datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
trec-covid
TRECCOVID
An MTEB dataset
Massive Text Embedding Benchmark
TRECCOVID is an ad-hoc search challenge based on the COVID-19 dataset containing scientific articles related to the COVID-19 pandemic.
Task category
t2t
Domains
Medical, Academic, Written
Reference
https://ir.nist.gov/covidSubmit/index.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["TRECCOVID"])… See the full description on the dataset page: https://huggingface.co/datasets/mteb/trec-covid.trec-covid
Dataset Card for BEIR Benchmark
trec-covid is one of the datasets from the Bio-Medical Retrieval task within BEIR, measuring scientific article retrieval for a given query on COVID-19.
Dataset Summary
BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/trec-covid.trec-covid-qrels
Dataset Card for BEIR Benchmark
Dataset Summary
BEIR is a heterogeneous benchmark that has been built from 18 diverse datasets representing 9 information retrieval tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018
Bio-Medical IR: TREC-COVID, BioASQ, NFCorpus
News Retrieval: TREC-NEWS, Robust04
Argument Retrieval: Touche-2020, ArguAna
Duplicate Question Retrieval: Quora, CqaDupstack
Citation-Prediction: SCIDOCS
Tweet… See the full description on the dataset page: https://huggingface.co/datasets/BeIR/trec-covid-qrels.covid19_emergency_event
Dataset Card for EXCEPTIUS Corpus
Dataset Summary
This dataset presents a new corpus of legislative documents from 8 European countries (Beglium, France, Hunary, Italy, Netherlands, Norway, Poland, UK) in 7 languages (Dutch, English, French, Hungarian, Italian, Norwegian Bokmål, Polish) manually annotated for exceptional measures against COVID-19. The annotation was done on the sentence level.
Supported Tasks and Leaderboards
The dataset can be used for… See the full description on the dataset page: https://huggingface.co/datasets/joelniklaus/covid19_emergency_event.ClusTREC-Covid
CLUSTREC-COVID: A Topical Clustering Benchmark for COVID-19 Scientific Research
Dataset Summary
CLUSTREC-COVID is a modified version of the TREC-COVID dataset, transformed into a topical clustering benchmark. The dataset consists of titles and abstracts from scientific papers about COVID-19 research, covering a diverse range of research topics. Each document in the dataset is assigned to a specific subtopic, making it ideal for use in document clustering and topic… See the full description on the dataset page: https://huggingface.co/datasets/Uri-ka/ClusTREC-Covid.COVID-19-disinformation
COVID-19 Infodemic Multilingual Dataset
This repository contains a multilingual dataset related to the COVID-19 infodemic, annotated with fine-grained labels. The dataset is curated to address questions of interest to journalists, fact-checkers, social media platforms, policymakers, and the general public. The dataset includes tweets in Arabic, Bulgarian, Dutch, and English, focusing on both binary (misinformation detection) and multiclass classification (different types of… See the full description on the dataset page: https://huggingface.co/datasets/QCRI/COVID-19-disinformation.CovidRetrieval
CovidRetrieval
An MTEB dataset
Massive Text Embedding Benchmark
COVID-19 news articles
Task category
t2t
Domains
Medical, Entertainment
Reference
https://arxiv.org/abs/2203.03367
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb
task = mteb.get_tasks(["CovidRetrieval"])
evaluator = mteb.MTEB(task)
model = mteb.get_model(YOUR_MODEL)
evaluator.run(model)
To learn more about how to run… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CovidRetrieval.covid-qa
ConTEB - Covid-QA
This dataset is part of ConTEB (Context-aware Text Embedding Benchmark), designed for evaluating contextual embedding model capabilities. It focuses on the theme of Healthcare, particularly stemming from articles about the COVID-19 pandemic.
Dataset Summary
This dataset was designed to elicit contextual information. It is built upon the COVID-QA dataset. To build the corpus, we start from the pre-existing collection documents, extract the text, and chunk… See the full description on the dataset page: https://huggingface.co/datasets/illuin-conteb/covid-qa.COVID-QA-unique-context-test-10-percent-validation-10-percent
Dataset Card for "COVID-QA-unique-context-test-10-percent-validation-10-percent"
More Information needed
CovidRetrieval
Dataset Card for "CovidRetrieval"
More Information needed
covid_qa_deepset
Dataset Card for COVID-QA
Dataset Summary
COVID-QA is a Question Answering dataset consisting of 2,019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19.
