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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
mpierrau/sv_corpora_parliament_processed | 2022-02-03T14:31:52.000Z | [
"region:us"
] | mpierrau | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mrm8488/goemotions | 2021-12-28T17:49:54.000Z | [
"arxiv:2005.00547",
"region:us"
] | mrm8488 | null | null | 5 | 2 | 2022-03-02T23:29:22 | # GoEmotions
**GoEmotions** is a corpus of 58k carefully curated comments extracted from Reddit,
with human annotations to 27 emotion categories or Neutral.
* Number of examples: 58,009.
* Number of labels: 27 + Neutral.
* Maximum sequence length in training and evaluation datasets: 30.
On top of the raw data, we al... | 7,112 | [
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mrojas/abbreviation | 2021-06-07T20:56:39.000Z | [
"region:us"
] | mrojas | \ | \ | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mrojas/body | 2021-06-07T14:31:18.000Z | [
"region:us"
] | mrojas | \ | \ | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mrojas/finding | 2021-06-07T21:11:37.000Z | [
"region:us"
] | mrojas | \ | \ | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mrojas/procedure | 2021-06-07T21:02:47.000Z | [
"region:us"
] | mrojas | \ | \ | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mrp/Thai-Semantic-Textual-Similarity-Benchmark | 2021-11-29T06:15:34.000Z | [
"region:us"
] | mrp | null | null | 0 | 2 | 2022-03-02T23:29:22 | Sentence representation plays a crucial role in NLP downstream tasks such as NLI, text classification, and STS. Recent sentence representation training techniques require NLI or STS datasets. However, there are no equivalent Thai NLI or STS datasets for sentence representation training.
To address this problem we provi... | 1,839 | [
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msivanes/github-issues | 2021-12-03T21:24:58.000Z | [
"region:us"
] | msivanes | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mtfelix/datasetdemo | 2022-02-14T10:09:12.000Z | [
"region:us"
] | mtfelix | null | null | 0 | 2 | 2022-03-02T23:29:22 | this is my test demo | 20 | [
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mtlew/0001_Angry_test | 2022-02-18T08:12:41.000Z | [
"region:us"
] | mtlew | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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muhtasham/autonlp-data-Doctor_DE | 2022-10-27T18:52:42.000Z | [
"task_categories:text-classification",
"task_ids:text-scoring",
"language:de",
"region:us"
] | muhtasham | null | null | 0 | 2 | 2022-03-02T23:29:22 | ---
language:
- de
task_categories:
- text-classification
task_ids:
- text-scoring
---
# AutoNLP Dataset for project: Doctor_DE
## Table of content
- [Dataset Description](#dataset-description)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Field... | 2,046 | [
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mvip/tr_corpora_parliament_processed | 2022-02-24T07:31:09.000Z | [
"region:us"
] | mvip | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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mvip/tr_corpora_parliament_processed_non_hatted | 2022-02-23T13:30:15.000Z | [
"region:us"
] | mvip | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/auto-cats-and-dogs | 2021-07-13T07:32:53.000Z | [
"task_categories:other",
"auto-generated",
"image-classification",
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 |
---
task_categories:
- other
task_ids:
- other-image-classification
- image-classification
tags:
- auto-generated
- image-classification
---
# nateraw/auto-cats-and-dogs
Image Classification Dataset
## Usage
```python
from PIL import Image
from datasets import load_dataset
def pil_loader(path: str):
with open... | 640 | [
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nateraw/auto-exp-2 | 2021-07-13T07:10:47.000Z | [
"task_categories:other",
"auto-generated",
"image-classification",
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 |
---
task_categories:
- other
task_ids:
- other-image-classification
- image-classification
tags:
- auto-generated
- image-classification
---
# nateraw/auto-exp-2
Image Classification Dataset
## Usage
```python
from PIL import Image
from datasets import load_dataset
def pil_loader(path: str):
with open(path, '... | 624 | [
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nateraw/beans | 2022-10-20T18:41:18.000Z | [
"task_categories:other",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"license:mit",
"region:us"
] | nateraw | Beans is a dataset of images of beans taken in the field using smartphone
cameras. It consists of 3 classes: 2 disease classes and the healthy class.
