large-finetuned-clinc
metrics: []
dataset_name: clinc_oos
dataset_config: small
dataset_split: test
col_mapping:
text: text
target: intent
---
# Dataset Car... |
davidberg | null | null | null | false | 1 | false | davidberg/inflation | 2022-06-29T21:57:10.000Z | null | false | f19a3041fde864693ebfa1a34337b0b62e055880 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/davidberg/inflation/resolve/main/README.md | ---
license: apache-2.0
---
|
davidberg | null | null | null | false | 1 | false | davidberg/sentiment-reviews | 2022-06-29T22:38:11.000Z | null | false | c43462c3ad3938da22954e98f95a5cb506e1dd23 | [] | [
"license:postgresql"
] | https://huggingface.co/datasets/davidberg/sentiment-reviews/resolve/main/README.md | ---
license: postgresql
---
|
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-00ac2adb-9115197 | 2022-06-29T22:41:58.000Z | null | false | 74178ac21d8791035a616fd4f97bbd652b541c78 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:cifar10"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-00ac2adb-9115197/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cifar10
eval_info:
task: image_multi_class_classification
model: abhishek/autotrain_cifar10_vit_base
metrics: []
dataset_name: cifar10
dataset_config: plain_text
dataset_split: test
col_mapping:
image: img
target: label
---
# Dataset... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-00ac2adb-9115199 | 2022-06-29T22:42:09.000Z | null | false | c535f479a30ffc48bc48663ca86c6f20272e9219 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:cifar10"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-00ac2adb-9115199/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cifar10
eval_info:
task: image_multi_class_classification
model: karthiksv/vit-base-patch16-224-cifar10
metrics: []
dataset_name: cifar10
dataset_config: plain_text
dataset_split: test
col_mapping:
image: img
target: label
---
# Data... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-00ac2adb-9115200 | 2022-06-29T22:42:47.000Z | null | false | e0d72b4c4e3aa00dc38e60a88deac5c4b3c10312 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:cifar10"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-00ac2adb-9115200/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cifar10
eval_info:
task: image_multi_class_classification
model: jimypbr/cifar10_outputs
metrics: []
dataset_name: cifar10
dataset_config: plain_text
dataset_split: test
col_mapping:
image: img
target: label
---
# Dataset Card for Au... |
loubnabnl | null | null | null | false | 1 | false | loubnabnl/github-code-more-filtering | 2022-06-30T22:28:37.000Z | null | false | 7d4eca2f188da2be524a990684e5871f4b836b50 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/loubnabnl/github-code-more-filtering/resolve/main/README.md | ---
license: apache-2.0
---
|
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-00ac2adb-9115202 | 2022-06-29T22:43:31.000Z | null | false | cc79d4ca52014f13aee22ec5c7872cebac96c9ed | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:cifar10"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-00ac2adb-9115202/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- cifar10
eval_info:
task: image_multi_class_classification
model: tanlq/vit-base-patch16-224-in21k-finetuned-cifar10
metrics: []
dataset_name: cifar10
dataset_config: plain_text
dataset_split: test
col_mapping:
image: img
target: labe... |
codeparrot | null | null | The GitHub Code clean dataset in a more filtered version of codeparrot/github-code dataset, it consists of 115M code files from GitHub in 32 programming languages with 60 extensions totaling in almost 1TB of text data. | false | 13,769 | false | codeparrot/github-code-clean | 2022-07-05T09:35:14.000Z | null | false | c48d40f9e70f0196f8236901ee35807f7d6c44c0 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/codeparrot/github-code-clean/resolve/main/README.md | ---
license: apache-2.0
---
This is a cleaner version of [Github-code dataset](https://huggingface.co/datasets/codeparrot/github-code), we add the following filters:
* Average line length < 100
* Alpha numeric characters fraction > 0.25
* Remove auto-generated files (keyword search)
3.39M files are removed making up 2... |
launch | null | @inproceedings{cao-wang-2021-controllable,
title = "Controllable Open-ended Question Generation with A New Question Type Ontology",
author = "Cao, Shuyang and
Wang, Lu",
booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joi... | Reddit question generation dataset. | false | 1 | false | launch/reddit_qg | 2022-11-09T01:58:05.000Z | null | false | 77859ef0ac63997f4e1a16f27cc4acbf8a06cc2f | [] | [
"annotations_creators:expert-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"task_categories:text-classification"
] | https://huggingface.co/datasets/launch/reddit_qg/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
task_categories:
- text-classification
task_ids: []
pretty_name: RedditQG
---
# Dataset Card for RedditQG
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-des... |
Manuel | null | null | null | false | 1 | false | Manuel/sentencias-corte-cons-colombia-1992-2021 | 2022-06-30T02:49:09.000Z | null | false | 3b2e18d24afd6b82d6db4bb5552c64298e1ad8b2 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/Manuel/sentencias-corte-cons-colombia-1992-2021/resolve/main/README.md | ---
license: cc-by-4.0
---
sentencias-corte-cons-colombia-1992-2021.
23750 Case law of the Colombia's Corte Constitucional.
Each row is a complete text of each case law.
23750 case law from 1992-2021.