A total of 147 scientific articles from the CORD-19 dataset were annotated by 15 experts.
Supported Tasks and Leaderboards
[More Information Needed]
Languages
The text in the dataset is in English.
Dataset Structure
Data… See the full description on the dataset page: https://huggingface.co/datasets/deepset/covid_qa_deepset.trec-covid-decontaminated
trec-covid (Decontaminated)
A decontaminated version of the trec-covid dataset from the BEIR benchmark, with samples found in the mgte-en pre-training dataset removed.
Decontamination methodology
Contamination was detected using a two-pass approach against the full mgte-en dataset (484 GB, 1,235 parquet files):
Pass 1: Exact hash matching
All texts (queries and corpus documents) were normalized (lowercased, unicode NFKD, whitespace collapsed) and hashed with… See the full description on the dataset page: https://huggingface.co/datasets/lightonai/trec-covid-decontaminated.CovidQA
CovidQA
An MTEB dataset
Massive Text Embedding Benchmark
LMEB semantic retrieval task based on COVID-QA, retrieving relevant biomedical evidence for COVID-19 questions.
Task category
Retrieval (text-to-text)
Domains
Academic, Medical, Written
Reference
LMEB: Long-horizon Memory Embedding Benchmark
Source datasets:
KaLM-Embedding/LMEB
How to evaluate on this task
You can evaluate an embedding model on this dataset using the following code:
import mteb… See the full description on the dataset page: https://huggingface.co/datasets/mteb/CovidQA.covid19-ct-seg
COVID-19 CT Segmentation Dataset
Dataset Description
The COVID-19 CT Segmentation dataset for lung and COVID-19 infection segmentation from CT scans. This dataset contains CT scans with dense segmentation annotations.
Dataset Details
Modality: CT
Target: left lung, right lung, COVID-19 infection
Format: NIfTI (.nii.gz)
Dataset Structure
Each sample in the JSONL file contains:
{
"image": "path/to/image.nii.gz",
"mask":… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/covid19-ct-seg.CovidRetrieval-qrels
Dataset Card for "CovidRetrieval-qrels"
More Information needed
covid_tweets_japanese
Dataset Card for COVID-19 日本語Twitterデータセット (COVID-19 Japanese Twitter Dataset)
Dataset Summary
53,640 Japanese tweets with annotation if a tweet is related to COVID-19 or not. The annotation is by majority decision by 5 - 10 crowd workers. Target tweets include "COVID" or "コロナ". The period of the tweets is from around January 2020 to around June 2020. The original tweets are not contained. Please use Twitter API to get them, for example.
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/community-datasets/covid_tweets_japanese.the-reddit-covid-datasetThis dataset attempts to capture the full extent of COVID-19 discussion across the entire site of Reddit. All posts and comments found to mention the term 'COVID' as of 2021-10-25 have been gathered from the site.covid_fake_newsConstraint@AAAI2021 - COVID19 Fake News Detection in English
@misc{patwa2020fighting,
title={Fighting an Infodemic: COVID-19 Fake News Dataset},
author={Parth Patwa and Shivam Sharma and Srinivas PYKL and Vineeth Guptha and Gitanjali Kumari and Md Shad Akhtar and Asif Ekbal and Amitava Das and Tanmoy Chakraborty},
year={2020},
eprint={2011.03327},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
COVID-19_weibo_emotionCOVID-19 Epidemic Weibo Emotional Dataset, the content of Weibo in this dataset is the epidemic Weibo obtained by using relevant keywords to filter during the epidemic, and its content is related to COVID-19.
Each tweet is labeled as one of the following six categories: neutral (no emotion), happy (positive), angry (angry), sad (sad), fear (fear), surprise (surprise)
The COVID-19 Weibo training dataset includes 8,606 Weibos, the validation set contains 2,000 Weibos, and the test dataset… See the full description on the dataset page: https://huggingface.co/datasets/souljoy/COVID-19_weibo_emotion.CovidQAChunkRetrievalCOVID-19-20
COVID-19-20 Lung CT Lesion Segmentation Challenge
Non-contrast chest CT with radiologist-verified binary COVID-19 lesion
masks, from the MICCAI 2020 COVID-19 Lung CT Lesion Segmentation Challenge
(a.k.a. COVID-19-20).
