id stringlengths 2 115 | lastModified stringlengths 24 24 | tags list | author stringlengths 2 42 ⌀ | description stringlengths 0 6.67k ⌀ | citation stringlengths 0 10.7k ⌀ | likes int64 0 3.66k | downloads int64 0 8.89M | created timestamp[us] | card stringlengths 11 977k | card_len int64 11 977k | embeddings list |
|---|---|---|---|---|---|---|---|---|---|---|---|
sanskrit_classic | 2022-11-03T16:07:56.000Z | [
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"size_categories:100K<n<1M",
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"language:sa",... | null | This dataset combines some of the classical Sanskrit texts. | @Misc{johnsonetal2014,
author = {Johnson, Kyle P. and Patrick Burns and John Stewart and Todd Cook},
title = {CLTK: The Classical Language Toolkit},
url = {https://github.com/cltk/cltk},
year = {2014--2020},
} | 2 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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- found
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- sa
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paperswithcode_id: null
pre... | 3,487 | [
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sede | 2022-11-18T21:44:41.000Z | [
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"language:en",
"license:apache-2.0",
"arxiv:2106.05006",
"arxiv:2005.02539",
"re... | null | SEDE (Stack Exchange Data Explorer) is new dataset for Text-to-SQL tasks with more than 12,000 SQL queries and their
natural language description. It's based on a real usage of users from the Stack Exchange Data Explorer platform,
which brings complexities and challenges never seen before in any other semantic parsing ... | @misc{hazoom2021texttosql,
title={Text-to-SQL in the Wild: A Naturally-Occurring Dataset Based on Stack Exchange Data},
author={Moshe Hazoom and Vibhor Malik and Ben Bogin},
year={2021},
eprint={2106.05006},
archivePrefix={arXiv},
primaryClass={cs.CL}
} | 3 | 85 | 2022-03-02T23:29:22 | ---
pretty_name: SEDE (Stack Exchange Data Explorer)
annotations_creators:
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- found
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- en
license:
- apache-2.0
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paperswithcode_id: sede
size_categories:
- 10K<n<100K
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- original
task_categories:
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- ... | 8,620 | [
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sesotho_ner_corpus | 2023-01-25T14:44:09.000Z | [
"task_categories:token-classification",
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"multilinguality:monolingual",
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"language:st",
"license:other",
"region:us"
] | null | Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags. | @inproceedings{sesotho_ner_corpus,
author = {M. Setaka and
Roald Eiselen},
title = {NCHLT Sesotho Named Entity Annotated Corpus},
booktitle = {Eiselen, R. 2016. Government domain named entity recognition for South African languages. Proceedings of the 10th Language Resource and Evaluat... | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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pretty_name: Sesotho NER Corpus
license_details: Cre... | 5,542 | [
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setswana_ner_corpus | 2023-01-25T14:44:12.000Z | [
"task_categories:token-classification",
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"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:tn",
"license:other",
"region:us"
] | null | Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags. | @inproceedings{sepedi_ner_corpus,
author = {S.S.B.M. Phakedi and
Roald Eiselen},
title = {NCHLT Setswana Named Entity Annotated Corpus},
booktitle = {Eiselen, R. 2016. Government domain named entity recognition for South African languages. Proceedings of the 10th Language Resource and Ev... | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
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- found
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- tn
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- other
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pretty_name: Setswana NER Corpus
license_details: Cr... | 5,552 | [
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siswati_ner_corpus | 2023-01-25T14:44:23.000Z | [
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"language:ss",
"license:other",
"region:us"
] | null | Named entity annotated data from the NCHLT Text Resource Development: Phase II Project, annotated with PERSON, LOCATION, ORGANISATION and MISCELLANEOUS tags. | @inproceedings{siswati_ner_corpus,
author = {B.B. Malangwane and
M.N. Kekana and
S.S. Sedibe and
B.C. Ndhlovu and
Roald Eiselen},
title = {NCHLT Siswati Named Entity Annotated Corpus},
booktitle = {Eiselen, R. 2016. Government domain named entity r... | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
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- found
language:
- ss
license:
- other
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- monolingual
size_categories:
- 10K<n<100K
source_datasets:
