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 |
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dalle-mini/wit | 2021-09-14T02:48:56.000Z | [
"region:us"
] | dalle-mini | null | null | 5 | 87 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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damlab/HIV_FLT | 2022-02-08T20:58:56.000Z | [
"region:us"
] | damlab | null | null | 0 | 87 | 2022-03-02T23:29:22 | # Dataset Description
## Dataset Summary
This dataset was derived from the Los Alamos National Laboratory HIV sequence (LANL) database.
It contains the most recent version (2016-Full-genome), composed of 1,609 high-quality full-length genomes.
The genes within these sequences were processed using the GeneCutter ... | 1,616 | [
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davanstrien/19th-century-ads | 2022-01-18T15:15:02.000Z | [
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davanstrien/manuscript_iiif_test | 2022-02-05T11:43:31.000Z | [
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] | davanstrien | null | null | 0 | 87 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DebateLabKIT/deepa2 | 2022-12-16T14:49:35.000Z | [
"task_categories:text-retrieval",
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"language:en",
"license:other",
"argument-mining",
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"conditional-text-ge... | DebateLabKIT | null | null | 3 | 87 | 2022-03-02T23:29:22 | ---
annotations_creators: []
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pretty_name: deepa2
tags:
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... | 6,988 | [
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dragosnicolae555/RoITD | 2022-10-25T09:07:43.000Z | [
"task_categories:question-answering",
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"annotations_creators:crowdsourced",
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"language:ro-RO",
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"region:us"
] | dragosnicolae555 | null | null | 0 | 87 | 2022-03-02T23:29:22 | ---
annotations_creators:
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pretty_name: 'RoITD: Romanian IT Question Answering Dataset'
size_categories:
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task_categories:
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CEBaB/CEBaB | 2022-08-16T21:54:47.000Z | [
"region:us"
] | CEBaB | null | null | 5 | 87 | 2022-05-09T22:51:59 | Entry not found | 15 | [
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tobiolatunji/afrispeech-200 | 2023-05-20T23:29:22.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:expert-generated",
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"size_categories:10K<n<100K",
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"language:en",
"license:cc-by-nc-sa-4.0",
"regio... | tobiolatunji | AFRISPEECH-200 is a 200hr Pan-African speech corpus for clinical and general domain English accented ASR;
a dataset with 120 African accents from 13 countries and 2,463 unique African speakers.
Our goal is to raise awareness for and advance Pan-African English ASR research,
especially for the clinical domain. | TBD | 8 | 87 | 2023-01-30T22:34:30 | ---
pretty_name: AfriSpeech-200
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
- expert-generated
language:
- en
license:
- cc-by-nc-sa-4.0
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da... | 17,874 | [
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Francesco/liver-disease | 2023-03-30T09:11:15.000Z | [
"task_categories:object-detection",
"annotations_creators:crowdsourced",
"language_creators:found",
"multilinguality:monolingual",
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"language:en",
"license:cc",
"rf100",
"region:us"
] | Francesco | null | null | 1 | 87 | 2023-03-30T09:10:00 | ---
dataset_info:
features:
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lengt... | 3,431 | [
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dmayhem93/agieval-lsat-ar | 2023-06-18T17:25:42.000Z | [
"arxiv:2304.06364",
"arxiv:2104.06598",
"region:us"
] | dmayhem93 | null | null | 1 | 87 | 2023-06-18T12:50:26 | ---
dataset_info:
features:
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splits:
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download_size: 66495
dataset_size: 273902
---
# Dataset Card for "agieval-lsat-ar"
Dataset taken from https:... | 2,534 | [
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yzhuang/autotree_automl_10000_bank-marketing_sgosdt_l256_dim7_d3_sd0 | 2023-09-07T02:31:08.000Z | [
"region:us"
] | yzhuang | null | null | 0 | 87 | 2023-09-07T02:31:04 | ---
dataset_info:
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- name: status
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sequence: flo... | 850 | [
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erico25/aminer_title_abstract_v10 | 2023-10-23T20:43:49.000Z | [
"size_categories:1M<n<10M",
"language:en",
"region:us"
] | erico25 | null | null | 0 | 87 | 2023-10-23T19:07:34 | ---
dataset_info:
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language:
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size_categories:
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---
# Dataset Card for "aminer_title_abstract_v10"
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id_newspapers_2018 | 2022-11-03T16:16:15.000Z | [
"task_categories:text-generation",
"task_categories:fill-mask",
"task_ids:language-modeling",
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"language_creators:found",
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"language:id",... | null | The dataset contains around 500K articles (136M of words) from 7 Indonesian newspapers: Detik, Kompas, Tempo,
CNN Indonesia, Sindo, Republika and Poskota. The articles are dated between 1st January 2018 and 20th August 2018
(with few exceptions dated earlier). The size of uncompressed 500K json files (newspapers-json.t... | @inproceedings{id_newspapers_2018,
author = {},
title = {Indonesian Newspapers 2018},
year = {2019},
url = {https://github.com/feryandi/Dataset-Artikel},
} | 4 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
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paperswithcode_id: null... | 7,227 | [
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moroco | 2023-01-25T14:40:41.000Z | [
"task_categories:text-classification",
"task_ids:topic-classification",
"annotations_creators:found",
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"source_datasets:original",
"language:ro",
"license:cc-by-4.0",
"arxiv:1901.06543",
"region:us"
] | null | The MOROCO (Moldavian and Romanian Dialectal Corpus) dataset contains 33564 samples of text collected from the news domain.