Columns:
ID
Texto: Complete text of the sentence |
superjordan | null | null | null | false | 4 | false | superjordan/insurance_qa | 2022-06-30T08:30:45.000Z | null | false | e24bf67e5967acd7359533aab1a406cbee4fc60a | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/superjordan/insurance_qa/resolve/main/README.md | ---
license: apache-2.0
---
|
Langame | null | null | null | false | 1 | false | Langame/langame-seeker | 2022-06-30T06:42:22.000Z | null | false | 094794ba406881792473d6d32a26ab95e41c1dfc | [] | [
"license:wtfpl"
] | https://huggingface.co/datasets/Langame/langame-seeker/resolve/main/README.md | ---
license: wtfpl
---
# langame-seeker
Self chat between two [Seeker Search-Augmented Language Model](https://parl.ai/projects/seeker/) using [Langame](https://langa.me/) conversation starters generated by Langame's proprietary language model. The 3000 conversation starters have been generated beforehand into an "of... |
dddb | null | null | null | false | 1 | false | dddb/autotrain-data-mt5_chinese_small_finetune | 2022-06-30T12:59:06.000Z | null | false | b34049cde0f0d716b965b826b6e3ddbaae7fee48 | [] | [] | https://huggingface.co/datasets/dddb/autotrain-data-mt5_chinese_small_finetune/resolve/main/README.md | ---
task_categories:
- conditional-text-generation
---
# AutoTrain Dataset for project: mt5_chinese_small_finetune
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project mt5_chinese_small_finetune.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset S... |
PolyAI | null | @inproceedings{Spithourakis2022evi,
author = {Georgios P. Spithourakis and Ivan Vuli\'{c} and Micha\l{} Lis and I\~{n}igo Casanueva and Pawe\l{} Budzianowski},
title = {{EVI}: Multilingual Spoken Dialogue Tasks and Dataset for Knowledge-Based Enrolment, Verification, and Identification},
year ... | EVI is a challenging spoken multilingual dataset with 5,506 dialogues in English, Polish, and French
that can be used for benchmarking and developing knowledge-based enrolment, identification, and identification
for spoken dialogue systems. | false | 1 | false | PolyAI/evi | 2022-10-25T10:39:33.000Z | evi-multilingual-spoken-dialogue-tasks-and-1 | false | 2e5f8d3dc550028d9ae1dbbb94476a6ae282134b | [] | [
"arxiv:2204.13496",
"annotations_creators:crowdsourced",
"annotations_creators:machine-generated",
"language_creators:crowdsourced",
"language_creators:expert-generated",
"language:en",
"language:fr",
"language:pl",
"license:cc-by-4.0",
"multilinguality:multilingual",
"language_bcp47:en",
"lan... | https://huggingface.co/datasets/PolyAI/evi/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
- machine-generated
language_creators:
- crowdsourced
- expert-generated
language:
- en
- fr
- pl
license:
- cc-by-4.0
multilinguality:
- multilingual
paperswithcode_id: evi-multilingual-spoken-dialogue-tasks-and-1
language_bcp47:
- en
- en-GB
- fr
- fr-FR
- pl
---
# EVI
## Da... |
AntoineLB | null | null | null | false | 1 | false | AntoineLB/watt-saving-agent-0 | 2022-07-19T13:21:51.000Z | null | false | bfe0aad3b98276b0223c58fba78bec540ac1e3f2 | [] | [] | https://huggingface.co/datasets/AntoineLB/watt-saving-agent-0/resolve/main/README.md | |
Tipfa | null | null | null | false | 7 | false | Tipfa/LibriAdapt | 2022-06-30T14:59:50.000Z | null | false | b42580de72377e12a2da4208246b5615d95296ae | [] | [] | https://huggingface.co/datasets/Tipfa/LibriAdapt/resolve/main/README.md | |
mesolitica | null | null | null | false | 1 | false | mesolitica/noisy-ms-en-augmentation | 2022-07-17T09:41:07.000Z | null | false | 413a9d216a483578b30e32df07ac2ecbdff14e43 | [] | [
"tags:generated_from_keras_callback"
] | https://huggingface.co/datasets/mesolitica/noisy-ms-en-augmentation/resolve/main/README.md | ---
tags:
- generated_from_keras_callback
model-index:
- name: t5-tiny-finetuned-noisy-ms-en
results: []
---
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
# ms-en
Notebooks to gath... |
allenai | null | null | null | false | 7,233 | false | allenai/metaicl-data | 2022-06-30T21:18:49.000Z | null | false | d24215071fc64685ee5a089688a4622b11d86786 | [] | [
"arxiv:2005.00700",
"license:cc-by-nc-4.0"
] | https://huggingface.co/datasets/allenai/metaicl-data/resolve/main/README.md | ---
license: cc-by-nc-4.0
---
This is the downloaded and processed data from Meta's [MetaICL](https://github.com/facebookresearch/MetaICL).
We follow their ["How to Download and Preprocess"](https://github.com/facebookresearch/MetaICL#how-to-download-and-preprocess) instructions to obtain their modified versions of [... |
richt | null | null | null | false | 1 | false | richt/Euroc | 2022-06-30T18:59:22.000Z | null | false | aafd21a31f3c31332a2140a7df63bf661e291f26 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/richt/Euroc/resolve/main/README.md | ---
license: apache-2.0
---
|
arize-ai | null | # @InProceedings{huggingface:dataset,
# title = {A great new dataset},
# author={huggingface, Inc.
# },
# year={2020}
# }
# | This dataset was crafted to be used in our tutorial [Link to the tutorial when
ready]. It consists on product reviews from an e-commerce store. The reviews
are labeled on a scale from 1 to 5 (stars). The training & validation sets are
fully composed by reviews written in english. However, the production set has
some re... | false | 1 | false | arize-ai/xtreme_en | 2022-07-01T17:23:29.000Z | null | false | 6d6b24c4204a6731263bcd5ec76564bbdbfbca58 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|xtreme",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/arize-ai/xtreme_en/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: named-entity-recognition-en-no-drift
size_categories:
- 10K<n<100K
source_datasets:
- extended|xtreme
task_categories:
- token-classification
task_ids:
- named-ent... |
arize-ai | null | # @InProceedings{huggingface:dataset,
# title = {A great new dataset},
# author={huggingface, Inc.
# },
# year={2020}
# }
# | This dataset was crafted to be used in our tutorial [Link to the tutorial when
ready]. It consists on product reviews from an e-commerce store. The reviews
are labeled on a scale from 1 to 5 (stars). The training & validation sets are
fully composed by reviews written in english. However, the production set has
some re... | false | 1 | false | arize-ai/xtreme_en_language_drift_es | 2022-07-01T17:25:51.000Z | null | false | dd67b07acb615f16950e239d3e5035ffd40b696a | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|xtreme",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/arize-ai/xtreme_en_language_drift_es/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: named-entity-recognition-en-no-drift
size_categories:
- 10K<n<100K
source_datasets:
- extended|xtreme
task_categories:
- token-classification
task_ids:
- named-ent... |
arize-ai | null | # @InProceedings{huggingface:dataset,
# title = {A great new dataset},
# author={huggingface, Inc.
# },
# year={2020}
# }
# | This dataset was crafted to be used in our tutorial [Link to the tutorial when
ready]. It consists on product reviews from an e-commerce store. The reviews
are labeled on a scale from 1 to 5 (stars). The training & validation sets are
fully composed by reviews written in english. However, the production set has
some re... | false | 1 | false | arize-ai/xtreme_en_token_drift | 2022-07-01T17:25:34.000Z | null | false | feb643d1f0a55643f91347b4c418d243343a94cd | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:mit",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|xtreme",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/arize-ai/xtreme_en_token_drift/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: named-entity-recognition-en-no-drift
size_categories:
- 10K<n<100K
source_datasets:
- extended|xtreme
task_categories:
- token-classification
task_ids:
- named-ent... |
bengaliAI | null | @inproceedings{commonvoice:2020,
author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
title = {Common Voice: A Massively-Multilingual Speech Corpus},
booktitle = {Proceedings of the 12th Conference on Lang... | null | false | 12 | false | bengaliAI/cvbn | 2022-07-01T02:17:25.000Z | null | false | ba204823a7b512e73ef1fe218dac19ad29c8afa1 | [] | [
"license:cc"
] | https://huggingface.co/datasets/bengaliAI/cvbn/resolve/main/README.md | ---
license: cc
---
|
launch | null | null | null | false | 8 | false | launch/ampere | 2022-11-09T01:57:52.000Z | null | false | e81e6a9ac798674b1a72239936bc4f71c4fa2c4e | [] | [
"annotations_creators:expert-generated",
"language:en",
"license:cc-by-4.0",
"multilinguality:monolingual",
"task_categories:text-classification"
] | https://huggingface.co/datasets/launch/ampere/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
task_categories:
- text-classification
task_ids: []
pretty_name: AMPERE
---
# Dataset Card for AMPERE
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-descript... |
Maysee | null | null | null | false | 3,951 | false | Maysee/tiny-imagenet | 2022-07-12T09:04:30.000Z | imagenet | false | 5a77092c28e51558c5586e9c5eb71a7e17a5e43f | [] | [
"annotations_creators:crowdsourced",
"extra_gated_prompt:By clicking on “Access repository” below, you also agree to ImageNet Terms of Access:\n[RESEARCHER_FULLNAME] (the \"Researcher\") has requested permission to use the ImageNet database (the \"Database\") at Princeton University and Stanford University. In ex... | https://huggingface.co/datasets/Maysee/tiny-imagenet/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
extra_gated_prompt: "By clicking on \u201CAccess repository\u201D below, you also\
\ agree to ImageNet Terms of Access:\n[RESEARCHER_FULLNAME] (the \"Researcher\"\
) has requested permission to use the ImageNet database (the \"Database\") at Princeton\
\ University and Sta... |
Tritkoman | null | null | null | false | 1 | false | Tritkoman/autotrain-data-Rusynpannonianpure | 2022-10-25T10:39:40.000Z | null | false | f7abfbaa550a0d2cd478151aa437b303badc4dc9 | [] | [
"language:en",
"language:es",
"task_categories:translation"
] | https://huggingface.co/datasets/Tritkoman/autotrain-data-Rusynpannonianpure/resolve/main/README.md | ---
language:
- en
- es
task_categories:
- translation
---
# AutoTrain Dataset for project: Rusynpannonianpure
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project Rusynpannonianpure.
### Languages
The BCP-47 code for the dataset's language is en2es.
## Dataset Structure
#... |
AswiN037 | null | null | null | false | 1 | false | AswiN037/tamil-question-answering-dataset | 2022-07-01T07:53:56.000Z | null | false | 09feea6476dba673a37248873f4e6e9998f1913d | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/AswiN037/tamil-question-answering-dataset/resolve/main/README.md | ---
license: afl-3.0
---
this dataset contains 5 columns
context, question, answer_start, answer_text, source
| Column | Description |
| :------------ |:---------------:|
| context | A general small paragraph in tamil language |
| question | question framed form the context |
| answer_text | ... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-a25a94fd-9305221 | 2022-07-02T12:09:46.000Z | null | false | 2ba908ef5001980a29cd652c16cebfe1a69035f8 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:big_patent"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-a25a94fd-9305221/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- big_patent
eval_info:
task: summarization
model: google/bigbird-pegasus-large-bigpatent
metrics: ['rouge']
dataset_name: big_patent
dataset_config: all
dataset_split: validation
col_mapping:
text: description
target: abstract
---
# D... |
GEM-submissions | null | null | null | false | 2 | false | GEM-submissions/lewtun__this-is-a-test-submission-2__1656667730 | 2022-07-01T09:28:55.000Z | null | false | 13ad152ac29b49542dfbb3500c6b72a499731db8 | [] | [
"benchmark:gem",
"type:prediction",
"submission_name:This is a test submission 2",
"tags:evaluation",
"tags:benchmark"
] | https://huggingface.co/datasets/GEM-submissions/lewtun__this-is-a-test-submission-2__1656667730/resolve/main/README.md | ---
benchmark: gem
type: prediction
submission_name: This is a test submission 2
tags:
- evaluation
- benchmark
---
# GEM Submission
Submission name: This is a test submission 2
|
benschill | null | @misc{kaggle-brain-tumor-classification,
title={Kaggle: Brain Tumor Classification (MRI)},
howpublished={\\url{https://www.kaggle.com/datasets/sartajbhuvaji/brain-tumor-classification-mri?resource=download}},
note = {Accessed: 2022-06-30},
} | This dataset is intended as a test case for classification tasks (4 different kinds of brain xrays). The dataset consists of almost 1400 JPEG images grouped into two splits - training and validation. Each split contains 4 categories labeled as n0~n3, each corresponding to a cancer result of the mrt.