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task_categories:
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task_ids:
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pretty_name: Siswati NER Corpus
license_details: C... | 5,632 | [
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smartdata | 2023-01-25T14:44:26.000Z | [
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"size_categories:1K<n<10K",
"source_datasets:original",
"language:de",
"license:cc-by-4.0",
"region:us"
] | null | DFKI SmartData Corpus is a dataset of 2598 German-language documents
which has been annotated with fine-grained geo-entities, such as streets,
stops and routes, as well as standard named entity types. It has also
been annotated with a set of 15 traffic- and industry-related n-ary
relations and events, such as Accidents... | @InProceedings{SCHIERSCH18.85,
author = {Martin Schiersch and Veselina Mironova and Maximilian Schmitt and Philippe Thomas and Aleksandra Gabryszak and Leonhard Hennig},
title = "{A German Corpus for Fine-Grained Named Entity Recognition and Relation Extraction of Traffic and Industry Events}",
booktitle = {Proce... | 1 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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- cc-by-4.0
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size_categories:
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task_categories:
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pretty_name: SmartData
dataset_info:
features:... | 5,978 | [
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ttc4900 | 2023-01-25T14:54:33.000Z | [
"task_categories:text-classification",
"annotations_creators:found",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:tr",
"license:unknown",
"news-category-classification",
"region:us"
] | null | The data set is taken from kemik group
http://www.kemik.yildiz.edu.tr/
The data are pre-processed for the text categorization, collocations are found, character set is corrected, and so forth.
We named TTC4900 by mimicking the name convention of TTC 3600 dataset shared by the study http://journals.sagepub.com/doi/abs/1... | @article{doi:10.5505/pajes.2018.15931,
author = {Yıldırım, Savaş and Yıldız, Tuğba},
title = {A comparative analysis of text classification for Turkish language},
journal = {Pamukkale Univ Muh Bilim Derg},
volume = {24},
number = {5},
pages = {879-886},
year = {2018},
doi = {10.5505/pajes.2018.15931},
note ={doi: 10.55... | 2 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
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- tr
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size_categories:
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task_categories:
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task_ids: []
pretty_name: TTC4900 - A Benchmark Data for Turkish Text Categorization
tags:
- news-c... | 6,494 | [
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Annabelleabbott/real-fake-news-workshop | 2022-01-07T00:45:18.000Z | [
"region:us"
] | Annabelleabbott | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ApiInferenceTest/asr_dummy | 2022-02-14T11:18:56.000Z | [
"region:us"
] | ApiInferenceTest | Self-supervised learning (SSL) has proven vital for advancing research in
natural language processing (NLP) and computer vision (CV). The paradigm
pretrains a shared model on large volumes of unlabeled data and achieves
state-of-the-art (SOTA) for various tasks with minimal adaptation. However, the
speech processing co... | @article{DBLP:journals/corr/abs-2105-01051,
author = {Shu{-}Wen Yang and
Po{-}Han Chi and
Yung{-}Sung Chuang and
Cheng{-}I Jeff Lai and
Kushal Lakhotia and
Yist Y. Lin and
Andy T. Liu and
Jiatong Shi and
... | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Check/region_9 | 2021-09-04T11:09:23.000Z | [
"region:us"
] | Check | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Crives/haha | 2022-02-22T09:40:35.000Z | [
"region:us"
] | Crives | null | null | 1 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DSCI511G1/COP26_Energy_Transition_Tweets | 2021-12-06T17:53:41.000Z | [
"region:us"
] | DSCI511G1 | null | null | 2 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Doohae/modern_music_re | 2021-12-06T05:58:20.000Z | [
"region:us"
] | Doohae | null | null | 0 | 85 | 2022-03-02T23:29:22 | Datasets for Relation Extraction Task
Source from Wikipedia (CC-BY-2.0)
Contributors : Doohae Jung, Hyesu Kim, Bosung Kim, Isaac Park, Miwon Jeon, Dagon Lee, Jihoo Kim | 173 | [
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DrishtiSharma/mr_opus100_processed | 2022-02-09T14:28:39.000Z | [
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Dumiiii/common-voice-romaniarss | 2022-01-11T11:29:09.000Z | [
"region:us"
] | Dumiiii | null | null | 0 | 85 | 2022-03-02T23:29:22 | This datasets consists in the last version of the common-voice-dataset for romanian language.
Also contains data from RSS (Romanian Speech Synthesis Dataset) from this site http://romaniantts.com/ | 197 | [
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Fraser/mnist-text-no-spaces | 2021-02-05T16:03:35.000Z | [
"region:us"
] | Fraser | MNIST dataset adapted to a text-based representation.