The samples belong to one of the following six topics:
- culture
- finance
- politics
- science
- sports
- tech | @inproceedings{ Butnaru-ACL-2019,
author = {Andrei M. Butnaru and Radu Tudor Ionescu},
title = "{MOROCO: The Moldavian and Romanian Dialectal Corpus}",
booktitle = {Proceedings of ACL},
year = {2019},
pages={688--698},
} | 0 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
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- ro
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- cc-by-4.0
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paperswithcode_id: moroco
pretty_name: 'MOROCO: The Moldavian ... | 8,072 | [
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ro_sts | 2022-11-18T21:42:20.000Z | [
"task_categories:text-classification",
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"size_categories:1K<n<10K",
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"language:ro",
"license:... | null | The RO-STS (Romanian Semantic Textual Similarity) dataset contains 8628 pairs of sentences with their similarity score. It is a high-quality translation of the STS benchmark dataset. | @inproceedings{dumitrescu2021liro,
title={Liro: Benchmark and leaderboard for romanian language tasks},
author={Dumitrescu, Stefan Daniel and Rebeja, Petru and Lorincz, Beata and Gaman, Mihaela and Avram, Andrei and Ilie, Mihai and Pruteanu, Andrei and Stan, Adriana and Rosia, Lorena and Iacobescu, Cristina and oth... | 0 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
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size_categories:
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paperswithcode_i... | 4,848 | [
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stsb_mt_sv | 2022-11-18T21:48:42.000Z | [
"task_categories:text-classification",
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"size_categories:1K<n<10K",
"source_datasets:extended|o... | null | null | @article{isbister2020not,
title={Why Not Simply Translate? A First Swedish Evaluation Benchmark for Semantic Similarity},
author={Isbister, Tim and Sahlgren, Magnus},
journal={arXiv preprint arXiv:2009.03116},
year={2020}
} | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
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language:
- sv
license:
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size_categories:
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source_datasets:
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task_categories:
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urdu_sentiment_corpus | 2023-01-25T15:02:01.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ur",
"license:unknown",
"region:us"
] | null | “Urdu Sentiment Corpus” (USC) shares the dat of Urdu tweets for the sentiment analysis and polarity detection.
The dataset is consisting of tweets and overall, the dataset is comprising over 17, 185 tokens
with 52% records as positive, and 48 % records as negative. | @inproceedings{khan2020usc,
title={Urdu Sentiment Corpus (v1.0): Linguistic Exploration and Visualization of Labeled Datasetfor Urdu Sentiment Analysis.},
author={Khan, Muhammad Yaseen and Nizami, Muhammad Suffian},
booktitle={2020 IEEE 2nd International Conference On Information Science & Communication Technolog... | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- ur
license:
- unknown
multilinguality:
- monolingual
size_categories:
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source_datasets:
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task_categories:
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task_ids:
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paperswithcode_id: urdu-sentiment-corpus
pre... | 3,493 | [
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youtube_caption_corrections | 2023-01-25T15:03:42.000Z | [
"task_categories:other",
"task_categories:text-generation",
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"multilinguality:monolingual",
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"... | null | Dataset built from pairs of YouTube captions where both 'auto-generated' and
'manually-corrected' captions are available for a single specified language.
This dataset labels two-way (e.g. ignoring single-sided insertions) same-length
token differences in the `diff_type` column. The `default_seq` is composed of
tokens f... | null | 4 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
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language_creators:
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language:
- en
license:
- mit
multilinguality:
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size_categories:
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source_datasets:
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pretty_name: YouT... | 8,215 | [
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ASCCCCCCCC/amazon_zh | 2022-02-17T02:16:59.000Z | [
"license:apache-2.0",
"region:us"
] | ASCCCCCCCC | null | null | 1 | 86 | 2022-03-02T23:29:22 | ---
license: apache-2.0
---
this is a datasets about amazon reviews | 70 | [
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Abirate/code_net_dataset | 2021-12-11T17:41:32.000Z | [
"region:us"
] | Abirate | null | null | 2 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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AhmedSSoliman/CoNaLa | 2022-01-22T09:34:19.000Z | [
"region:us"
] | AhmedSSoliman | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
task_categories:
- Code Generation
- Translation
- Text2Text generation
---
# CoNaLa Dataset for Code Generation
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fi... | 1,593 | [
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Aisha/BAAD16 | 2022-10-22T05:31:54.000Z | [
"task_categories:text-classification",
"task_ids:multi-class-classification",
"annotations_creators:found",
"annotations_creators:crowdsourced",
"annotations_creators:expert-generated",
"language_creators:found",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"source_datasets:origi... | Aisha | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
- crowdsourced
- expert-generated
language_creators:
- found
- crowdsourced
language:
- bn
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: 'BAAD16: Bangla Authorship Attribution Dataset (16 Authors)'
source_datasets:
- original
task_categories:
- text-classification
ta... | 3,171 | [
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Akila/ForgottenRealmsWikiDataset | 2022-12-18T12:28:34.000Z | [
"region:us"
] | Akila | null | null | 2 | 86 | 2022-03-02T23:29:22 | ## Citing this work
@inproceedings{peiris2022synthesis,
title={{Synthesis and Evaluation of a Domain-specific Large Data Set for Dungeons \& Dragons}},
author={Akila Peiris and Nisansa de Silva},
booktitle={Proceedings of the 36th Pacific Asia Conference on Language, Information and Computation},... | 368 | [
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Check/region_2 | 2021-09-04T11:04:11.000Z | [
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Check/region_6 | 2021-09-04T11:08:02.000Z | [
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"region:us"
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"region:us"
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Check/regions | 2021-08-31T14:34:50.000Z | [
"region:us"
] | Check | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Check/vverify | 2021-09-11T05:13:10.000Z | [
"region:us"
] | Check | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Cropinky/wow_fishing_bobber | 2021-06-30T22:14:04.000Z | [
"region:us"
] | Cropinky | null | null | 0 | 86 | 2022-03-02T23:29:22 | ## Wow fishing bobber object detection dataset
Hello, in this zip you will find 160 annotated images each containing 1 fishing bobber from World of warcraft.