| Label | Xray Ca... | false | 1 | false | benschill/brain-tumor-collection | 2022-07-04T08:26:59.000Z | null | false | fe18ffc594c9e8bade2ea0049f90d2e7d25ed7f7 | [] | [
"license:pddl"
] | https://huggingface.co/datasets/benschill/brain-tumor-collection/resolve/main/README.md | ---
license: pddl
---
|
dgrnd4 | null | null | null | false | 52 | false | dgrnd4/stanford_dog_dataset | 2022-07-01T11:27:56.000Z | null | false | 3fd4d57d14b98665aa12b9e6a359a15f203ef787 | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/dgrnd4/stanford_dog_dataset/resolve/main/README.md | ---
license: afl-3.0
---
|
joelito | null | null | null | false | 2,705 | false | joelito/covid19_emergency_event | 2022-09-22T13:44:15.000Z | null | false | bba0491bc1ba950369eafcceb1d522537b54ab2e | [] | [
"annotations_creators:found",
"annotations_creators:other",
"language_creators:found",
"language:en",
"language:fr",
"language:hu",
"language:it",
"language:nb",
"language:nl",
"language:pl",
"license:cc0-1.0",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:or... | https://huggingface.co/datasets/joelito/covid19_emergency_event/resolve/main/README.md | ---
annotations_creators:
- found
- other
language_creators:
- found
language:
- en
- fr
- hu
- it
- nb
- nl
- pl
license:
- cc0-1.0
multilinguality:
- multilingual
pretty_name: EXCEPTIUS Corpus
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-label-classi... |
joelito | null | null | null | false | 1,738 | false | joelito/german_argument_mining | 2022-09-22T13:44:35.000Z | null | false | 576b52004ed78dd747c0f9858fa6dacc7e4196e2 | [] | [
"annotations_creators:expert-generated",
"annotations_creators:found",
"language_creators:found",
"language:de",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-class-classification... | https://huggingface.co/datasets/joelito/german_argument_mining/resolve/main/README.md | ---
annotations_creators:
- expert-generated
- found
language_creators:
- found
language:
- de
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Annotated German Legal Decision Corpus
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-... |
joelito | null | null | null | false | 1,652 | false | joelito/greek_legal_ner | 2022-09-22T13:44:49.000Z | null | false | 2b39f22db86ba0e9a0e22144611b9a2766edcce1 | [] | [
"annotations_creators:other",
"language_creators:found",
"language:el",
"license:cc-by-nc-sa-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/joelito/greek_legal_ner/resolve/main/README.md | ---
annotations_creators:
- other
language_creators:
- found
language:
- el
license:
- cc-by-nc-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: Greek Legal Named Entity Recognition
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- na... |
joelito | null | null | null | false | 1,159 | false | joelito/legalnero | 2022-09-22T13:45:09.000Z | null | false | d7c1daa1778709f527069edc0b71d9ac144de495 | [] | [
"annotations_creators:other",
"language_creators:found",
"language:ro",
"license:cc-by-nc-nd-4.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:token-classification",
"task_ids:named-entity-recognition"
] | https://huggingface.co/datasets/joelito/legalnero/resolve/main/README.md | ---
annotations_creators:
- other
language_creators:
- found
language:
- ro
license:
- cc-by-nc-nd-4.0
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: Romanian Named Entity Recognition in the Legal domain (LegalNERo)
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- token-... |
joelito | null | null | null | false | 2,734 | false | joelito/online_terms_of_service | 2022-09-22T13:45:42.000Z | null | false | 448c5caa985b8dafb275294f226120f41a7f8251 | [] | [
"annotations_creators:found",
"annotations_creators:other",
"language_creators:found",
"language:de",
"language:en",
"language:it",
"language:pl",
"license:other",
"multilinguality:multilingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"... | https://huggingface.co/datasets/joelito/online_terms_of_service/resolve/main/README.md | ---
annotations_creators:
- found
- other
language_creators:
- found
language:
- de
- en
- it
- pl
license:
- other
multilinguality:
- multilingual
pretty_name: A Corpus for Multilingual Analysis of Online Terms of Service
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
ta... |
lapix | null | @misc{CCAgTDataset,
doi = {10.17632/WG4BPM33HJ.2},
url = {https://data.mendeley.com/datasets/wg4bpm33hj/2},
author = {Jo{\\~{a}}o Gustavo Atkinson Amorim and Andr{\'{e}} Vict{\'{o}}ria Matias and Tainee Bottamedi and Vinícius Sanches and Ane Francyne Costa and Fabiana Botelho De Miranda Onofre and Alexandre Sher... | The CCAgT (Images of Cervical Cells with AgNOR Stain Technique) dataset contains 9339 images (1600x1200 resolution where each pixel is 0.111µmX0.111µm) from 15 different slides stained using the AgNOR technique.
Each image has at least one label. In total, this dataset has more than 63K instances of annotated object.
T... | false | 1 | false | lapix/CCAgT | 2022-07-27T21:11:52.000Z | null | false | 2f9aa77e76373edaf9fd26f2b4b42a14d230c956 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:en",
"license:cc-by-nc-3.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:image-segmentation",
"task_categories:object-detection",
"task_ids:semantic-... | https://huggingface.co/datasets/lapix/CCAgT/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- cc-by-nc-3.0
multilinguality:
- monolingual
paperswithcode_id: null
pretty_name: Images of Cervical Cells with AgNOR Stain Technique
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- ima... |
davanstrien | null | null | null | false | 1 | false | davanstrien/newspaper_navigator | 2022-10-14T08:15:42.000Z | null | false | 3b109dff6af7c935dda7835e33d6ecf9f2fa0eea | [] | [
"annotations_creators:machine-generated",
"language_creators:machine-generated",
"task_categories:image-to-text",
"task_categories:text-to-image",
"task_categories:feature-extraction",
"task_categories:zero-shot-image-classification",
"task_ids:image-captioning"
] | https://huggingface.co/datasets/davanstrien/newspaper_navigator/resolve/main/README.md | ---
annotations_creators:
- machine-generated
language: []
language_creators:
- machine-generated
license: []
multilinguality: []
pretty_name: Newspaper Navigator
size_categories: []
source_datasets: []
tags: []
task_categories:
- image-to-text
- text-to-image
- feature-extraction
- zero-shot-image-classification
task_... |
gegham | null | null | null | false | 1 | false | gegham/tensor | 2022-07-13T13:07:12.000Z | null | false | 64f93ccd51d919efda61d1cdde92dc31e52deadd | [] | [] | https://huggingface.co/datasets/gegham/tensor/resolve/main/README.md | efdsv |
jonaskoenig | null | null | null | false | 2 | false | jonaskoenig/trump_administration_statement | 2022-07-15T10:53:15.000Z | null | false | 6ac51b5ccffa328054172eac65dc6084c2f6a1c4 | [] | [
"license:mit"
] | https://huggingface.co/datasets/jonaskoenig/trump_administration_statement/resolve/main/README.md | ---
license: mit
---
|
paren8esis | null | @ARTICLE{
9749916,
author={Sykas, Dimitrios and Sdraka, Maria and Zografakis, Dimitrios and Papoutsis, Ioannis},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segmentation wi... | Sen4AgriNet is a Sentinel-2 based time series multi country benchmark dataset, tailored for
agricultural monitoring applications with Machine and Deep Learning. It is annotated from
farmer declarations collected via the Land Parcel Identification System (LPIS) for harmonizing
country wide labels. These declarations ... | false | 5 | false | paren8esis/S4A | 2022-07-04T14:05:06.000Z | null | false | 6ee48afecc22f3a08f6a01267d55a6d0c6d3ebb2 | [] | [
"arxiv:2204.00951"
] | https://huggingface.co/datasets/paren8esis/S4A/resolve/main/README.md | ---
YAML tags:
---
## Dataset Description
- **Homepage:** [www.sen4agrinet.space.noa.gr](https://www.sen4agrinet.space.noa.gr/)
- **Repository:** [github.com/Orion-AI-Lab/S4A](https://github.com/Orion-AI-Lab/S4A)
- **Paper:** ["A Sentinel-2 multi-year, multi-country benchmark dataset for crop classification and segme... |
Yehor | null | null | null | false | 1 | false | Yehor/ukrainian-news-headlines | 2022-07-30T17:39:30.000Z | null | false | cecdd5845d29aa5a62fbcecf294d1b72d8fd860b | [] | [
"language:uk",
"license:cc-by-nc-sa-4.0",
"tags:uk"
] | https://huggingface.co/datasets/Yehor/ukrainian-news-headlines/resolve/main/README.md | ---
language:
- uk
license: cc-by-nc-sa-4.0
tags:
- uk
---
This dataset contains **5,242,391** samples of Ukrainian news headlines.