This allows testing interpolation quality for Transformer-VAEs.
System is heavily inspired by Matthew Rayfield's work https://youtu.be/Z9K3cwSL6uM
Works by quantising each MNIST pixel into one of 64 characters.
Every sample has an up & down version to encourage t... | @dataset{dataset,
author = {Fraser Greenlee},
year = {2021},
month = {2},
pages = {},
title = {MNIST text dataset (no spaces).},
doi = {}
} | 1 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Fraser/python-lines | 2021-02-22T10:20:34.000Z | [
"region:us"
] | Fraser | Dataset of single lines of Python code taken from the [CodeSearchNet](https://github.com/github/CodeSearchNet) dataset.
Context
This dataset allows checking the validity of Variational-Autoencoder latent spaces by testing what percentage of random/intermediate latent points can be greedily decoded into valid Python c... | @dataset{dataset,
author = {Fraser Greenlee},
year = {2020},
month = {12},
pages = {},
title = {Python single line dataset.},
doi = {}
} | 1 | 85 | 2022-03-02T23:29:22 | Dataset of single lines of Python code taken from the [CodeSearchNet](https://github.com/github/CodeSearchNet) dataset.
Context
This dataset allows checking the validity of Variational-Autoencoder latent spaces by testing what percentage of random/intermediate latent points can be greedily decoded into valid Python c... | 561 | [
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Fraser/wiki_sentences | 2021-07-21T07:43:08.000Z | [
"region:us"
] | Fraser | null | null | 0 | 85 | 2022-03-02T23:29:22 | # Wiki Sentences
A dataset of all english sentences in Wikipedia.
Taken from the OPTIMUS project. https://github.com/ChunyuanLI/Optimus/blob/master/download_datasets.md
The dataset is 11.8GB so best to load it using streaming:
```python
from datasets import load_dataset
dataset = load_dataset("Fraser/wiki_sentences... | 358 | [
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GEM/Taskmaster | 2022-10-24T15:30:09.000Z | [
"task_categories:conversational",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"dialog-response-generation",
"arxiv:2012.12458",
"region:us"
] | GEM | The Taskmaster-3 (aka TicketTalk) dataset consists of 23,789 movie ticketing dialogs
(located in Taskmaster/TM-3-2020/data/). By "movie ticketing" we mean conversations
where the customer's goal is to purchase tickets after deciding on theater, time,
movie name, number of tickets, and date, or opt out of the transactio... | @article{byrne2020tickettalk,
title={TicketTalk: Toward human-level performance with end-to-end, transaction-based dialog systems},
author={Byrne, Bill and Krishnamoorthi, Karthik and Ganesh, Saravanan and Kale, Mihir Sanjay},
journal={arXiv preprint arXiv:2012.12458},
year={2020}
} | 1 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- cc-by-4.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: Taskmaster
tags:
- dialog-response-generation
---
# Dataset Card for GEM/Taskma... | 17,520 | [
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GEM/dstc10_track2_task2 | 2022-10-24T15:30:17.000Z | [
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"language:en",
"license:apache-2.0",
"dialog-response-generation",
"region:us"
] | GEM | \ | @article{kim2020domain,
title={Beyond Domain APIs: Task-oriented Conversational Modeling with Unstructured Knowledge Access},
author={Seokhwan Kim and Mihail Eric and Karthik Gopalakrishnan and Behnam Hedayatnia and Yang Liu and Dilek Hakkani-Tur},
journal={arXiv preprint arXiv:2006.03533}
year={2020}
} | 4 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- en
license:
- apache-2.0
multilinguality:
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task_ids: []
pretty_name: dstc10_track2_task2
tags:
- dialog-response-generation
---
# Dataset Card for ... | 23,017 | [
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Intel/WEC-Eng | 2021-10-04T11:21:48.000Z | [
"region:us"
] | Intel | null | null | 0 | 85 | 2022-03-02T23:29:22 | # WEC-Eng
A large-scale dataset for cross-document event coreference extracted from English Wikipedia. </br>
- **Repository (Code for generating WEC):** https://github.com/AlonEirew/extract-wec
- **Paper:** https://aclanthology.org/2021.naacl-main.198/
### Languages
English
## Load Dataset
You can read in WEC-Eng f... | 5,118 | [
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Karavet/ILUR-news-text-classification-corpus | 2022-10-21T16:06:12.000Z | [
"task_categories:text-classification",
"multilinguality:monolingual",
"language:hy",
"license:apache-2.0",
"region:us"
] | Karavet | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
language:
- hy
task_categories: [news-classification, text-classification]
multilinguality: [monolingual]