⚠️ Scope of this upload (training split only)
This repository contains the public training split: 199 CT volumes, each with a
ground-truth lesion mask. It is a faithful subset of the full challenge:
Split
Cases
Masks
Included here
Train… See the full description on the dataset page: https://huggingface.co/datasets/MedOtter/COVID-19-20.africa-burkinafaso-covid19-subnational
Burkina Faso: Coronavirus (Covid-19) Subnational | Africa (original)
Size category: 1K<n<10K - Formats: parquet - Sector: health - Engineered by Electric Sheep Africa
TL;DR
This dataset is part of the Electric Sheep Africa catalog on Hugging Face. It is indexed for African data discovery with standardized metadata, loading guidance, provenance notes, and analyst-oriented context.
What This Dataset Covers
Health datasets help researchers examine… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-burkinafaso-covid19-subnational.trec-covid_CS-MTEB
TREC-COVID CS-MTEB
An MTEB dataset
Massive Text Embedding Benchmark
Code-switching version of mteb/trec-covid, with queries rewritten in Chinese-English, Japanese-English, German-English, Spanish-English, Korean-English, French-English, Italian-English, Portuguese-English, Dutch-English code-switching styles.
Dataset Structure
The dataset contains the following configurations:
From original dataset (unchanged):
corpus: Original corpus documents
default: Original relevance… See the full description on the dataset page: https://huggingface.co/datasets/UTokyo-Yokoya-Lab/trec-covid_CS-MTEB.covid19-cxr-bm3d-denoising
Dataset Card for COVID-19 CXR BM3D Denoising
Dataset Summary
This dataset contains paired chest X-ray (CXR) images for supervised image denoising.It is built from the COVID-19 Radiography Database and, for each original CXR, provides:
the original (clean) image,
a synthetically noisy version,
a BM3D-denoised version (pseudo–ground truth).
The goal is to train and evaluate models that learn to reproduce BM3D from noisy CXRs.
Important: This is a derived… See the full description on the dataset page: https://huggingface.co/datasets/adlito/covid19-cxr-bm3d-denoising.beir-trec-covid
TRECCOVID — BEIR, unified schema
A normalised copy of the dataset behind the mteb task TRECCOVID, one of the tasks of the BEIR benchmark as mteb defines it. Same queries, documents
and relevance judgements as the benchmark evaluates — reshaped into one strict schema shared by every dataset
in this collection.
Source
mteb/trec-covid @ bb9466bac815 (the revision pinned in mteb)
Domain · languages
biomedical · eng
Queries / documents / qrels
50 / 171,332 / 66,336… See the full description on the dataset page: https://huggingface.co/datasets/Hyukkyu/beir-trec-covid.trec-covid-vn
TRECCOVID-VN
An MTEB dataset
Massive Text Embedding Benchmark
A translated dataset from TRECCOVID is an ad-hoc search challenge based on the COVID-19 dataset containing scientific articles related to the COVID-19 pandemic. The process of creating the VN-MTEB (Vietnamese Massive Text Embedding Benchmark) from English samples involves a new automated system: - The system uses large language models (LLMs), specifically Coherence's Aya model, for translation. - Applies advanced embedding… See the full description on the dataset page: https://huggingface.co/datasets/GreenNode/trec-covid-vn.medical-scan-covidbenchmark-trec-covidmteb-nl-COVID-19-disinformationThis dataset contains Dutch tweets that were annotated for fine-grained disinformation analysis.
Citation Information
If you find our paper, benchmark or models helpful, please consider cite as follows:
@misc{banar2025mtebnle5nlembeddingbenchmark,
title={MTEB-NL and E5-NL: Embedding Benchmark and Models for Dutch},
author={Nikolay Banar and Ehsan Lotfi and Jens Van Nooten and Cristina Arhiliuc and Marija Kliocaite and Walter Daelemans},
year={2025}… See the full description on the dataset page: https://huggingface.co/datasets/clips/mteb-nl-COVID-19-disinformation.africa-madagascar-africa-covid-19-cumulative-infections-national-795398fb
Africa: Covid-19 Cumulative infections (National) | Africa (Madagascar official open data)
996 rows - 1 Africa country - not-applicable - Repackaged by Electric Sheep Africa
TL;DR
This dataset packages one official CSV resource from Madagascar as
ML-ready Parquet. The source file is the provenance boundary; all usable
indicators or tabular columns from the resource stay together in this repo.
About the source
Source: Africa: Covid-19… See the full description on the dataset page: https://huggingface.co/datasets/electricsheepafrica/africa-madagascar-africa-covid-19-cumulative-infections-national-795398fb.