Usage:
```python
from datasets import load_dataset
ds = load_dataset('Yehor/ukrainian-news-headlines', split='train')
for row in ds:
print(row['headline'])
```
Attribution to ... |
Shlepa | null | null | null | false | 1 | false | Shlepa/Krop | 2022-07-02T03:10:52.000Z | null | false | aafb58901d736dab1d50526db670f2f7df58fac9 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/Shlepa/Krop/resolve/main/README.md | ---
license: apache-2.0
---
|
bryanbocao | null | null | null | false | 1 | false | bryanbocao/coco_minitrain | 2022-07-03T00:10:15.000Z | null | false | aced9745c97a9790fe99638dba7fd4d8f03e44b2 | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/bryanbocao/coco_minitrain/resolve/main/README.md | ---
license: cc-by-4.0
---
|
nev | null | null | null | false | 1 | false | nev/nsd-general-clip | 2022-08-10T20:32:52.000Z | null | false | 7b9d89fae2feed46732ce28327fafab410bb9863 | [] | [
"license:isc"
] | https://huggingface.co/datasets/nev/nsd-general-clip/resolve/main/README.md | ---
license: isc
---
|
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 1 | false | MicPie/unpredictable_full | 2022-08-04T20:07:28.000Z | null | false | 4e75b1b7fabb453a60a571bc9ccc2b95b9789fe0 | [] | [
"arxiv:2208.01009",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_full/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-full
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-generat... |
bigscience-biomedical | null | @inproceedings{scitail,
author = {Tushar Khot and Ashish Sabharwal and Peter Clark},
booktitle = {AAAI}
title = {SciTail: A Textual Entailment Dataset from Science Question Answering},
year = {2018}
} | The SciTail dataset is an entailment dataset created from multiple-choice science exams and
web sentences. Each question and the correct answer choice are converted into an assertive
statement to form the hypothesis. We use information retrieval to obtain relevant text from
a large text corpus of web sentences, and use... | false | 32 | false | bigscience-biomedical/scitail | 2022-10-16T19:22:02.000Z | scitail | false | 0fdbed1e3345a91d2f22be471dd24396c2877052 | [] | [
"language:en",
"license:apache-2.0",
"multilinguality:monolingual"
] | https://huggingface.co/datasets/bigscience-biomedical/scitail/resolve/main/README.md | ---
language: en
license: apache-2.0
multilinguality: monolingual
pretty_name: SciTail
paperswithcode_id: scitail
---
# Dataset Card for SciTail
## Dataset Description
- **Homepage:** https://allenai.org/data/scitail
- **Pubmed:** False
- **Public:** True
- **Tasks:** Textual Entailment
The SciTail dataset is an ... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-854c0218-9415245 | 2022-07-02T22:28:44.000Z | null | false | dad2cadd8d501bf91facd78bbd7a598d98f32e7e | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:emotion"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-854c0218-9415245/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- emotion
eval_info:
task: multi_class_classification
model: lewtun/sagemaker-distilbert-emotion
metrics: []
dataset_name: emotion
dataset_config: default
dataset_split: test
col_mapping:
text: text
target: label
---
# Dataset Card for... |
autoevaluate | null | null | null | false | 1 | false | autoevaluate/autoeval-staging-eval-project-562e1223-9425246 | 2022-07-02T23:01:39.000Z | null | false | f68d414189a214d5a52b5842006e55eb8b95a337 | [] | [
"type:predictions",
"tags:autotrain",
"tags:evaluation",
"datasets:bigscience-biomedical/tmp-scitail"
] | https://huggingface.co/datasets/autoevaluate/autoeval-staging-eval-project-562e1223-9425246/resolve/main/README.md | ---
type: predictions
tags:
- autotrain
- evaluation
datasets:
- bigscience-biomedical/tmp-scitail
eval_info:
task: binary_classification
model: gabrielaltay/autotrain-at-test-bb-tmp-scitail-1078438446
metrics: []
dataset_name: bigscience-biomedical/tmp-scitail
dataset_config: scitail_bigbio_te
dataset_spli... |
dddb | null | null | null | false | 1 | false | dddb/autotrain-data-new_model | 2022-07-03T04:34:26.000Z | null | false | d40231fb47c493a4a6cbdc01e69ef4193b27bd2c | [] | [] | https://huggingface.co/datasets/dddb/autotrain-data-new_model/resolve/main/README.md | ---
task_categories:
- conditional-text-generation
---
# AutoTrain Dataset for project: new_model
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project new_model.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Data Instances
A sa... |
mahdiAsefi | null | null | null | false | 1 | false | mahdiAsefi/autotrain-data-persina-paraphrase | 2022-07-03T06:53:16.000Z | null | false | fc9df95d425ad80e3a96ff6a7738b8fb93ee3c80 | [] | [] | https://huggingface.co/datasets/mahdiAsefi/autotrain-data-persina-paraphrase/resolve/main/README.md | ---
task_categories:
- conditional-text-generation
---
# AutoTrain Dataset for project: persina-paraphrase
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project persina-paraphrase.
### Languages
The BCP-47 code for the dataset's language is unk.