Diseases depicted include Angular Leaf Spot and Bean Rust. Data was annotated
by experts from the National Crops Resources Research Institute (NaCRRI) in
Uganda and colle... | @ONLINE {beansdata,
author="Makerere AI Lab",
title="Bean disease dataset",
month="January",
year="2020",
url="https://github.com/AI-Lab-Makerere/ibean/"
} | 0 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- en
license:
- mit
multilinguality:
- monolingual
pretty_name: Beans
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- other
task_ids:
- other-other-image-classification
---
# Dataset Card for Beans
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nateraw/bulk-dummy | 2021-09-07T05:01:26.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/cats-and-dogs | 2021-06-02T20:32:52.000Z | [
"region:us"
] | nateraw | null | @Inproceedings (Conference){asirra-a-captcha-that-exploits-interest-aligned-manual-image-categorization,
author = {Elson, Jeremy and Douceur, John (JD) and Howell, Jon and Saul, Jared},
title = {Asirra: A CAPTCHA that Exploits Interest-Aligned Manual Image Categorization},
booktitle = {Proceedings of 14th A... | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/filings-10k | 2021-09-05T21:53:35.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/food101 | 2022-07-08T07:06:41.000Z | [
"task_categories:other",
"annotations_creators:crowdsourced",
"language_creators:crowdsourced",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:extended|other-foodspotting",
"language:en",
"license:unknown",
"region:us"
] | nateraw | null | @inproceedings{bossard14,
title = {Food-101 -- Mining Discriminative Components with Random Forests},
author = {Bossard, Lukas and Guillaumin, Matthieu and Van Gool, Luc},
booktitle = {European Conference on Computer Vision},
year = {2014}
} | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
language:
- en
license:
- unknown
multilinguality:
- monolingual
pretty_name: food101
size_categories:
- 10K<n<100K
source_datasets:
- extended|other-foodspotting
task_categories:
- other
task_ids:
- other-other-image-classification
paperswithco... | 3,968 | [
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nateraw/huggingpics-data-2 | 2021-11-23T04:06:40.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/imagefolder | 2021-08-31T07:21:19.000Z | [
"region:us"
] | nateraw | null | null | 1 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/img-demo | 2021-08-24T22:50:24.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/punks | 2022-02-28T18:55:06.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/rock_paper_scissors | 2021-07-13T16:07:15.000Z | [
"region:us"
] | nateraw | null | @ONLINE {rps,
author = "Laurence Moroney",
title = "Rock, Paper, Scissors Dataset",
month = "feb",
year = "2019",
url = "http://laurencemoroney.com/rock-paper-scissors-dataset"
} | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/test | 2021-06-02T03:07:46.000Z | [
"region:us"
] | nateraw | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nateraw/wit | 2021-09-27T17:41:33.000Z | [
"region:us"
] | nateraw | Wikipedia-based Image Text (WIT) Dataset is a large multimodal multilingual dataset. WIT is composed of a curated set
of 37.6 million entity rich image-text examples with 11.5 million unique images across 108 Wikipedia languages. Its
size enables WIT to be used as a pretraining dataset for multimodal machine learning... | @article{srinivasan2021wit,
title={WIT: Wikipedia-based Image Text Dataset for Multimodal Multilingual Machine Learning},
author={Srinivasan, Krishna and Raman, Karthik and Chen, Jiecao and Bendersky, Michael and Najork, Marc},
journal={arXiv preprint arXiv:2103.01913},
year={2021}
} | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nathanlsl/news | 2021-10-05T12:50:37.000Z | [
"region:us"
] | nathanlsl | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
naver-clova-conversation/klue-tc-dev-tsv | 2021-05-26T06:54:08.000Z | [
"region:us"
] | naver-clova-conversation | null | null | 0 | 2 | 2022-03-02T23:29:22 | This is a in-house development version of KLUE Topic Classification benchmark, as the test split is not released by the KLUE team.