I think this is an easy object detection datset, my yolov3 network was trained on it for 2000 iterations, it achieved
a loss of 0.05. It was working flawlessly as... | 495 | [
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DDSC/reddit-da-asr-preprocessed | 2022-02-15T19:17:08.000Z | [
"region:us"
] | DDSC | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Davlan/conll2003_noMISC | 2022-02-03T19:00:25.000Z | [
"region:us"
] | Davlan | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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DelgadoPanadero/Pokemon | 2022-01-03T10:10:40.000Z | [
"region:us"
] | DelgadoPanadero | null | null | 3 | 86 | 2022-03-02T23:29:22 | # Pokemon Dataset
This dataset contains a text representation of more that 10k pokemon sprites from different pokemon videogames (red, yellow, gold, ruby,...). The original images are from 40 to 96 pixel of size and every pixel is represented with an ASCII character depending to its color.
# Supported Tasks
* Text ... | 8,885 | [
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Emanuel/UD_Portuguese-Bosque | 2022-10-25T08:54:18.000Z | [
"language:pt",
"region:us"
] | Emanuel | null | null | 1 | 86 | 2022-03-02T23:29:22 | ---
language:
- pt
---
# AutoNLP Dataset for project: pos-tag-bosque
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-fields)
- [Data Splits](#data-splits)
## Datase... | 1,705 | [
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FIG-Loneliness/FIG-Loneliness | 2022-07-14T23:14:43.000Z | [
"region:us"
] | FIG-Loneliness | null | null | 1 | 86 | 2022-03-02T23:29:22 | # Dataset Card for FIG-Loneliness
## 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-str... | 8,774 | [
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GEM/CrossWOZ | 2022-10-24T15:29:55.000Z | [
"task_categories:conversational",
"annotations_creators:none",
"language_creators:unknown",
"multilinguality:unknown",
"size_categories:unknown",
"source_datasets:original",
"language:zh",
"license:apache-2.0",
"dialog-response-generation",
"region:us"
] | GEM | CrossWOZ is the first large-scale Chinese Cross-Domain Wizard-of-Oz task-oriented dataset. It contains 6K dialogue sessions and 102K utterances for 5 domains, including hotel, restaurant, attraction, metro, and taxi. Moreover, the corpus contains rich annotation of dialogue states and dialogue acts at both user and sys... | @article{zhu2020crosswoz,
author = {Qi Zhu and Kaili Huang and Zheng Zhang and Xiaoyan Zhu and Minlie Huang},
title = {Cross{WOZ}: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset},
journal = {Transactions of the Association for Computational Linguistics},
year = {2020}
} | 5 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- none
language_creators:
- unknown
language:
- zh
license:
- apache-2.0
multilinguality:
- unknown
size_categories:
- unknown
source_datasets:
- original
task_categories:
- conversational
task_ids: []
pretty_name: CrossWOZ
tags:
- dialog-response-generation
---
# Dataset Card for GEM/CrossWO... | 43,055 | [
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GEM-submissions/submission-scores | 2023-06-08T23:06:02.000Z | [
"region:us"
] | GEM-submissions | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Gabriel/quora_swe | 2022-10-22T09:39:38.000Z | [
"task_categories:text-retrieval",
"task_categories:text-classification",
"task_ids:semantic-similarity-classification",
"size_categories:10K<n<100K",
"language:sv",
"license:mit",
"question-pairing",
"semantic-search",
"region:us"
] | Gabriel | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
language:
- sv
license:
- mit
size_categories:
- 10K<n<100K
task_categories:
- text-retrieval
- text-classification
task_ids:
- semantic-similarity-classification
tags:
- question-pairing
- semantic-search
---
# Dataset Card for "quora_swe"
The dataset quora_swe is a subset of the automatically translated (MNT) S... | 386 | [
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JesseParvess/book_snippets_asr | 2021-12-09T10:36:16.000Z | [
"region:us"
] | JesseParvess | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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Jiejie/asr_book_lm | 2022-02-26T10:27:32.000Z | [
"region:us"
] | Jiejie | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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LysandreJik/demo1 | 2021-09-25T19:54:41.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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LysandreJik/demo2 | 2021-09-25T19:57:03.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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LysandreJik/demo3 | 2021-09-25T19:58:09.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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LysandreJik/pushed-to-hub | 2021-10-07T22:33:54.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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LysandreJik/test-16336486877862 | 2021-10-07T23:18:09.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03... |
LysandreJik/test-16340052972855 | 2021-10-12T02:21:38.000Z | [
"region:us"
] | LysandreJik | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.021392822265625,
-0.0149688720703125,
0.057220458984375,
0.0288238525390625,
-0.03509521484375,
0.046539306640625,
0.052520751953125,
0.005046844482421875,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.01495361328125,
-0.060333251953125,
0.03... |
NYTK/HuSST | 2023-03-27T09:54:13.000Z | [
"task_categories:text-classification",
"task_ids:sentiment-classification",
"task_ids:sentiment-scoring",
"task_ids:text-scoring",
"annotations_creators:found",
"language_creators:found",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datase... | NYTK | null | null | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- found
language_creators:
- found
- expert-generated
language:
- hu
license:
- bsd-2-clause
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- extended|other
task_categories:
- text-classification
task_ids:
- sentiment-classification
- sentiment-scoring
- text-scorin... | 6,082 | [
[
-0.022491455078125,
-0.0623779296875,
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0.0130615234375,