## Dataset Structure
### Da... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_mmo-champion-com | 2022-08-04T20:09:49.000Z | null | false | 85aaa66a7843304692990eea17bc3b89ef99aac5 | [] | [
"arxiv:2208.01009",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_mmo-champion-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-mmo-champion-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_baseball-fantasysports-yahoo-com | 2022-08-04T19:37:41.000Z | null | false | ccd340079cf7705fabed9a460fdff394abac01bd | [] | [
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_baseball-fantasysports-yahoo-com/resolve/main/README.md | ---
annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-baseball-fantasysports-yahoo-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classi... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_phonearena-com | 2022-08-04T20:11:00.000Z | null | false | f4f1dcb833270d8e0319a2a86cfa3805fb3e4081 | [] | [
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"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_phonearena-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-phonearena-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2te... |
djagatiya | null | null | null | false | 3 | false | djagatiya/ner-ontonotes-v5-eng-v4 | 2022-07-03T11:36:33.000Z | null | false | 944fe3f43c298ca526eeb51927210795ab4721a0 | [] | [
"language:eng",
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"source_datasets:subset"
] | https://huggingface.co/datasets/djagatiya/ner-ontonotes-v5-eng-v4/resolve/main/README.md | ---
language:
- eng
task_categories:
- token-classification
task_ids:
- named-entity-recognition
source_datasets:
- subset
---
# (NER) ontonotes-v5-eng-v4
This dataset is subset of [conll2012_ontonotesv5](https://huggingface.co/datasets/conll2012_ontonotesv5) original dataset.
- Language: english
- Version: v4
... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_support-google-com | 2022-08-04T20:15:33.000Z | null | false | 0b76fc0ecb5ea9fe99a5d5be9812716664061013 | [] | [
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annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-support-google-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
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- zero-shot-classification
- tex... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_dividend-com | 2022-08-04T20:04:10.000Z | null | false | a74dbc1675b4a257fa3312c56efdc297cdc2361f | [] | [
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_dividend-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-dividend-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_bulbapedia-bulbagarden-net | 2022-08-04T19:40:16.000Z | null | false | 121fb00f1583e20e3457e130c80e05a68c3c7f39 | [] | [
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"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_bulbapedia-bulbagarden-net/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
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pretty_name: UnpredicTable-bulbapedia-bulbagarden-net
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classificati... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_wkdu-org | 2022-08-04T20:18:48.000Z | null | false | f05478ec2e00f9b85c0076a44b771504dffaa14f | [] | [
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_wkdu-org/resolve/main/README.md | ---
annotations_creators:
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language_creators:
- found
language:
- en
license:
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multilinguality:
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pretty_name: UnpredicTable-wkdu-org
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-gen... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_dummies-com | 2022-08-04T20:04:46.000Z | null | false | 36db98c5f36305fb63229fd88b9c1f50bca7b140 | [] | [
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annotations_creators:
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language_creators:
- found
language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-dummies-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_mgoblog-com | 2022-08-04T20:09:03.000Z | null | false | 13f3febb67413609d9cb25545f3587fa2ca5604d | [] | [
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"task_categories:multiple-choice",
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_mgoblog-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: AdapTable-mgoblog-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-gene... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_gamefaqs-com | 2022-08-04T20:08:30.000Z | null | false | 91c25524931b0f421ab607c20c1a7bc6199be922 | [] | [
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"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_gamefaqs-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-gamefaqs-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_studystack-com | 2022-08-04T20:15:01.000Z | null | false | 832c7304a9b4dbd1c3f7a436d5e644c78084962d | [] | [
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annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-studystack-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2te... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_sittercity-com | 2022-08-04T20:13:09.000Z | null | false | 2af65195e39bd9839053773b0afb1a330165449c | [] | [
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"task_categories:multiple-choice",
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_sittercity-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
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pretty_name: UnpredicTable-sittercity-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2te... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_msdn-microsoft-com | 2022-08-04T20:10:19.000Z | null | false | 107a673e9688ef4bc63e27884e16e2c741ee494d | [] | [
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annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-msdn-microsoft-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
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- tex... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_cappex-com | 2022-08-04T19:41:09.000Z | null | false | eaf057b4650acaee32eefcc413131ab5e64ff2c4 | [] | [
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annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-cappex.com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
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- zero-shot-classification
- text2text-g... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 1 | false | MicPie/unpredictable_en-wikipedia-org | 2022-08-04T20:05:44.000Z | null | false | 848fe8a39fc1bb84dce9e3a26818376eb810e77d | [] | [
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annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-en-wikipedia-org
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_cram-com | 2022-08-04T20:03:25.000Z | null | false | c295ef60a01bb8a33a8702ddda18308eacba4a31 | [] | [
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"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_cram-com/resolve/main/README.md | ---
annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
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pretty_name: UnpredicTable-cram-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-gen... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 1 | false | MicPie/unpredictable_w3-org | 2022-08-04T20:16:53.000Z | null | false | 13acf265ff28b4809f0e95a5b41a5b96e831cdb4 | [] | [
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"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_w3-org/resolve/main/README.md | ---
annotations_creators:
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language_creators:
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language:
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license:
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multilinguality:
- monolingual
pretty_name: UnpredicTable-w3-org
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-gener... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_sporcle-com | 2022-08-04T20:13:59.000Z | null | false | 7d11a3ddcd818ce988ae8d89e5e997e8eea2c0a1 | [] | [