We randomly split the original validation set (9,107 instances) into in-house validation set (5,107 instances) and the in-house test set (4,000 instances).
| 288 | [
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naver-clova-conversation/klue-tc-tsv | 2021-05-26T06:26:31.000Z | [
"region:us"
] | naver-clova-conversation | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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navjordj/nak_nb | 2021-11-18T18:39:13.000Z | [
"region:us"
] | navjordj | null | null | 0 | 2 | 2022-03-02T23:29:22 | Norsk Avis Korpus 2012-2019
* https://www.nb.no/sprakbanken/ressurskatalog/oai-nb-no-sbr-4/
Hentet ut artiklene på bokmål
Parset xml og hentet ut all teksten inni <p>-tags.
| 174 | [
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ncats/EpiSet4BinaryClassification | 2023-09-14T00:42:57.000Z | [
"annotations_creators:unknown",
"language_creators:unknown",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:unknown",
"language:en",
"license:cc-by-4.0",
"region:us"
] | ncats | INSERT DESCRIPTION | John JN, Sid E, Zhu Q. Recurrent Neural Networks to Automatically Identify Rare Disease Epidemiologic Studies from PubMed. AMIA Jt Summits Transl Sci Proc. 2021 May 17;2021:325-334. PMID: 34457147; PMCID: PMC8378621. | 0 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- unknown
language_creators:
- unknown
language:
- en
license:
- cc-by-4.0
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- unknown
paperswithcode_id: glue
pretty_name: GLUE (General Language Understanding Evaluation benchmark)
---
# DOCUMENTATION UPDATES IN PRO... | 6,290 | [
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ncats/EpiSet4NER-v1 | 2022-09-20T14:08:28.000Z | [
"task_ids:named-entity-recognition",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:100K<n<1M",
"language:en",
"license:other",
"region:us"
] | ncats | **REWRITE*
EpiSet4NER is a dataset generated from 620 rare disease abstracts labeled using statistical and rule-base methods. The test set was then manually corrected by a rare disease expert.
For more details see *INSERT PAPER* and https://github.com/ncats/epi4GARD/tree/master/EpiExtract4GARD#epiextract4gard | *REDO*
@inproceedings{wang2019crossweigh,
title={CrossWeigh: Training Named Entity Tagger from Imperfect Annotations},
author={Wang, Zihan and Shang, Jingbo and Liu, Liyuan and Lu, Lihao and Liu, Jiacheng and Han, Jiawei},
booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Proc... | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- train: programmatically-generated
- val: programmatically-generated
- test: programmatically-generated, expert-validated
language_creators:
- found
language:
- en
license:
- other
multilinguality:
- monolingual
size_categories:
- 100K<n<1M
task_categories:
- structure-prediction
task_ids:
-... | 8,892 | [
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ncats/GARD_EpiSet4TextClassification | 2021-11-20T01:02:09.000Z | [
"region:us"
] | ncats | INSERT DESCRIPTION | John JN, Sid E, Zhu Q. Recurrent Neural Networks to Automatically Identify Rare Disease Epidemiologic Studies from PubMed. AMIA Jt Summits Transl Sci Proc. 2021 May 17;2021:325-334. PMID: 34457147; PMCID: PMC8378621. | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ncduy/github-issues | 2021-12-04T15:38:19.000Z | [
"region:us"
] | ncduy | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.03790... |
ncoop57/csnc_human_judgement | 2021-11-06T14:15:56.000Z | [
"region:us"
] | ncoop57 | This new dataset is designed to solve this great NLP task and is crafted with a lot of care. | @InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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neelalex/raft-predictions | 2021-08-04T22:25:12.000Z | [
"benchmark:raft",
"region:us"
] | neelalex | \\nThis dataset contains a corpus of AI papers. The first task is to determine\\n whether or not a datapoint is an AI safety paper. The second task is to\\n determine what type of paper it is. | \\n@InProceedings{huggingface:dataset,
title = {A great new dataset},
author={huggingface, Inc.