-0.0289154052734375,
-0.0033473968505859375,
-0.03741455078125,
-0.0244598388671875,
0.0244598388671875,
0.02801513671875,
-0.049560546875,
-0.07452392578125,
-0.04144287109375,
0.01... |
SuperAI2-Machima/ThaiQA_LST20 | 2022-02-25T06:29:22.000Z | [
"language:thai",
"language:th",
"license:mit",
"question-generation dataset",
"qa dataset",
"region:us"
] | SuperAI2-Machima | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
tags:
- question-generation dataset
- qa dataset
language:
- thai
- th
datasets:
- LST20
license: mit
---
[SuperAI Engineer Season 2](https://superai.aiat.or.th/) , [Machima](https://machchima.superai.me/)
Machima_ThaiQA_LST20 เป็นชุดข้อมูลที่สกัดหาคำถาม และคำตอบ จากบทความในชุดข้อมูล LST20 โดยสกัดได้คำถาม-ตอบทั... | 1,527 | [
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... |
abidlabs/crowdsourced-speech4 | 2022-01-21T16:26:22.000Z | [
"region:us"
] | abidlabs | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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-0.01494598388671875,
-0.06036376953125,
0.03790... |
antoinegk/HealthChallenge_dataset | 2022-01-19T18:21:42.000Z | [
"region:us"
] | antoinegk | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.021392822265625,
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-0.01494598388671875,
-0.06036376953125,
0.03790... |
lmqg/qg_jaquad | 2022-12-02T18:51:27.000Z | [
"task_categories:text-generation",
"task_ids:language-modeling",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:SkelterLabsInc/JaQuAD",
"language:ja",
"license:cc-by-sa-3.0",
"question-generation",
"arxiv:2210.03992",
"region:us"
] | lmqg | [JaQuAD](https://github.com/SkelterLabsInc/JaQuAD) dataset for question generation (QG) task. The test set of the original
data is not publicly released, so we randomly sampled test questions from the training set. | @inproceedings{ushio-etal-2022-generative,
title = "{G}enerative {L}anguage {M}odels for {P}aragraph-{L}evel {Q}uestion {G}eneration",
author = "Ushio, Asahi and
Alva-Manchego, Fernando and
Camacho-Collados, Jose",
booktitle = "Proceedings of the 2022 Conference on Empirical Methods in Nat... | 4 | 86 | 2022-03-02T23:29:22 | ---
license: cc-by-sa-3.0
pretty_name: JaQuAD for question generation
language: ja
multilinguality: monolingual
size_categories: 10K<n<100K
source_datasets: SkelterLabsInc/JaQuAD
task_categories:
- text-generation
task_ids:
- language-modeling
tags:
- question-generation
---
# Dataset Card for "lmqg/qg_jaquad"
## Da... | 4,726 | [
[
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-0.045166015625,
-0.01255035400390625,
0.0137557... |
azuur/es_corpora_parliament_processed | 2022-01-26T16:58:53.000Z | [
"region:us"
] | azuur | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
badranx/opus_raw | 2022-01-28T14:19:19.000Z | [
"region:us"
] | badranx | mono corpus from http://www.opensubtitles.org/. Please check http://www.opensubtitles.org/ for the available corpora and licenses. | P. Lison and J. Tiedemann, 2016, OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles. In Proceedings of the 10th International Conference on Language Resources and Evaluation (LREC 2016) | 1 | 86 | 2022-03-02T23:29:22 | ## Load mono corpora from OPUS
OPUS provides many parallel corpora, but it has more data for a single language. This enables you to load any raw mono corpus from [opus.nlpl.eu](https://opus.nlpl.eu/). Please check [opus.nlpl.eu](https://opus.nlpl.eu/) for the available corpora and licenses. The targeted corpus is call... | 1,089 | [
[
-0.033538818359375,
-0.027191162109375,
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0.043548583984375,
-0.039520263671875,
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-0.037841796875,
-0.02032470703125,
0.035369873046875,
0.0440673828125,
-0.03369140625,
-0.049102783203125,
-0.0191497802734375,
0.031524... |
biu-nlp/qa_align | 2021-11-19T01:01:40.000Z | [
"region:us"
] | biu-nlp | This dataset contains QA-Alignments - annotations of cross-text content overlap.
The task input is two sentences from two documents, roughly talking about the same event, along with their QA-SRL annotations
which capture verbal predicate-argument relations in question-answer format. The output is a cross-sentence ali... | @inproceedings{brook-weiss-etal-2021-qa,
title = "{QA}-Align: Representing Cross-Text Content Overlap by Aligning Question-Answer Propositions",
author = "Brook Weiss, Daniela and
Roit, Paul and
Klein, Ayal and
Ernst, Ori and
Dagan, Ido",
booktitle = "Proceedings of the 2021 Conf... | 0 | 86 | 2022-03-02T23:29:22 | # QA-Align
This dataset contains QA-Alignments --- fine-grained annotations of cross-text content overlap.
The task input is two sentences from two documents, roughly talking about the same event, along with their QA-SRL annotations
which capture verbal predicate-argument relations in question-answer format. The out... | 2,099 | [
[
-0.0184326171875,
-0.05120849609375,
0.03485107421875,
-0.0003135204315185547,
0.007175445556640625,
-0.00847625732421875,
0.00716400146484375,
-0.017425537109375,
0.0288848876953125,
0.035614013671875,
-0.071533203125,
-0.047271728515625,
-0.0211944580078125,
... |
biu-nlp/qanom | 2022-10-18T09:50:01.000Z | [
"region:us"
] | biu-nlp | The dataset contains question-answer pairs to model predicate-argument structure of deverbal nominalizations.
The questions start with wh-words (Who, What, Where, What, etc.) and contain a the verbal form of a nominalization from the sentence;
the answers are phrases in the sentence.
See the paper for details: QANom... | @inproceedings{klein2020qanom,
title={QANom: Question-Answer driven SRL for Nominalizations},
author={Klein, Ayal and Mamou, Jonathan and Pyatkin, Valentina and Stepanov, Daniela and He, Hangfeng and Roth, Dan and Zettlemoyer, Luke and Dagan, Ido},
booktitle={Proceedings of the 28th International Conference on Co... | 1 | 86 | 2022-03-02T23:29:22 | # QANom
This dataset contains question-answer pairs to model the predicate-argument structure of deverbal nominalizations.
The questions start with wh-words (Who, What, Where, What, etc.) and contain the verbal form of a nominalization from the sentence;
the answers are phrases in the sentence.