"arxiv:2208.01009",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_sporcle-com/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-sporcle-com
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 2 | false | MicPie/unpredictable_wiki-openmoko-org | 2022-08-04T20:17:59.000Z | null | false | 00686de27a07cdda04f8fe2bdeafb534e2c8a839 | [] | [
"arxiv:2208.01009",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_wiki-openmoko-org/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-wiki-openmoko-org
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text... |
MicPie | null | @misc{chan2022few,
author = {Chan, Jun Shern and Pieler, Michael and Jao, Jonathan and Scheurer, Jérémy and Perez, Ethan},
title = {Few-shot Adaptation Works with UnpredicTable Data},
publisher={arXiv},
year = {2022},
url = {https://arxiv.org/abs/2208.01009}
} | The UnpredicTable dataset consists of web tables formatted as few-shot tasks for fine-tuning language models to improve their few-shot performance. For more details please see the accompanying dataset card. | false | 1 | false | MicPie/unpredictable_ensembl-org | 2022-08-04T20:06:23.000Z | null | false | a9b29ebafb43b2a8e2f6f3c3253aa0df2e920688 | [] | [
"arxiv:2208.01009",
"annotations_creators:no-annotation",
"language_creators:found",
"language:en",
"license:apache-2.0",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"task_categories:multiple-choice",
"task_categories:question-answering",
"task_categories:zero-shot-classification",... | https://huggingface.co/datasets/MicPie/unpredictable_ensembl-org/resolve/main/README.md | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
license:
- apache-2.0
multilinguality:
- monolingual
pretty_name: UnpredicTable-ensembl-org
size_categories:
- 100K<n<1M
source_datasets: []
task_categories:
- multiple-choice
- question-answering
- zero-shot-classification
- text2text-... |
FIdo-AI | null | null | null | false | 2 | false | FIdo-AI/ua-squad | 2022-07-09T20:55:51.000Z | null | false | 9d9df9f4f8531f0033aa1a9ec78925759ef84c0a | [] | [] | https://huggingface.co/datasets/FIdo-AI/ua-squad/resolve/main/README.md | annotations_creators:
- crowdsourced
language:
- uk
language_creators:
- crowdsourced
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
paperswithcode_id: squad
pretty_name: ''
size_categories:
- 100K<n<1M
source_datasets:
- extended|squad_v2
task_categories:
- question-answering
task_ids:
- open-domain-qa
- extra... |
1989shack | null | null | null | false | 1 | false | 1989shack/1989shack.com | 2022-07-03T15:36:48.000Z | null | false | d6c1735480b71f983a3c1c28cc89e64a5ac34fc2 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/1989shack/1989shack.com/resolve/main/README.md | ---
license: apache-2.0
---
|
tonne | null | null | null | false | 1 | false | tonne/trader | 2022-07-03T17:56:43.000Z | null | false | 9024105e51db311744cc449d11e6b14f583175d3 | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/tonne/trader/resolve/main/README.md | ---
license: apache-2.0
---
|
FJC | null | null | null | false | 1 | false | FJC/corpusELE.csv | 2022-07-06T22:06:44.000Z | null | false | c2dd5ab3983839f23d24c455c115d39634fe2f2c | [] | [] | https://huggingface.co/datasets/FJC/corpusELE.csv/resolve/main/README.md | # Dataset Card for [corpusELE.csv]
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-st... |
mf99 | null | null | null | false | 1 | false | mf99/autotrain-data-sum-200-random | 2022-10-23T06:22:05.000Z | null | false | b76b66326552bd73cd041a6090c8b3eb5f7e3f55 | [] | [
"language:en"
] | https://huggingface.co/datasets/mf99/autotrain-data-sum-200-random/resolve/main/README.md | ---
language:
- en
task_categories:
- conditional-text-generation
---
# AutoTrain Dataset for project: sum-200-random
## Dataset Descritpion
This dataset has been automatically processed by AutoTrain for project sum-200-random.
### Languages
The BCP-47 code for the dataset's language is en.
## Dataset Structure
#... |
santiagxf | null | null | null | false | 1 | false | santiagxf/spanish-marketing-tweets | 2022-07-03T21:49:27.000Z | null | false | 6ade0ffc1c18044e853676892c4933509f1c7f4e | [] | [
"license:unlicense"
] | https://huggingface.co/datasets/santiagxf/spanish-marketing-tweets/resolve/main/README.md | ---
license: unlicense
---
|
fce-m72109 | null | null | null | false | 1 | false | fce-m72109/mascorpus | 2022-07-03T21:51:58.000Z | null | false | 3a15ceec53f10ce3576701cfcce7541f0e667fea | [] | [
"license:unlicense"
] | https://huggingface.co/datasets/fce-m72109/mascorpus/resolve/main/README.md | ---
license: unlicense
---
|
EnZon3 | null | null | null | false | 1 | false | EnZon3/The-Worlds-Sentiment | 2022-07-04T23:08:24.000Z | null | false | 7c23e66a959c1f7198c25fd82111d6c633e8d514 | [] | [] | https://huggingface.co/datasets/EnZon3/The-Worlds-Sentiment/resolve/main/README.md | annotations_creators:
- other
language:
- en
language_creators:
- found
license:
- gpl-3.0
multilinguality:
- monolingual
pretty_name: The World's Sentiment
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
task_ids: []
# Dataset Card for The World's Sentiment
## Table of Contents
- [Da... |
Yincen | null | null | null | false | 218 | false | Yincen/SalienceEvaluation | 2022-07-04T02:36:58.000Z | null | false | dd93e7ba97dd8c0776cb50249b0e1d53e4076b2c | [] | [
"annotations_creators:crowdsourced",
"language:zh",
"language_creators:found",
"license:gpl-3.0",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-input-text-classification"
] | https://huggingface.co/datasets/Yincen/SalienceEvaluation/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language:
- zh
language_creators:
- found
license:
- gpl-3.0
multilinguality:
- monolingual
pretty_name: Yincen/SalienceEvaluation
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-input-text-classification
---
# ... |
holylovenia | null | null | null | false | 1 | false | holylovenia/TITML-IDN | 2022-10-25T06:23:17.000Z | null | false | eb915043fa53039237e47183108b7aaf19b7da9e | [] | [
"annotations_creators:expert-generated",
"language_creators:found",
"language:id",
"license:other",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:automatic-speech-recognition",
"tags:speech-recognition"
] | https://huggingface.co/datasets/holylovenia/TITML-IDN/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- id
license:
- other
multilinguality:
- monolingual
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: 'TITML-IDN: A large vocabulary continuous speech recogn... |
Li-Tang | null | null | null | false | 1 | false | Li-Tang/test_dataset | 2022-07-05T03:52:56.000Z | null | false | b6ecea87dc9076cbdc6138d23499264cb6c7649e | [] | [
"license:apache-2.0"
] | https://huggingface.co/datasets/Li-Tang/test_dataset/resolve/main/README.md | ---
license: apache-2.0
---
|
joheras | null | null | null | false | 1 | false | joheras/prueba | 2022-07-04T09:43:30.000Z | null | false | 4f31650cfbb35f343399d3d11591f139738ce8f3 | [] | [
"license:cc"
] | https://huggingface.co/datasets/joheras/prueba/resolve/main/README.md | ---
license: cc
---
|
joheras | null | null | null | false | 1 | false | joheras/caes | 2022-07-04T10:21:43.000Z | null | false | 95771eb06730cd63c66ed6ecf892a55c06956fef | [] | [
"license:cc"
] | https://huggingface.co/datasets/joheras/caes/resolve/main/README.md | ---
license: cc
---
|
msalnikov | null | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | HuggingFace wrapper for https://github.com/askplatypus/wikidata-simplequestions dataset
Simplequestions dataset based on Wikidata. | false | 1 | false | msalnikov/wikidata_simplequestions | 2022-07-04T12:21:52.000Z | null | false | e1c3445fcff645e27b0253b205b1017b8f2126aa | [] | [] | https://huggingface.co/datasets/msalnikov/wikidata_simplequestions/resolve/main/README.md | # Wikidata Simplequestions
Huggingface Dataset wrapper for Wikidata-simplequestion dataset
```python3
from datasets import load_dataset;
load_dataset('../wikidata_simplequestions', 'answerable_en', cache_dir='/YOUR_PATH_TO_CACHE/')
```
|
CShorten | null | null | null | false | 1 | false | CShorten/ArXiv-ML-Abstract-Embeddings | 2022-07-04T13:13:37.000Z | null | false | ee6ef3917f0210c08e7337f318b99b48c4c4c4c0 | [] | [] | https://huggingface.co/datasets/CShorten/ArXiv-ML-Abstract-Embeddings/resolve/main/README.md | This dataset contains embeddings of the abstracts of ArXiv Machine Learning papers.