},
year={2020}
} | 1 | 2 | 2022-03-02T23:29:22 | ---
benchmark: raft
---
# Dummy predictions for RAFT | 53 | [
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ngdiana/hu_severity | 2022-02-04T14:01:43.000Z | [
"region:us"
] | ngdiana | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ngdiana/uaspeech | 2022-02-04T11:49:17.000Z | [
"region:us"
] | ngdiana | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ngdiana/uaspeech_severity | 2022-02-04T12:53:47.000Z | [
"region:us"
] | ngdiana | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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ngdiana/uaspeech_severity_low | 2022-02-03T22:05:35.000Z | [
"region:us"
] | ngdiana | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nlpconnect/dpr-nq-reader-v2 | 2022-01-02T16:39:51.000Z | [
"region:us"
] | nlpconnect | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nlpconnect/ms_marco_subset_v2.1 | 2022-01-22T17:30:11.000Z | [
"region:us"
] | nlpconnect | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.016998291015625,
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0.0379... |
nlpufg/brwac-pt | 2021-07-12T23:25:24.000Z | [
"region:us"
] | nlpufg | null | null | 0 | 2 | 2022-03-02T23:29:22 | preprocessed removing mojibake texts | 36 | [
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0.0238... |
nlpufg/brwac | 2021-08-04T03:57:19.000Z | [
"region:us"
] | nlpufg | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
nlpufg/oscar-pt | 2021-07-12T23:26:15.000Z | [
"region:us"
] | nlpufg | null | null | 0 | 2 | 2022-03-02T23:29:22 | preprocessed removing mojibake texts | 36 | [
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nntadotzip/iuQAchatbot | 2022-01-20T07:25:26.000Z | [
"region:us"
] | nntadotzip | null | null | 0 | 2 | 2022-03-02T23:29:22 | annotations_creators:
- crowdsourced
language_creators:
- crowdsourced
- found
languages:
- en
licenses:
- cc-by-4.0
multilinguality:
- monolingual
paperswithcode_id: squad
pretty_name: SQuAD
size_categories:
- 10K<n<100K
source_datasets:
- extended|wikipedia
task_categories:
- question-answering
task_ids:
- extractive... | 323 | [
[
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0.03509521484375,
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-0.041717529296875,
0.0562... |
notional/notional-python | 2022-10-21T13:39:56.000Z | [
"task_ids:language-modeling",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:py",
"license:unknown",
"region:us"
] | notional | null | null | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language:
- py
language_creators:
- found
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- code-generation
- conditional-text-generation
task_ids:
- language-modeling
- code-generation
---
# Dataset ... | 2,565 | [
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0.00... |
nouamanetazi/ar_common_voice_processed | 2022-02-10T02:17:59.000Z | [
"region:us"
] | nouamanetazi | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
nouamanetazi/ar_opus100_processed | 2022-02-09T22:25:55.000Z | [
"region:us"
] | nouamanetazi | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nthngdy/bananas | 2022-01-05T10:19:33.000Z | [
"region:us"
] | nthngdy | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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nthngdy/openwebtext_split | 2022-02-08T22:01:10.000Z | [
"region:us"
] | nthngdy | An open-source replication of the WebText dataset from OpenAI. | @misc{Gokaslan2019OpenWeb,
title={OpenWebText Corpus},
author={Aaron Gokaslan*, Vanya Cohen*, Ellie Pavlick, Stefanie Tellex},
howpublished{\\url{http://Skylion007.github.io/OpenWebTextCorpus}},
year={2019}
} | 1 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
ntutexas/amazon | 2021-12-07T01:17:14.000Z | [
"region:us"
] | ntutexas | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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0.052520751953125,
0.005062103271484375,
0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
nucklehead/ht-voice-dataset | 2021-04-14T12:34:47.000Z | [
"region:us"
] | nucklehead | null | null | 0 | 2 | 2022-03-02T23:29:22 | # Ansanb done vwa an Kreyòl pou antrene DeepSPeech.
Dataset sa a gen plis pase 7 è tan anrejistreman vwa ak prèske 100 moun an Kreyòl pou bati sistèm ASR ak TTS pou lang Kreyòl la.
Pifò nan done yo soti nan "CMU Haitian Creole Speech Recognition Database" la.
Done sa yo gentan filtre epi òganize pou ka antrene modè... | 527 | [
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-0.047821044921875,
0.021057128... |
nykodmar/cs_corpora_parliament_processed | 2022-02-21T08:54:20.000Z | [
"region:us"
] | nykodmar | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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0.0379... |
ought/raft-submission | 2023-04-27T22:20:54.000Z | [
"region:us"
] | ought | null | null | 3 | 2 | 2022-03-02T23:29:22 | # RAFT Submission Template
Welcome to the [RAFT benchmark](https://raft.elicit.org/)! RAFT is a few-shot classification benchmark that tests language models:
- across multiple domains (lit review, tweets, customer interaction, etc.)