task_ids: [news-classification, text-classification]
license:
- apache-2.0
---
## Table of Contents
- [Table of Contents](#table-of-contents)
- [News Texts Dataset](#news-texts-dataset)
## News Texts Dataset
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Mulin/my_third_dataset | 2021-09-19T01:36:15.000Z | [
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- for wolf classification | 42 | [
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"region:us"
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NbAiLab/NPSC_test | 2022-11-07T12:37:31.000Z | [
"task_categories:automatic-speech-recognition",
"task_categories:audio-classification",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:2G<n<1B",
"source_datasets:original",
"language:nb",
"language:no",
"language:nn",
"license:cc0... | NbAiLab | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- nb
- 'no'
- nn
license:
- cc0-1.0
multilinguality:
- monolingual
size_categories:
- 2G<n<1B
source_datasets:
- original
task_categories:
- automatic-speech-recognition
- audio-classification
task_ids:
- speech-modeling
pretty_name: NPSC
ta... | 6,338 | [
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PaulLerner/triviaqa_for_viquae | 2022-08-02T08:24:26.000Z | [
"region:us"
] | PaulLerner | null | null | 0 | 85 | 2022-03-02T23:29:22 | See https://github.com/PaulLerner/ViQuAE
Get the original dataset there: http://nlp.cs.washington.edu/triviaqa/ (or via HF: https://huggingface.co/datasets/trivia_qa) | 166 | [
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Recognai/ag_news_corrected_labels | 2021-12-29T17:00:24.000Z | [
"region:us"
] | Recognai | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Recognai/corrected_labels_ag_news | 2021-12-29T16:57:56.000Z | [
"region:us"
] | Recognai | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Recognai/veganuary | 2022-02-04T10:07:21.000Z | [
"region:us"
] | Recognai | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
Sabokou/qg_squad_modified_dev | 2021-12-30T10:35:48.000Z | [
"region:us"
] | Sabokou | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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SaulLu/toy_struc_dataset | 2021-09-22T12:26:40.000Z | [
"region:us"
] | SaulLu | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
Tahsin-Mayeesha/Bengali-SQuAD | 2022-10-25T09:06:50.000Z | [
"task_categories:question-answering",
"multilinguality:monolingual",
"language:bn",
"region:us"
] | Tahsin-Mayeesha | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
language:
- bn
multilinguality:
- monolingual
task_categories:
- question-answering
---
# Overview
This dataset contains the data for the paper [Deep learning based question answering system in Bengali](https://www.tandfonline.com/doi/full/10.1080/24751839.2020.1833136). It is a translated version of [SQuAD 2.0](h... | 442 | [
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Zoe10/ner_dataset | 2021-12-14T11:13:54.000Z | [
"region:us"
] | Zoe10 | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
abidlabs/crowdsourced-speech-demo | 2022-04-28T08:13:52.000Z | [
"region:us"
] | abidlabs | null | null | 1 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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abidlabs/crowdsourced-speech2 | 2022-01-21T15:44:22.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
abidlabs/crowdsourced-speech5 | 2022-01-21T16:38:34.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
abidlabs/crowdsourced-speech7 | 2022-01-21T17:21:47.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
abidlabs/test-audio-1 | 2022-01-19T16:26:19.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
abidlabs/test-audio-13 | 2022-01-21T16:42:41.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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abidlabs/test-image-13 | 2022-01-19T19:33:09.000Z | [
"region:us"
] | abidlabs | null | null | 1 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
abidlabs/test-image-classifier-dataset | 2021-12-23T19:41:31.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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addy88/sanskrit-asr-84 | 2021-12-14T13:39:37.000Z | [
"region:us"
] | addy88 | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
akumar33/manufacturing | 2021-10-14T04:51:48.000Z | [
"region:us"
] | akumar33 | null | null | 1 | 85 | 2022-03-02T23:29:22 | This dataset is associated with FabNER paper. https://link.springer.com/article/10.1007/s10845-021-01807-x
Kindly cite if you use it. | 133 | [
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alperbayram/Tweet_Siniflandirma | 2022-10-25T10:02:12.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"size_categories:unknown",
"language:tr",
"region:us"