See the paper for ... | 822 | [
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0.057403564453125,
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-0.059326171875,
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0.01... |
castorini/msmarco_v1_doc_doc2query-t5_expansions | 2022-07-02T19:16:12.000Z | [
"language:en",
"license:apache-2.0",
"region:us"
] | castorini | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
language:
- en
license: apache-2.0
---
# Dataset Summary
The repo provides queries generated for the MS MARCO V1 document corpus with docTTTTTquery (sometimes written as docT5query or doc2query-T5), the latest version of the doc2query family of document expansion models. The basic idea is to train a model, that ... | 2,172 | [
[
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0.055816650390625,
-0.05517578125,
-0.05828857421875,
-0.035186767578125,
... |
castorini/nq_gar-t5_expansions | 2023-10-10T18:58:22.000Z | [
"language:en",
"license:apache-2.0",
"region:us"
] | castorini | null | null | 1 | 86 | 2022-03-02T23:29:22 | ---
language:
- "en"
license: "apache-2.0"
---
# Dataset Summary
The repo provides answer, title and sentence expansions for the Natural Questions corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
"predicted_answe... | 1,042 | [
[
-0.05224609375,
-0.0579833984375,
0.01983642578125,
-0.0252532958984375,
-0.024688720703125,
0.0218505859375,
0.00951385498046875,
-0.01458740234375,
0.010345458984375,
0.04412841796875,
-0.06585693359375,
-0.0406494140625,
-0.034912109375,
0.03277587890625,... |
castorini/triviaqa_gar-t5_expansions | 2022-02-17T00:58:32.000Z | [
"language:English",
"license:Apache License 2.0",
"region:us"
] | castorini | null | null | 0 | 86 | 2022-03-02T23:29:22 | ---
language:
- English
license: "Apache License 2.0"
---
# Dataset Summary
The repo provides answer,title and sentence expansions for the Trivia QA corpus with gar-T5.
# Dataset Structure
There are dev and test folds
An example data entry of the dev split looks as follows:
```
{
"id": "1",
... | 1,365 | [
[
-0.037139892578125,
-0.0487060546875,
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0.00031375885009765625,
-0.014801025390625,
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0.01136016845703125,
0.0413818359375,
-0.040618896484375,
-0.061553955078125,
-0.022796630859375,
... |
cdminix/mgb1 | 2021-02-05T16:04:03.000Z | [
"region:us"
] | cdminix | The first edition of the Multi-Genre Broadcast (MGB-1) Challenge is an evaluation of speech recognition, speaker diarization, and lightly supervised alignment using TV recordings in English.
The speech data is broad and multi-genre, spanning the whole range of TV output, and represents a challenging task for speech te... | @inproceedings{bell2015mgb,
title={The MGB challenge: Evaluating multi-genre broadcast media recognition},
author={Bell, Peter and Gales, Mark JF and Hain, Thomas and Kilgour, Jonathan and Lanchantin, Pierre and Liu, Xunying and McParland, Andrew and Renals, Steve and Saz, Oscar and Wester, Mirjam and others},
bo... | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.02142333984375,
-0.01495361328125,
0.05718994140625,
0.0288238525390625,
-0.035064697265625,
0.046539306640625,
0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
cem/dnm | 2021-12-24T10:48:27.000Z | [
"region:us"
] | cem | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
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0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
cestwc/adapted-msrcomp | 2021-12-16T06:34:25.000Z | [
"region:us"
] | cestwc | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
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0.052490234375,
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0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
cestwc/adapted-synonym | 2021-12-29T16:59:46.000Z | [
"region:us"
] | cestwc | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
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0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
cestwc/conjnli | 2022-02-15T15:23:38.000Z | [
"region:us"
] | cestwc | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
chenyuxuan/wikigold | 2021-07-26T12:40:03.000Z | [
"region:us"
] | chenyuxuan | WikiGold dataset. | @inproceedings{balasuriya-etal-2009-named,
title = "Named Entity Recognition in Wikipedia",
author = "Balasuriya, Dominic and
Ringland, Nicky and
Nothman, Joel and
Murphy, Tara and
Curran, James R.",
booktitle = "Proceedings of the 2009 Workshop on The People{'}s Web Meets {NLP}:... | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
cheulyop/dementiabank | 2021-10-04T14:18:42.000Z | [
"region:us"
] | cheulyop | DementiaBank Pitt Corpus includes audios and transcripts of 99 controls and 194 dementia patients. These transcripts and audio files were gathered as part of a larger protocol administered by the Alzheimer and Related Dementias Study at the University of Pittsburgh School of Medicine. The original acquisition of the De... | @article{becker1994natural,
title={The natural history of Alzheimer's disease: description of study cohort and accuracy of diagnosis},
author={Becker, James T and Boiler, Fran{\c{c}}ois and Lopez, Oscar L and Saxton, Judith and McGonigle, Karen L},
journal={Archives of neurology},
volume={51},
number={6},
p... | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
-0.0213775634765625,
-0.01497650146484375,
0.05718994140625,
0.02880859375,
-0.0350341796875,
0.046478271484375,
0.052490234375,
0.00507354736328125,
0.051361083984375,
0.0170135498046875,
-0.052093505859375,
-0.01497650146484375,
-0.0604248046875,
0.0379028... |
clarin-pl/2021-punctuation-restoration | 2022-08-29T16:39:18.000Z | [
"task_categories:automatic-speech-recognition",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:n<1K",
"language:pl",
"region:us"
] | clarin-pl | This dataset is designed to be used in training models
that restore punctuation marks from the output of
Automatic Speech Recognition system for Polish language. | """
_DESCRIPTION = | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language:
- pl
language_creators:
- crowdsourced
license: []
multilinguality:
- monolingual
pretty_name: 2021-punctuation-restoration
size_categories:
- n<1K
source_datasets: []
tags: []
task_categories:
- automatic-speech-recognition
task_ids: []
---
# Punctuation restoration ... | 17,751 | [
[
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0.03668212890625,
-0.0261993408203125,
0.007080078125,
-0.020263671875,
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0.0322265625,
0.02557373046875,
-0.050445556640625,
-0.0377197265625,
-0.041748046875,
0.034881591796875,... |
clarin-pl/aspectemo | 2022-08-29T16:39:32.000Z | [
"task_categories:token-classification",
"task_ids:sentiment-classification",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:1K",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:pl",
"license:mit",
"region:us"
... | clarin-pl | AspectEmo dataset: Multi-Domain Corpus of Consumer Reviews for Aspect-Based
Sentiment Analysis | @misc{11321/849,
title = {{AspectEmo} 1.0: Multi-Domain Corpus of Consumer Reviews for Aspect-Based Sentiment Analysis},
author = {Koco{\'n}, Jan and Radom, Jarema and Kaczmarz-Wawryk, Ewa and Wabnic, Kamil and Zaj{\c a}czkowska, Ada and Za{\'s}ko-Zieli{\'n}ska, Monika},
url = {http://hdl.handle.net/11321/849},
... | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- mit
multilinguality:
- monolingual
pretty_name: 'AspectEmo'
size_categories:
- 1K
- 1K<n<10K
source_datasets:
- original
task_categories:
- token-classification
task_ids:
- sentiment-classification
---
# AspectE... | 6,891 | [
[
-0.039825439453125,
-0.0452880859375,
0.02886962890625,
0.022247314453125,
-0.0220184326171875,
-0.0154266357421875,
-0.01491546630859375,
-0.0233001708984375,
0.043792724609375,
0.0299835205078125,
-0.031097412109375,
-0.061798095703125,
-0.031585693359375,
... |
clarin-pl/nkjp-pos | 2023-01-30T22:53:57.000Z | [
"task_categories:other",
"task_ids:part-of-speech",
"annotations_creators:expert-generated",
"language_creators:other",
"multilinguality:monolingual",
"size_categories:unknown",
"source_datasets:original",
"language:pl",
"license:gpl-3.0",
"structure-prediction",
"region:us"
] | clarin-pl | NKJP-POS tagging dataset. | null | 1 | 86 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- other
language:
- pl
license:
- gpl-3.0
multilinguality:
- monolingual
size_categories:
- unknown
source_datasets:
- original
task_categories:
- other
task_ids:
- part-of-speech
pretty_name: nkjp-pos
tags:
- structure-prediction
---
# nkjp-pos
## Descr... | 6,162 | [
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0.013... |
classla/janes_tag | 2022-10-25T07:31:04.000Z | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:part-of-speech",
"language:si",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | classla | The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent_id'),
list of tokens ('tokens'), list of normalised word forms ('norms'), list of lemmas ('lemmas'),
list of Multext-East tags ('xpos_tags... | null | 0 | 86 | 2022-03-02T23:29:22 | ---
language:
- si
license:
- cc-by-sa-4.0
task_categories:
- other
task_ids:
- lemmatization
- part-of-speech
tags:
- structure-prediction
- normalization
- tokenization
---
The dataset contains 6273 training samples, 762 validation samples and 749 test samples.
Each sample represents a sentence and includes the foll... | 615 | [
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0.047027587890625,
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classla/reldi_hr | 2022-10-25T07:30:56.000Z | [
"task_categories:other",
"task_ids:lemmatization",
"task_ids:named-entity-recognition",
"task_ids:part-of-speech",
"language:hr",
"license:cc-by-sa-4.0",
"structure-prediction",
"normalization",
"tokenization",
"region:us"
] | classla | The dataset contains 6339 training samples, 815 validation samples and 785 test samples.
Each sample represents a sentence and includes the following features: sentence ID ('sent_id'),
list of tokens ('tokens'), list of lemmas ('lemmas'), list of UPOS tags ('upos_tags'),
list of Multext-East tags ('xpos_tags), list ... | null | 0 | 86 | 2022-03-02T23:29:22 | ---
language:
- hr
license:
- cc-by-sa-4.0
task_categories:
- other
task_ids:
- lemmatization
- named-entity-recognition
- part-of-speech
tags:
- structure-prediction
- normalization
- tokenization
---
This dataset is based on 3,871 Croatian tweets that were segmented into sentences, tokens, and annotated with normaliz... | 1,469 | [
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-0.03973388671875,
0.02734... |
cloverhxy/DADER-source | 2023-02-26T08:58:31.000Z | [
"region:us"
] | cloverhxy | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.06036376953125,
0.03... |
ctu-aic/anli_cs | 2021-11-21T21:12:10.000Z | [
"region:us"
] | ctu-aic | TODO: Anli_cs is a Czech translation of the Adversarial NLI dataset | todo | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.014984130859375,
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0.0379... |
ctu-aic/ctkfacts_nli | 2022-11-01T06:35:47.000Z | [
"arxiv:2201.11115",
"region:us"
] | ctu-aic | CtkFactsNLI is a NLI version of the Czech CTKFacts dataset | @article{DBLP:journals/corr/abs-2201-11115,
author = {Jan Drchal and
Herbert Ullrich and
Martin R{\'{y}}par and
Hana Vincourov{\'{a}} and
V{\'{a}}clav Moravec},
title = {CsFEVER and CTKFacts: Czech Datasets for Fact Verification},
journal = {CoR... | 2 | 86 | 2022-03-02T23:29:22 | # CTKFacts dataset for Natural Language Inference
Czech Natural Language Inference dataset of ~3K *evidence*-*claim* pairs labelled with SUPPORTS, REFUTES or NOT ENOUGH INFO veracity labels. Extracted from a round of fact-checking experiments concluded and described within the CsFEVER and [CTKFacts: Czech Datasets for... | 532 | [
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0.0655517578125,
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0.03... |
davanstrien/iiif_manuscripts_label_ge_50 | 2022-02-28T18:53:18.000Z | [
"region:us"
] | davanstrien | null | null | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
davidwisdom/reddit-randomness | 2021-11-06T23:56:43.000Z | [
"region:us"
] | davidwisdom | null | null | 0 | 86 | 2022-03-02T23:29:22 | # Reddit Randomness Dataset
A dataset I created because I was curious about how "random" r/random really is.
This data was collected by sending `GET` requests to `https://www.reddit.com/r/random` for a few hours on September 19th, 2021.
I scraped a bit of metadata about the subreddits as well.