- on economically valuable classification tasks (someone inherently cares about the t... | 7,064 | [
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... |
pasinit/scotus | 2021-09-23T14:18:55.000Z | [
"region:us"
] | pasinit | Dataset extracted from case laws of Supreme Court of United States. | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
patrickvonplaten/common_voice_6_tr | 2021-10-28T22:35:25.000Z | [
"region:us"
] | patrickvonplaten | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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patrickvonplaten/common_voice_processed_turkish | 2021-09-21T14:34:57.000Z | [
"region:us"
] | patrickvonplaten | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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patrickvonplaten/helena_coworking | 2021-11-08T22:17:00.000Z | [
"region:us"
] | patrickvonplaten | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
patrickvonplaten/librispeech_local | 2021-08-12T00:10:54.000Z | [
"region:us"
] | patrickvonplaten | LibriSpeech is a corpus of approximately 1000 hours of read English speech with sampling rate of 16 kHz,
prepared by Vassil Panayotov with the assistance of Daniel Povey. The data is derived from read
audiobooks from the LibriVox project, and has been carefully segmented and aligned.87
Note that in order to limit the ... | @inproceedings{panayotov2015librispeech,
title={Librispeech: an ASR corpus based on public domain audio books},
author={Panayotov, Vassil and Chen, Guoguo and Povey, Daniel and Khudanpur, Sanjeev},
booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on},
pages={5206--... | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
patrickvonplaten/sensitive_data_sv | 2022-01-20T17:06:06.000Z | [
"region:us"
] | patrickvonplaten | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
persiannlp/parsinlu_translation_fa_en | 2022-10-24T17:01:27.000Z | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:expert-generated",
"multilinguality:fa",
"multilinguality:en",
"size_categories:1K<n<10K",
"source_datasets:extended",
"language:fa",
"license:cc-by-nc-sa-4.0",
"arxiv:2012.06154",
"region:us"
] | persiannlp | A Persian translation dataset (Persian -> English). | @article{huggingface:dataset,
title = {ParsiNLU: A Suite of Language Understanding Challenges for Persian},
authors = {Khashabi, Daniel and Cohan, Arman and Shakeri, Siamak and Hosseini, Pedram and Pezeshkpour, Pouya and Alikhani, Malihe and Aminnaseri, Moin and Bitaab, Marzieh and Brahman, Faeze and Ghazarian,... | 0 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- fa
license:
- cc-by-nc-sa-4.0
multilinguality:
- fa
- en
size_categories:
- 1K<n<10K
source_datasets:
- extended
task_categories:
- translation
task_ids:
- translation
---
# Dataset Card for PersiNLU (Machine Translation)
#... | 4,322 | [
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peterhsu/github-issues | 2022-01-07T09:16:29.000Z | [
"region:us"
] | peterhsu | null | null | 0 | 2 | 2022-03-02T23:29:22 | annotations_creators:
- no-annotation
language_creators:
- found
languages:
- en
licenses:
- unknown
multilinguality:
- monolingual
pretty_name: Practice
size_categories:
- unknown
source_datasets:
- original
task_categories:
- text-classification
- text-retrieval
task_ids:
- multi-class-classification
- multi-label-cl... | 2,696 | [
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philschmid/prompted-germanquad | 2022-01-24T14:20:21.000Z | [
"region:us"
] | philschmid | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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phoelti/squad_dev | 2021-12-26T20:19:19.000Z | [
"region:us"
] | phoelti | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
phongdtd/youtube_casual_audio | 2022-11-01T13:23:24.000Z | [
"task_categories:automatic-speech-recognition",
"source_datasets:extended|youtube",
"region:us"
] | phongdtd | \ | null | 3 | 2 | 2022-03-02T23:29:22 | ---
multilinguality:
vi:
- 190K<n<200K
source_datasets:
- extended|youtube
task_categories:
- automatic-speech-recognition
task_ids: []
Pretty_name: Youtube Casual Audio
Annotations_creators:
- crowdsourced
Language_creators:
- datlq
Languages:
- vi
Licenses:
- cc0-1.0
---
# Dataset Card for common_voice
## Table... | 4,081 | [
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0.0... |
phonlab-tcd/cngv1 | 2021-09-02T16:51:12.000Z | [
"region:us"
] | phonlab-tcd | Corpus of written Irish. | @article{ite2003corpas,
title={Corpas Náisiúnta na Gaeilge/National Corpus of Irish, Volume 1},
author={Institiúid Teangeolaíochta Éireann},
journal={Dublin: ITÉ},
year={2003}
} | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
phonlab-tcd/corpuscrawler-ga | 2021-09-05T09:59:34.000Z | [
"region:us"
] | phonlab-tcd | Irish web corpus, crawled with Corpus Crawler.