] | alperbayram | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
- expert-generated
language_creators:
- crowdsourced
language:
- tr
size_categories:
- unknown
source_datasets: []
task_categories:
- text-classification
task_ids:
- sentiment-classification
pretty_name: Turkish Sentiment Dataset
---
# References
- [alper bayram](https://github... | 339 | [
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bhavnicksm/sentihood | 2022-10-25T09:07:23.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:multi-class-classification",
"task_ids:natural-language-inference",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc-by-4.0",
"arxiv:1610.03771",
... | bhavnicksm | null | null | 3 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators: []
language_creators: []
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: SentiHood Dataset
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- text-classification
task_ids:
- sentiment-classification
- multi-class-classification
- natural... | 4,085 | [
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castorini/msmarco_v1_doc_segmented_doc2query-t5_expansions | 2021-11-10T04:51:35.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides queries generated for the MS MARCO V1 document segmented corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea i... | 1,749 | [
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chenghao/scielo_books | 2022-07-01T18:34:59.000Z | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:multilingual",
"size_categories:n<1K",
"source_datasets:original",
"language:en",
"language:pt",
"language:es",
"license:cc-by-nc-sa-3.0",
"region:us"
] | chenghao | null | null | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- en
- pt
- es
license:
- cc-by-nc-sa-3.0
multilinguality:
- multilingual
paperswithcode_id: null
size_categories:
- n<1K
source_datasets:
- original
task_categories:
- sequence-modeling
task_ids:
- language-modeling
---
## Dataset Descrip... | 3,824 | [
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dataset/wikipedia_bn | 2021-06-04T16:22:44.000Z | [
"region:us"
] | dataset | Bengali Wikipedia from the dump of 03/20/2021.
The data was processed using the huggingface datasets wikipedia script early april 2021.
The dataset was built from the Wikipedia dump (https://dumps.wikimedia.org/).
Each example contains the content of one full Wikipedia article with cleaning to strip
markdown and unwant... | @ONLINE {wikidump,
author = {Wikimedia Foundation},
title = {Wikimedia Downloads},
url = {https://dumps.wikimedia.org}
} | 1 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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davanstrien/beyond_test | 2022-02-20T14:20:55.000Z | [
"region:us"
] | davanstrien | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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davanstrien/embellishments | 2022-01-10T16:59:02.000Z | [
"region:us"
] | davanstrien | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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davanstrien/test_iiif | 2022-01-08T14:52:27.000Z | [
"region:us"
] | davanstrien | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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davanstrien/testpush | 2022-01-05T20:30:22.000Z | [
"region:us"
] | davanstrien | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.014984130859375,
-0.060455322265625,
0.03793334... |
dvilasuero/test-dataset | 2021-12-29T14:53:03.000Z | [
"region:us"
] | dvilasuero | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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flxclxc/encoded_drug_reviews | 2022-02-04T14:25:31.000Z | [
"region:us"
] | flxclxc | null | null | 3 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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gcaillaut/pubmed | 2021-10-21T15:39:47.000Z | [
"region:us"
] | gcaillaut | The Pubmed Diabetes dataset consists of 19717 scientific publications from PubMed database pertaining to diabetes classified into one of three classes. The citation network consists of 44338 links. Each publication in the dataset is described by a TF/IDF weighted word vector from a dictionary which consists of 500 uniq... | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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gfigueroa/wikitext_processed | 2022-01-19T18:16:40.000Z | [
"region:us"
] | gfigueroa | null | null | 0 | 85 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DDSC/dagw_reddit_filtered_v1.0.0 | 2022-11-06T15:30:56.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:DDSC/partial-danish-gigaword-no-twitter",
"source_datasets:DDSC/reddit-da",
"language:da... | DDSC | null | null | 1 | 85 | 2022-05-11T13:46:39 | ---