`randomness_12k_clean.csv... | 2,782 | [
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-0.035614013671875,
... |
ebrigham/labels | 2022-03-15T15:08:28.000Z | [
"region:us"
] | ebrigham | AG is a collection of more than 1 million news articles. News articles have been
gathered from more than 2000 news sources by ComeToMyHead in more than 1 year of
activity. ComeToMyHead is an academic news search engine which has been running
since July, 2004. The dataset is provided by the academic comunity for researc... | @inproceedings{Zhang2015CharacterlevelCN,
title={Character-level Convolutional Networks for Text Classification},
author={Xiang Zhang and Junbo Jake Zhao and Yann LeCun},
booktitle={NIPS},
year={2015}
} | 0 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.01494598388671875,
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0.03790... |
emrecan/stsb-mt-turkish | 2022-10-25T10:55:24.000Z | [
"task_categories:text-classification",
"task_ids:semantic-similarity-scoring",
"task_ids:text-scoring",
"language_creators:machine-generated",
"size_categories:1K<n<10K",
"source_datasets:extended|other-sts-b",
"language:tr",
"region:us"
] | emrecan | null | null | 3 | 86 | 2022-03-02T23:29:22 | ---
language_creators:
- machine-generated
language:
- tr
size_categories:
- 1K<n<10K
source_datasets:
- extended|other-sts-b
task_categories:
- text-classification
task_ids:
- semantic-similarity-scoring
- text-scoring
---
# STSb Turkish
Semantic textual similarity dataset for the Turkish language. It is a machine t... | 566 | [
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0... |
gigant/african_accented_french | 2022-10-24T17:39:03.000Z | [
"task_categories:automatic-speech-recognition",
"language:fr",
"license:cc",
"region:us"
] | gigant | \
This corpus consists of approximately 22 hours of speech recordings. Transcripts are provided for all the recordings. The corpus can be divided into 3 parts:
1. Yaounde
Collected by a team from the U.S. Military Academy's Center for Technology Enhanced Language Learning (CTELL) in 2003 in Yaoundé, Cameroon. It... | \ | 3 | 86 | 2022-03-02T23:29:22 | ---
language:
- fr
license: cc
size_categories:
fr:
- 10K<n<100K
task_categories:
- automatic-speech-recognition
task_ids: []
pretty_name: African Accented French
---
## Dataset Description
- **Homepage:** http://www.openslr.org/57/
### Dataset Summary
This corpus consists of approximately 22 hours of speech rec... | 2,412 | [
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0.... |
huggingface/transformers-metadata | 2023-11-02T20:10:54.000Z | [
"region:us"
] | huggingface | null | null | 6 | 86 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ctheodoris/Genecorpus-30M | 2023-10-10T01:37:03.000Z | [
"license:apache-2.0",
"region:us"
] | ctheodoris | null | null | 34 | 86 | 2022-03-12T21:21:46 | ---
license: apache-2.0
---
# Dataset Card for Genecorpus-30M
## Table of Contents
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks)
- [Species](#species)
- [Dataset Structure](#dataset-structure)
... | 11,902 | [
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hackathon-pln-es/MESD | 2022-03-25T18:15:07.000Z | [
"license:cc-by-4.0",
"region:us"
] | hackathon-pln-es | null | null | 6 | 86 | 2022-03-19T18:39:32 | ---
license: cc-by-4.0
Duville, Mathilde Marie; Alonso-Valerdi, Luz Maria; Ibarra, David (2022), “Mexican Emotional Speech Database (MESD)”, Mendeley Data, V5, doi: 10.17632/cy34mh68j9.5
---
# Dataset Card for MESD
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#... | 6,276 | [
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tner/conll2003 | 2022-07-18T00:43:28.000Z | [
"task_categories:token-classification",
"task_ids:named-entity-recognition",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"language:en",
"license:other",
"region:us"
] | tner | [CoNLL 2003 NER dataset](https://aclanthology.org/W03-0419/) | @inproceedings{tjong-kim-sang-de-meulder-2003-introduction,
title = "Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition",
author = "Tjong Kim Sang, Erik F. and De Meulder, Fien",
booktitle = "Proceedings of the Seventh Conference on Natural Language Learning at {H... | 1 | 86 | 2022-07-16T10:39:09 | ---
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
task_categories:
- token-classification
task_ids:
- named-entity-recognition
pretty_name: CoNLL-2003
---
# Dataset Card for "tner/conll2003"
## Dataset Description
- **Repository:** [T-NER](https://github.com/asahi417/tn... | 2,973 | [
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0.0375... |
keremberke/football-object-detection | 2023-01-04T20:39:21.000Z | [
"task_categories:object-detection",
"roboflow",
"region:us"
] | keremberke | null | @misc{ football-player-detection-kucab_dataset,
title = { Football-Player-Detection Dataset },
type = { Open Source Dataset },
author = { Augmented Startups },
howpublished = { \\url{ https://universe.roboflow.com/augmented-startups/football-player-detection-kucab } },
url = { https://universe.robof... | 5 | 86 | 2022-12-28T20:09:47 | ---
task_categories:
- object-detection
tags:
- roboflow
---
### Roboflow Dataset Page
[https://universe.roboflow.com/augmented-startups/football-player-detection-kucab](https://universe.roboflow.com/augmented-startups/football-player-detection-kucab?ref=roboflow2huggingface)
### Citation
```
@misc{ football-player-d... | 1,539 | [
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... |
Francesco/cable-damage | 2023-03-30T09:29:47.000Z | [
"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 | 2 | 86 | 2023-03-30T09:29:23 | ---
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... | 3,367 | [
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0.02886962890625,
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-0.0545654296875,
-0.04364013671875,
0.0... |
slvnwhrl/blurbs-clustering-p2p | 2023-04-24T11:42:06.000Z | [
"size_categories:10K<n<100K",
"language:de",
"license:cc-by-nc-4.0",
"embeddings",
"clustering",
"benchmark",
"region:us"
] | slvnwhrl | null | null | 0 | 86 | 2023-04-21T14:17:32 | ---
license: cc-by-nc-4.0
language:
- de
tags:
- embeddings
- clustering
- benchmark
size_categories:
- 10K<n<100K
---
This dataset can be used as a benchmark for clustering word embeddings for <b>German</b>.