Uses a list of URLs, collected by the crawler, to
retrieve the files from the crawler's cache. | null | 1 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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pierreguillou/test_datasetdict | 2021-12-07T11:04:58.000Z | [
"region:us"
] | pierreguillou | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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pierresi/cord | 2021-10-13T16:47:07.000Z | [
"region:us"
] | pierresi | https://github.com/clovaai/cord/ | @article{park2019cord,
title={CORD: A Consolidated Receipt Dataset for Post-OCR Parsing},
author={Park, Seunghyun and Shin, Seung and Lee, Bado and Lee, Junyeop and Surh, Jaeheung and Seo, Minjoon and Lee, Hwalsuk}
booktitle={Document Intelligence Workshop at Neural Information Processing Systems}
year={2019}
} | 0 | 2 | 2022-03-02T23:29:22 | CORD: A Consolidated Receipt Dataset for Post-OCR Parsing. | 59 | [
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polinaeterna/benchmark_dataset | 2022-03-02T13:01:47.000Z | [
"region:us"
] | polinaeterna | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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polinaeterna/test_opus | 2022-02-03T10:40:34.000Z | [
"region:us"
] | polinaeterna | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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prajin/ne_corpora_parliament_processed | 2022-01-30T05:38:18.000Z | [
"region:us"
] | prajin | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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pritamdeka/cord-19-abstract | 2022-02-01T23:58:54.000Z | [
"region:us"
] | pritamdeka | null | null | 1 | 2 | 2022-03-02T23:29:22 | # Dataset Card for [pritamdeka/cord-19-abstract]
## Dataset Description
### Dataset Summary
This is a modified [cord19](https://huggingface.co/datasets/cord19) dataset which contains only the abstract field. This can be used directly for language modelling tasks.
### Languages
English
### Citation Information... | 870 | [
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projecte-aina/catalan_general_crawling | 2023-09-13T12:47:07.000Z | [
"task_categories:fill-mask",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1M<n<10M",
"source_datasets:original",
"language:ca",
"license:cc-by-4.0",
"arxiv:2107.07903",
"region:us"
] | projecte-aina | The Catalan General Crawling Corpus is a 435-million-token web corpus of Catalan built from the web. It has been obtained by crawling the 500 most popular .cat and .ad domains during July 2020. It consists of 434.817.705 tokens, 19.451.691 sentences and 1.016.114 documents. Documents are separated by single new lines. ... | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de ... | 0 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-4.0
multilinguality:
- monolingual
pretty_name: Catalan General Crawling
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- fill-mask
task_ids: []
---
# Dataset Card for Catalan General Crawling... | 9,825 | [
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projecte-aina/catalan_textual_corpus | 2023-09-13T12:48:11.000Z | [
"task_categories:fill-mask",
"annotations_creators:no-annotation",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10M<n<100M",
"source_datasets:original",
"source_datasets:extended|opus_dogc",
"source_datasets:extended|cawac",
"source_datasets:extended|oscar",
"source_d... | projecte-aina | The Catalan Textual Corpus is a 1760-million-token web corpus of Catalan built from several sources: existing corpus such as DOGC, CaWac (non-dedup version), Oscar (unshuffled version), Open Subtitles, Catalan Wikipedia; and three brand new crawlings: the Catalan General Crawling, obtained by crawling the 500 most popu... | @inproceedings{armengol-estape-etal-2021-multilingual,
title = "Are Multilingual Models the Best Choice for Moderately Under-resourced Languages? {A} Comprehensive Assessment for {C}atalan",
author = "Armengol-Estap{\'e}, Jordi and
Carrino, Casimiro Pio and
Rodriguez-Penagos, Carlos and
de ... | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- no-annotation
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: Catalan Textual Corpus
size_categories:
- 10M<n<100M
source_datasets:
- original
- extended|opus_dogc
- extended|cawac
- extended|oscar
- extended|open_subtitles
- exte... | 6,047 | [
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projecte-aina/vilaquad | 2023-09-13T12:43:28.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:ca",
"license:cc-by-sa-4.0",
"arxiv:2107.07903",
"arxiv:1606.05250"... | projecte-aina | This dataset contains 2095 of Catalan language news articles along with 1 to 5 questions referring to each fragment (or context).