annotations_creators:
- no-annotation
language_creators:
- crowdsourced
language:
- da
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- DDSC/partial-danish-gigaword-no-twitter
- DDSC/reddit-da
task_categories:
- text-generation
task_ids:
- language-modeling
pretty_na... | 5,056 | [
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WorkInTheDark/FairytaleQA | 2023-08-22T18:49:30.000Z | [
"task_categories:question-answering",
"task_categories:text-generation",
"language:en",
"license:apache-2.0",
"education",
"children education",
"region:us"
] | WorkInTheDark | FairytaleQA dataset, an open-source dataset focusing on comprehension of narratives, targeting students from kindergarten to eighth grade. The FairytaleQA dataset is annotated by education experts based on an evidence-based theoretical framework. It consists of 10,580 explicit and implicit questions derived from 278 ch... | @inproceedings{xu-etal-2022-fantastic,
title = "Fantastic Questions and Where to Find Them: {F}airytale{QA} {--} An Authentic Dataset for Narrative Comprehension",
author = "Xu, Ying and
Wang, Dakuo and
Yu, Mo and
Ritchie, Daniel and
Yao, Bingsheng and
Wu, Tongshuang and
... | 1 | 85 | 2022-05-18T19:11:00 | ---
license: apache-2.0
task_categories:
- question-answering
- text-generation
language:
- en
tags:
- education
- children education
---
# Dataset Card for FairytaleQA
## Dataset Description
- **Homepage:**
- **Repository:**
https://github.com/uci-soe/FairytaleQAData
https://github.com/WorkInTheDark/FairytaleQA_... | 4,225 | [
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GroNLP/divemt | 2023-02-10T11:04:33.000Z | [
"task_categories:translation",
"annotations_creators:machine-generated",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:it",
"language:vi",
"language:nl",
"langu... | GroNLP | DivEMT is the first publicly available post-editing study of Neural Machine Translation (NMT) over a typologically diverse set of target languages. Using a strictly controlled setup, 18 professional translators were instructed to translate or post-edit the same set of English documents into Arabic, Dutch, Italian, Turk... | @inproceedings{sarti-etal-2022-divemt,
title = "{D}iv{EMT}: Neural Machine Translation Post-Editing Effort Across Typologically Diverse Languages",
author = "Sarti, Gabriele and Bisazza, Arianna and Guerberof Arenas, Ana and Toral, Antonio",
booktitle = "Proceedings of the 2022 Conference on Empirical Metho... | 2 | 85 | 2022-05-23T19:56:55 | ---
annotations_creators:
- machine-generated
- expert-generated
language_creators:
- found
language:
- en
- it
- vi
- nl
- uk
- tr
- ar
license:
- gpl-3.0
multilinguality:
- translation
pretty_name: divemt
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
---
# Dataset Card for Di... | 14,687 | [
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yhavinga/xsum_dutch | 2022-08-21T20:50:08.000Z | [
"task_categories:summarization",
"task_ids:news-articles-summarization",
"language:nl",
"region:us"
] | yhavinga | Extreme Summarization (XSum) Dataset.
There are three features:
- document: Input news article.
- summary: One sentence summary of the article.
- id: BBC ID of the article. | @article{Narayan2018DontGM,
title={Don't Give Me the Details, Just the Summary! Topic-Aware Convolutional Neural Networks for Extreme Summarization},
author={Shashi Narayan and Shay B. Cohen and Mirella Lapata},
journal={ArXiv},
year={2018},
volume={abs/1808.08745}
} | 0 | 85 | 2022-08-21T20:29:43 | ---
pretty_name: Extreme Summarization (XSum) in Dutch
language:
- nl
paperswithcode_id: xsum_dutch
task_categories:
- summarization
task_ids:
- news-articles-summarization
train-eval-index:
- config: default
task: summarization
task_id: summarization
splits:
train_split: train
eval_split: test
col_mapp... | 6,530 | [
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proteinea/deeploc | 2023-01-16T14:59:58.000Z | [
"doi:10.57967/hf/1105",
"region:us"
] | proteinea | null | null | 0 | 85 | 2022-12-12T15:48:32 | Entry not found | 15 | [
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proteinea/remote_homology | 2022-12-12T16:20:18.000Z | [
"doi:10.57967/hf/1107",
"region:us"
] | proteinea | null | null | 2 | 85 | 2022-12-12T15:55:43 | Entry not found | 15 | [
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irds/trec-robust04 | 2023-01-05T03:52:55.000Z | [
"task_categories:text-retrieval",
"region:us"
] | irds | null | null | 1 | 85 | 2023-01-05T03:52:49 | ---
pretty_name: '`trec-robust04`'
viewer: false
source_datasets: []
task_categories:
- text-retrieval
---
# Dataset Card for `trec-robust04`
The `trec-robust04` dataset, provided by the [ir-datasets](https://ir-datasets.com/) package.