The datasets contains book titles and is based on the dataset from the [GermEval 2019 Shared Task on Hierarch... | 850 | [
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0... |
thu-coai/chid | 2023-05-08T09:11:55.000Z | [
"language:zh",
"license:apache-2.0",
"arxiv:1906.01265",
"region:us"
] | thu-coai | null | null | 3 | 86 | 2023-05-08T08:21:01 | ---
license: apache-2.0
language:
- zh
---
The ChID dataset. [GitHub repo](https://github.com/chujiezheng/ChID-Dataset). [Original paper](https://arxiv.org/abs/1906.01265).
```bib
@inproceedings{zheng-etal-2019-chid,
title = "{C}h{ID}: A Large-scale {C}hinese {ID}iom Dataset for Cloze Test",
author = "Zheng, ... | 422 | [
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... |
d0rj/dialogsum-ru | 2023-05-13T06:27:30.000Z | [
"task_categories:summarization",
"task_categories:text2text-generation",
"task_categories:text-generation",
"annotations_creators:expert-generated",
"language_creators:translated",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:knkarthick/dialogsum",
"language:ru",
"... | d0rj | null | null | 2 | 86 | 2023-05-08T14:17:46 | ---
annotations_creators:
- expert-generated
language_creators:
- translated
language:
- ru
license:
- mit
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- knkarthick/dialogsum
task_categories:
- summarization
- text2text-generation
- text-generation
task_ids: []
pretty_name: DIALOGSum Co... | 3,816 | [
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augtoma/medmcqa | 2023-08-11T20:44:27.000Z | [
"region:us"
] | augtoma | null | null | 1 | 86 | 2023-08-11T20:44:11 | ---
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: test
path: data/test-*
dataset_info:
features:
- name: id
dtype: string
- name: question
dtype: string
- name: cop
dtype:
class_label:
names:
'0': a
'1': b
... | 1,095 | [
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open-llm-leaderboard/details_psmathur__model_007_13b | 2023-08-27T12:28:41.000Z | [
"region:us"
] | open-llm-leaderboard | null | null | 0 | 86 | 2023-08-18T00:15:44 | ---
pretty_name: Evaluation run of psmathur/model_007_13b
dataset_summary: "Dataset automatically created during the evaluation run of model\
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harvard-lil/cold-cases | 2023-10-19T20:17:38.000Z | [
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---
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shengqin/web-attacks-long | 2023-10-03T07:50:07.000Z | [
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BubbleJoe/multi_nli_unified_input | 2023-10-10T19:45:11.000Z | [
"region:us"
] | BubbleJoe | null | null | 1 | 86 | 2023-10-10T19:39:20 | ---
configs:
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data_files:
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path: data/train-*
- split: validation_matched
path: data/validation_matched-*
- split: validation_mismatched
path: data/validation_mismatched-*
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ofis_publik | 2022-11-03T16:15:15.000Z | [
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"language:fr",
"license:unknown",
"region:us"
] | null | Texts from the Ofis Publik ar Brezhoneg (Breton Language Board) provided by Francis Tyers
2 languages, total number of files: 278
total number of tokens: 2.12M
total number of sentence fragments: 0.13M | @InProceedings{TIEDEMANN12.463,
author = {J{\"o}rg Tiedemann},
title = {Parallel Data, Tools and Interfaces in OPUS},
booktitle = {Proceedings of the Eight International Conference on Language Resources and Evaluation (LREC'12)},
year = {2012},
month = {may},
date = {23-25},
address = {Istanbul, Turkey},
... | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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paperswithcode_id: null
pretty_name: OfisPublik
dataset_info:
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opus_finlex | 2022-11-03T16:08:11.000Z | [
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] | null | The Finlex Data Base is a comprehensive collection of legislative and other judicial information of Finland, which is available in Finnish, Swedish and partially in English. This corpus is taken from the Semantic Finlex serice that provides the Finnish and Swedish data as linked open data and also raw XML files. | J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012) | 1 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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paperswithcode_id: null
pretty_name: OpusFinlex
dataset_info:
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opus_fiskmo | 2022-11-03T16:08:01.000Z | [
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] | null | fiskmo, a massive parallel corpus for Finnish and Swedish. | J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012) | 0 | 85 | 2022-03-02T23:29:22 | ---
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paperswithcode_id: null
pretty_name: OpusFiskmo
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opus_montenegrinsubs | 2022-11-03T16:08:11.000Z | [
"task_categories:translation",
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"region:us"
] | null | Opus MontenegrinSubs dataset for machine translation task, for language pair en-me: english and montenegrin | J. Tiedemann, 2012, Parallel Data, Tools and Interfaces in OPUS. In Proceedings of the 8th International Conference on Language Resources and Evaluation (LREC 2012) | 0 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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task_ids: []
paperswithcode_id: null
pretty_name: OpusMontenegrinsubs
dataset_info:
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pass | 2022-11-03T16:15:51.000Z | [
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"language:en",
"license:cc-by-4.0",
"image-self-supervised pre... | null | PASS (Pictures without humAns for Self-Supervision) is a large-scale dataset of 1,440,191 images that does not include any humans
and which can be used for high-quality pretraining while significantly reducing privacy concerns.
The PASS images are sourced from the YFCC-100M dataset. | @Article{asano21pass,
author = "Yuki M. Asano and Christian Rupprecht and Andrew Zisserman and Andrea Vedaldi",
title = "PASS: An ImageNet replacement for self-supervised pretraining without humans",
journal = "NeurIPS Track on Datasets and Benchmarks",
year = "2021"
} | 1 | 85 | 2022-03-02T23:29:22 | ---
annotations_creators:
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paperswithcode_id: pass
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