VilaQuad articles are extracted from the daily Vilaweb (www.vilaweb.cat) and used under CC-by-nc-sa-nd (https://creativecommons.org/licenses/by-nc-nd/3.0/deed.ca) licence.
This dataset ca... | Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
VilaQuAD: an extractive QA dataset for catalan, from Vilaweb newswire text
[Data set]. Zenodo. https://doi.org/10.5281/zenodo.4562337 | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: VilaQuAD
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# Dataset Card for VilaQuAD
##... | 8,157 | [
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projecte-aina/viquiquad | 2023-09-13T12:44:04.000Z | [
"task_categories:question-answering",
"task_ids:extractive-qa",
"annotations_creators:expert-generated",
"language_creators:found",
"multilinguality:monolingual",
"size_categories:10K<n<100K",
"source_datasets:original",
"language:ca",
"license:cc-by-sa-4.0",
"arxiv:2107.07903",
"arxiv:1606.0525... | projecte-aina | ViquiQuAD: an extractive QA dataset from Catalan Wikipedia.
This dataset contains 3111 contexts extracted from a set of 597 high quality original (no translations)
articles in the Catalan Wikipedia "Viquipèdia" (ca.wikipedia.org), and 1 to 5 questions with their
answer for each fragment. Viquipedia articles are used u... | Rodriguez-Penagos, Carlos Gerardo, & Armentano-Oller, Carme. (2021).
ViquiQuAD: an extractive QA dataset from Catalan Wikipedia (Version ViquiQuad_v.1.0.1)
[Data set]. Zenodo. http://doi.org/10.5281/zenodo.4761412 | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- found
language:
- ca
license:
- cc-by-sa-4.0
multilinguality:
- monolingual
pretty_name: ViquiQuAD
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
---
# ViquiQuAD, An extractive Q... | 7,538 | [
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psrpsj/stop_words | 2021-12-14T18:02:24.000Z | [
"region:us"
] | psrpsj | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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pstroe/cc100-latin | 2022-11-02T14:28:12.000Z | [
"region:us"
] | pstroe | null | null | 4 | 2 | 2022-03-02T23:29:22 | ## Latin part of cc100 corpus
This dataset contains parts of the Latin part of the [cc100](http://data.statmt.org/cc-100/) dataset. It was used to train a [RoBERTa-based LM model](https://huggingface.co/pstroe/roberta-base-latin-cased) with huggingface.
### Preprocessing
I undertook the following preprocessing steps:... | 1,222 | [
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... |
quarter100/boolq_log | 2021-12-26T19:12:23.000Z | [
"region:us"
] | quarter100 | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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-0.0604248046875,
0.037... |
radhakri119/sv_corpora_parliament_processed | 2022-01-19T16:26:45.000Z | [
"region:us"
] | radhakri119 | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0170135498046875,
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-0.0604248046875,
0.0379028... |
rajeshradhakrishnan/malayalam_news | 2022-07-04T05:57:19.000Z | [
"region:us"
] | rajeshradhakrishnan | The AI4Bharat-IndicNLP dataset is an ongoing effort to create a collection of large-scale,
general-domain corpora for Indian languages. Currently, it contains 2.7 billion words for 10 Indian languages from two language families.
We share pre-trained word embeddings trained on these corpora.