For more information about the dataset, see the [documentation](https://ir-dataset... | 1,844 | [
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Francesco/axial-mri | 2023-03-30T09:39:28.000Z | [
"task_categories:object-detection",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:cc",
"rf100",
"region:us"
] | Francesco | null | null | 0 | 85 | 2023-03-30T09:39:10 | ---
dataset_info:
features:
- name: image_id
dtype: int64
- name: image
dtype: image
- name: width
dtype: int32
- name: height
dtype: int32
- name: objects
sequence:
- name: id
dtype: int64
- name: area
dtype: int64
- name: bbox
sequence: float32
lengt... | 3,337 | [
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0.0294036... |
MU-NLPC/Calc-ape210k | 2023-10-30T15:56:39.000Z | [
"license:mit",
"arxiv:2305.15017",
"arxiv:2009.11506",
"region:us"
] | MU-NLPC | null | null | 10 | 85 | 2023-05-22T14:20:16 | ---
license: mit
dataset_info:
- config_name: default
features:
- name: id
dtype: string
- name: question
dtype: string
- name: question_chinese
dtype: string
- name: chain
dtype: string
- name: result
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- name: result_float
dtype: float64
- name: equation
dtype: ... | 6,194 | [
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0.... |
dmayhem93/agieval-aqua-rat | 2023-06-18T17:14:34.000Z | [
"license:apache-2.0",
"arxiv:2304.06364",
"region:us"
] | dmayhem93 | null | null | 0 | 85 | 2023-06-18T03:50:28 | ---
dataset_info:
features:
- name: query
dtype: string
- name: choices
sequence: string
- name: gold
sequence: int64
splits:
- name: test
num_bytes: 93696
num_examples: 254
download_size: 0
dataset_size: 93696
license: apache-2.0
---
# Dataset Card for "agieval-aqua-rat"
Dataset ta... | 2,880 | [
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dmayhem93/agieval-lsat-rc | 2023-06-18T17:27:15.000Z | [
"license:mit",
"arxiv:2304.06364",
"arxiv:2104.06598",
"region:us"
] | dmayhem93 | null | null | 0 | 85 | 2023-06-18T12:50:49 | ---
dataset_info:
features:
- name: query
dtype: string
- name: choices
sequence: string
- name: gold
sequence: int64
splits:
- name: test
num_bytes: 1136305
num_examples: 269
download_size: 322710
dataset_size: 1136305
license: mit
---
# Dataset Card for "agieval-lsat-rc"
Dataset t... | 2,550 | [
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dmayhem93/agieval-sat-en | 2023-06-18T17:30:59.000Z | [
"license:mit",
"arxiv:2304.06364",
"region:us"
] | dmayhem93 | null | null | 2 | 85 | 2023-06-18T12:50:59 | ---
dataset_info:
features:
- name: query
dtype: string
- name: choices
sequence: string
- name: gold
sequence: int64
splits:
- name: test
num_bytes: 1019350
num_examples: 206
download_size: 265465
dataset_size: 1019350
license: mit
---
# Dataset Card for "agieval-sat-en"
Dataset t... | 1,833 | [
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dmayhem93/agieval-sat-en-without-passage | 2023-06-18T17:31:43.000Z | [
"license:mit",
"arxiv:2304.06364",
"region:us"
] | dmayhem93 | null | null | 0 | 85 | 2023-06-18T12:51:12 | ---
dataset_info:
features:
- name: query
dtype: string
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sequence: string
- name: gold
sequence: int64
splits:
- name: test
num_bytes: 154762
num_examples: 206
download_size: 85136
dataset_size: 154762
license: mit
---
# Dataset Card for "agieval-sat-en-without-passage... | 1,846 | [
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benjamin/compoundpiece | 2023-07-24T17:03:10.000Z | [
"license:mit",
"arxiv:2305.14214",
"region:us"
] | benjamin | null | null | 1 | 85 | 2023-07-23T13:50:23 | ---
configs:
- config_name: wiktionary
data_files:
- split: train
path: "wiktionary/train.csv"
- split: validation
path: "wiktionary/valid.csv"
- config_name: web
data_files:
- split: train
path: "web/train.csv"
- split: validation
path: "web/valid.csv"
license: mit
---
# Co... | 1,117 | [
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0.02... |
tanganke/EuroSAT | 2023-08-01T08:09:39.000Z | [
"task_categories:image-classification",
"region:us"
] | tanganke | null | null | 0 | 85 | 2023-08-01T07:29:45 | ---
task_categories:
- image-classification
---
# EuroSAT
EuroSAT: Downloaded from https://github.com/phelber/EuroSAT (direct link: https://madm.dfki.de/files/sentinel/EuroSAT.zip).