The embeddings are produced from sentence-transformers/paraphrase-MiniLM-L6-v2. The model can be accessed here: <a href = "https://huggingface.co/sentence-transformers/paraphrase-MiniLM-L6-v2/discussions/2">HuggingFace Sentence Transfo... |
CShorten | null | null | null | false | 1 | false | CShorten/ArXiv-ML-Title-Embeddings | 2022-07-04T13:44:15.000Z | null | false | 7c2cd16a06fdbd304e68d85877485fde46e97312 | [] | [] | https://huggingface.co/datasets/CShorten/ArXiv-ML-Title-Embeddings/resolve/main/README.md | This dataset contains embeddings of the titles of ArXiv Machine Learning papers.
The embeddings are produced from sentence-transformers/paraphrase-MiniLM-L6-v2. The model can be accessed here: HuggingFace Sentence Transformers
The original dataset before embedding can be accessed here: ML ArXiv Papers |
mounikaiiith | null | null | null | false | 1 | false | mounikaiiith/Telugu_Clickbait | 2022-07-04T14:59:27.000Z | null | false | df94aa548fa4f93e16c6c269a99f0bd746a2ed1f | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/mounikaiiith/Telugu_Clickbait/resolve/main/README.md | ---
license: cc-by-4.0
---
Do cite the below reference for using the dataset:
@inproceedings{marreddy2021clickbait,
title={Clickbait Detection in Telugu: Overcoming NLP Challenges in Resource-Poor Languages using Benchmarked Techniques},
author={Marreddy, Mounika and Oota, Subba Reddy and Vakada, Lakshmi Sireesha ... |
mideind | null | null | null | false | 1 | false | mideind/icelandic-winogrande | 2022-07-04T15:44:19.000Z | null | false | 0a9a45fb300768e0443a1907eea6fa846da5837d | [] | [
"license:cc-by-4.0"
] | https://huggingface.co/datasets/mideind/icelandic-winogrande/resolve/main/README.md | ---
license: cc-by-4.0
---
|
BDas | null | ----Turkish Data---- | The dataset, prepared in Turkish, includes 53.000 tests, 53.000 validations and 160600 train data.
The data is composed of customer comments and created from e-commerce sites. | false | 10 | false | BDas/Turkish-Dataset | 2022-09-16T07:34:57.000Z | null | false | 4d23111fad1b11390bf0ac0124e54c8f125e0dc9 | [] | [
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"language:tr",
"license:other",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:multi-class-classification",
"task_ids:multi-label... | https://huggingface.co/datasets/BDas/Turkish-Dataset/resolve/main/README.md | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- tr
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- multi-class-classification
- multi-label-classification
pretty_nam... |
lyakaap | null | null | null | false | 1 | false | lyakaap/laion-mini-ja | 2022-07-05T02:30:45.000Z | null | false | 8f65fde41b0e3362383eaf9e7f0dbfa53bf5e487 | [] | [] | https://huggingface.co/datasets/lyakaap/laion-mini-ja/resolve/main/README.md | #samples=5007831
```
dataset = load_dataset('lyakaap/laion2B-japanese-subset', split='train')
dataset = dataset.remove_columns(['LANGUAGE', 'NSFW', 'LICENSE', 'SAMPLE_ID'])
dataset = dataset.filter(lambda x: x['HEIGHT'] <= 384 and x['WIDTH'] <= 384)
dataset = dataset.filter(lambda x: x['HEIGHT'] >= 128 and x['WIDTH'] ... |
HTTP404ERROR | null | null | null | false | 1 | false | HTTP404ERROR/huggingface | 2022-07-05T02:42:14.000Z | null | false | 6359aba5ca767bae5c184ebea62c9a0127c9dd7a | [] | [
"license:afl-3.0"
] | https://huggingface.co/datasets/HTTP404ERROR/huggingface/resolve/main/README.md | ---
license: afl-3.0
---
|
Paul | null | null | null | false | 2 | false | Paul/hatecheck-spanish | 2022-07-05T10:27:07.000Z | null | false | a7ea759535bb9fad6361cca151cf94a46e88edf3 | [] | [
"arxiv:2206.09917",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language:es",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:hate-speech-detection"
] | https://huggingface.co/datasets/Paul/hatecheck-spanish/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- es
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Spanish HateCheck
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- hate-speech-detection
---
# Dataset ... |
Paul | null | null | null | false | 21 | false | Paul/hatecheck-portuguese | 2022-07-05T10:27:47.000Z | null | false | 323bdf67e0fbd3d7f8086fad0971b5bd5a62524b | [] | [
"arxiv:2206.09917",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language:pt",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:hate-speech-detection"
] | https://huggingface.co/datasets/Paul/hatecheck-portuguese/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- pt
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Portuguese HateCheck
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- hate-speech-detection
---
# Datas... |
Paul | null | null | null | false | 8 | false | Paul/hatecheck-polish | 2022-07-05T10:26:41.000Z | null | false | 28d7098e2e5a211c4810d0a4d8deccc5889e55b6 | [] | [
"arxiv:2206.09917",
"annotations_creators:crowdsourced",
"language_creators:expert-generated",
"language:pl",
"license:cc-by-4.0",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"task_categories:text-classification",
"task_ids:hate-speech-detection"
] | https://huggingface.co/datasets/Paul/hatecheck-polish/resolve/main/README.md | ---
annotations_creators:
- crowdsourced
language_creators:
- expert-generated
language:
- pl
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Polish HateCheck
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- hate-speech-detection
---
# Dataset C... |
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