We create news article cat... | @article{kunchukuttan2020indicnlpcorpus,
title={AI4Bharat-IndicNLP Corpus: Monolingual Corpora and Word Embeddings for Indic Languages},
author={Anoop Kunchukuttan and Divyanshu Kakwani and Satish Golla and Gokul N.C. and Avik Bhattacharyya and Mitesh M. Khapra and Pratyush Kumar},
year={2020},
journal=... | 1 | 2 | 2022-03-02T23:29:22 | ## IndicNLP News Article Classification Dataset
We used the IndicNLP text corpora to create classification datasets comprising news articles and their categories for 9 languages. The dataset is balanced across classes. The following table contains the statistics of our dataset:
| Language | Classes ... | 1,626 | [
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0.0196685791015625,
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-0.052398681640625,
-0.0418701171... |
ramitsurana/sanskrit | 2021-12-26T11:44:08.000Z | [
"region:us"
] | ramitsurana | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379028... |
ramybaly/nerd | 2021-08-20T04:48:51.000Z | [
"region:us"
] | ramybaly | Recently, considerable literature has grown up around the theme of few-shot named entity recognition (NER), but little published benchmark
data specifically focused on the practical and challenging task. Current approaches collect existing supervised NER datasets and reorganize
them into the few-shot setting for empiri... | @article{ding2021few,
title={Few-NERD: A Few-Shot Named Entity Recognition Dataset},
author={Ding, Ning and Xu, Guangwei and Chen, Yulin and Wang, Xiaobin and Han, Xu and Xie, Pengjun and Zheng, Hai-Tao and Liu, Zhiyuan},
journal={arXiv preprint arXiv:2105.07464},
year={2021}
} | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379028... |
rbawden/DiaBLa | 2022-10-25T14:21:10.000Z | [
"task_categories:translation",
"annotations_creators:expert-generated",
"language_creators:crowdsourced",
"multilinguality:translation",
"size_categories:1K<n<10K",
"source_datasets:original",
"language:en",
"language:fr",
"license:cc-by-sa-4.0",
"region:us"
] | rbawden | null | null | 1 | 2 | 2022-03-02T23:29:22 | ---
annotations_creators:
- expert-generated
language_creators:
- crowdsourced
language:
- en
- fr
license:
- cc-by-sa-4.0
multilinguality:
- translation
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
pretty_name: DiaBLa
language_bcp47:
- en-UK
- fr-FR
---
# Dataset... | 12,878 | [
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0.... |
ronaldvanos/testdata | 2021-11-09T12:56:07.000Z | [
"region:us"
] | ronaldvanos | null | null | 0 | 2 | 2022-03-02T23:29:22 | #this is a test dataset and should not be used by anyone
#i am not the owner of the data
| 89 | [
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... |
roskoN/dstc8-reddit-corpus | 2021-04-23T00:19:35.000Z | [
"region:us"
] | roskoN | The DSTC8 dataset as provided in the original form.
The only difference is that the splits are in separate zip files.
In the orignal output it is one big archive containing all splits. | @article{lee2019multi,
title={Multi-domain task-completion dialog challenge},
author={Lee, S and Schulz, H and Atkinson, A and Gao, J and Suleman, K and El Asri, L and Adada, M and Huang, M and Sharma, S and Tay, W and others},
journal={Dialog system technology challenges},
volume={8},
pages={9},
year={2019... | 0 | 2 | 2022-03-02T23:29:22 | # DSTC8 Reddit Corpus
The data is based of the following repository:
> [https://github.com/microsoft/dstc8-reddit-corpus](https://github.com/microsoft/dstc8-reddit-corpus)
The dataset is created is a convenience to enable skipping the lengthy extraction process. | 265 | [
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0.02911376953... |
rubrix/cleanlab-label_errors | 2022-02-24T19:43:17.000Z | [
"region:us"
] | rubrix | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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rubrix/imdb_spacy-ner | 2022-02-22T11:10:59.000Z | [
"region:us"
] | rubrix | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
rubrix/sentiment-banking | 2022-02-28T18:22:25.000Z | [
"region:us"
] | rubrix | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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s3h/arabic-gec | 2021-12-06T18:22:00.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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0.0379... |
s3h/custom-qalb-classification | 2021-11-29T17:09:22.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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s3h/customized-qalb-v2 | 2021-11-30T12:32:51.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
s3h/customized-qalb | 2021-12-06T18:03:24.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
s3h/gec-arabic | 2021-12-31T11:00:34.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.016998291015625,
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0.0379... |
s3h/gec-cleaned | 2021-12-20T19:01:32.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.016998291015625,
-0.052093505859375,
-0.014984130859375,
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0.0379... |
s3h/poc-gec | 2021-12-20T16:36:38.000Z | [
"region:us"
] | s3h | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
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0.0379... |
safik/github-issues-comments | 2022-02-13T10:23:03.000Z | [
"region:us"
] | safik | null | null | 0 | 2 | 2022-03-02T23:29:22 | Entry not found | 15 | [
[
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0.0513916015625,
0.016998291015625,
-0.052093505859375,
-0.014984130859375,
-0.060394287109375,
0.0379... |
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