For this dataset we randomly split the downloaded data into train/validation/test (21,600/2,700/2,700 samples). | 295 | [
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doanhieung/vi-stsbenchmark | 2023-08-28T01:26:09.000Z | [
"license:mit",
"region:us"
] | doanhieung | null | null | 2 | 85 | 2023-08-28T01:25:05 | ---
license: mit
---
The STSbenchmark dataset for Vietnamese | 60 | [
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yzhuang/autotree_automl_10000_credit_sgosdt_l256_dim10_d3_sd0 | 2023-09-07T02:24:10.000Z | [
"region:us"
] | yzhuang | null | null | 0 | 85 | 2023-09-07T02:24:03 | ---
dataset_info:
features:
- name: id
dtype: int64
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sequence:
sequence: float32
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sequence:
sequence: float32
- name: input_y_clean
sequence:
sequence: float32
- name: rtg
sequence: float64
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sequence: flo... | 844 | [
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ai4bharat/IN22-Conv | 2023-09-12T11:11:17.000Z | [
"task_categories:translation",
"language_creators:expert-generated",
"multilinguality:multilingual",
"multilinguality:translation",
"size_categories:1K<n<10K",
"language:as",
"language:bn",
"language:brx",
"language:doi",
"language:en",
"language:gom",
"language:gu",
"language:hi",
"langua... | ai4bharat | IN-22 is a newly created comprehensive benchmark for evaluating machine translation performance in multi-domain, n-way parallel contexts across 22 Indic languages.
IN22-Conv is the conversation domain subset of IN22. It is designed to assess translation quality in typical day-to-day conversational-style applications. ... | @article{ai4bharat2023indictrans2,
title = {IndicTrans2: Towards High-Quality and Accessible Machine Translation Models for all 22 Scheduled Indian Languages},
author = {AI4Bharat and Jay Gala and Pranjal A. Chitale and Raghavan AK and Sumanth Doddapaneni and Varun Gumma and Aswanth Kumar and Janki Nawale and An... | 2 | 85 | 2023-09-09T17:35:58 | ---
language:
- as
- bn
- brx
- doi
- en
- gom
- gu
- hi
- kn
- ks
- mai
- ml
- mr
- mni
- ne
- or
- pa
- sa
- sat
- sd
- ta
- te
- ur
language_details: >-
asm_Beng, ben_Beng, brx_Deva, doi_Deva, eng_Latn, gom_Deva, guj_Gujr,
hin_Deva, kan_Knda, kas_Arab, mai_Deva, mal_Mlym, mar_Deva, mni_Mtei,
npi_Deva, ory_Ory... | 7,627 | [
[
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0.00521087646484375,
0.0221405029296875,
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0.01256561279296875,
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0.01385498046875,
-0.043670654296875,
-0.0445556640625,
-0.040924072265625,
0.0197... |
mapama247/wikihow_es | 2023-09-19T12:48:50.000Z | [
"task_categories:text-classification",
"task_categories:question-answering",
"task_categories:conversational",
"task_categories:summarization",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"language:es",
"license:cc-by-nc-sa-3.0",
"Spanish",
"WikiHow",
"Wiki Articles",
"Tutorials... | mapama247 | null | null | 0 | 85 | 2023-09-18T08:39:33 | ---
pretty_name: WikiHow-ES
license: cc-by-nc-sa-3.0
size_categories: 1K<n<10K
language: es
multilinguality: monolingual
task_categories:
- text-classification
- question-answering
- conversational
- summarization
tags:
- Spanish
- WikiHow
- Wiki Articles
- Tutorials
- Step-By-Step
- Instruction Tuning
---
### Dataset... | 5,544 | [
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0.0279388427734375,
-0.05987548828125,
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-0.033782958984375,
... |
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