datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
Nemotron-ClimbMix
ClimbMix Dataset
🚀 Creating the highest-quality pre-training datasets for LLMs 🌟
📄 PAPER
🤗 CLIMBLAB
🤗 CLIMBMIX
🏠 HOMEPAGE
Figure 1: Continuously training a 1B model yields a 2.0% improvement over Llama-3.2-1B, demonstrating a more efficient scaling trend compared to prior models.
Figure 2: Pre-training a 1B model from scratch on ClimbMix shows better scaling effects than training on other datasets.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-ClimbMix.beir-nl-cqadupstack
Dataset Card for BEIR-NL Benchmark
Dataset Summary
BEIR-NL is a Dutch-translated version of the BEIR benchmark, a diverse and heterogeneous collection of datasets covering various domains from biomedical and financial texts to general web content. Our benchmark is integrated into the Massive Multilingual Text Embedding Benchmark (MMTEB).
BEIR-NL contains the following tasks:
Fact-checking: FEVER, Climate-FEVER, SciFact
Question-Answering: NQ, HotpotQA, FiQA-2018… See the full description on the dataset page: https://huggingface.co/datasets/clips/beir-nl-cqadupstack.CLIcK
CLIcK 🇰🇷🧠
A Benchmark Dataset of Cultural and Linguistic Intelligence in Korean
Introduction 🎉
CLIcK (Cultural and Linguistic Intelligence in Korean) is a comprehensive dataset designed to evaluate cultural and linguistic intelligence in the context of Korean language models. In an era where diverse language models are continually emerging, there is a pressing need for robust evaluation datasets, especially for non-English languages like Korean. CLIcK… See the full description on the dataset page: https://huggingface.co/datasets/EunsuKim/CLIcK.ClimbMixClimbMix is a high-quality pre-training corpus released by NVIDIA. Here is the description:
ClimbMix is a compact yet powerful 400-billion-token dataset designed for efficient pre-training that delivers superior performance under an equal token budget. It was introduced in this paper.
We proposed a new algorithm to filter and mix the dataset. First, we grouped the data into 1,000 groups based on topic information. Then we applied two classifiers: one to detect advertisements and another to… See the full description on the dataset page: https://huggingface.co/datasets/OptimalScale/ClimbMix.climate-fever
ClimateFEVER
An MTEB dataset
Massive Text Embedding Benchmark
CLIMATE-FEVER is a dataset adopting the FEVER methodology that consists of 1,535 real-world claims (queries) regarding climate-change. The underlying corpus is the same as FVER.
Task category
t2t
Domains
Encyclopaedic, Written
Reference
https://www.sustainablefinance.uzh.ch/en/research/climate-fever.html
How to evaluate on this task
You can evaluate an embedding model on this dataset using… See the full description on the dataset page: https://huggingface.co/datasets/mteb/climate-fever.PMC-Clinical
🔭 Overview
R2MED: First Reasoning-Driven Medical Retrieval Benchmark
R2MED is a high-quality, high-resolution synthetic information retrieval (IR) dataset designed for medical scenarios. It contains 876 queries with three retrieval tasks, five medical scenarios, and twelve body systems.
Dataset
#Q
#D
Avg. Pos
Q-Len
D-Len
Biology
103
57359
3.6
115.2
83.6
Bioinformatics77
47473
2.9
273.8
150.5
Medical Sciences
88
34810
2.8
107.1
122.7
MedXpertQA-Exam
97… See the full description on the dataset page: https://huggingface.co/datasets/R2MED/PMC-Clinical.IIYi-Clinical
🔭 Overview
R2MED: First Reasoning-Driven Medical Retrieval Benchmark
R2MED is a high-quality, high-resolution synthetic information retrieval (IR) dataset designed for medical scenarios. It contains 876 queries with three retrieval tasks, five medical scenarios, and twelve body systems.
Dataset
#Q
#D
Avg. Pos
Q-Len
D-Len
Biology
103
57359
3.6
115.2
83.6
Bioinformatics77
47473
2.9
273.8
150.5
Medical Sciences
88
34810
2.8
107.1
122.7
MedXpertQA-Exam
97… See the full description on the dataset page: https://huggingface.co/datasets/R2MED/IIYi-Clinical.augmented-clinical-notes
Augmented Clinical Notes
The Augmented Clinical Notes dataset is an extension of existing datasets containing 30,000 triplets from different sources:
Real clinical notes (PMC-Patients): Clinical notes correspond to patient summaries from the PMC-Patients dataset, which are extracted from PubMed Central case studies.
Synthetic dialogues (NoteChat): Synthetic patient-doctor conversations were generated from clinical notes using GPT 3.5.
Structured patient information (ours): From… See the full description on the dataset page: https://huggingface.co/datasets/AGBonnet/augmented-clinical-notes.CUREv1
Dataset Card for CUREv1
Clinia's CURE, Clinical Understanding & Retrieval Evaluation
Evaluate your retriever’s performance on query-passage pairs curated by medical professionals, across 10 disciplines and 3 cross-lingual settings.
Dataset Details
Uses
Direct Use
You can use the following code to load the dataset:
from datasets import load_dataset
language_setting = "en"
domain = "dermatology" # NOTE: If you don’t specify a domain, all domains will… See the full description on the dataset page: https://huggingface.co/datasets/clinia/CUREv1.Real-UI-Clickboxes
RUC: Real UI Clickboxes
Click carefully, even when the page is trying to trick you! 👀
Official Hugging Face release for RUC: Real UI Clickboxes, the dataset accompanying our ACL 2026 paper Don't Click That: Teaching Web Agents to Resist Deceptive Interfaces on deceptive UI understanding for web agents.
ACL Anthology: https://aclanthology.org/2026.acl-long.310/
PDF: https://aclanthology.org/2026.acl-long.310.pdf
DOI: https://doi.org/10.18653/v1/2026.acl-long.310… See the full description on the dataset page: https://huggingface.co/datasets/DUDE-Framework/Real-UI-Clickboxes.ClinicalExtract-DatasetCLIP-CC
📚 CLIP-CC Dataset (Movie Clips Edition)
Paper | arXiv | Project Page | Benchmark Code (CLIP-CC-Bench) | Dataset Repo (CLIP-CC)
CLIP-CC is a curated dataset for long-form video description: 200 movie clips sourced from YouTube, each about 90 seconds long (~5 hours in total) and drawn from more than 140 films spanning 1959–2024, each paired with one human-written English reference description averaging 402 ± 208 words. The references were written by four graduate-student… See the full description on the dataset page: https://huggingface.co/datasets/MINT-SDSU/CLIP-CC.climbing-holds
[!IMPORTANT]
This dataset is in construction. The current files are raw scans intended for establishing the structure.
Using them? Help us clean them up or identify the brands by consulting the CONTRIBUTING.md guide.
GUI for contributions
https://setrsoft.github.io/holds-dataset-hub/
Or send your files here
Climbing Holds 3D dataset (SetRsoft)
📋 Project Overview
This dataset is a community-driven open-source dataset of 3D-scanned climbing holds… See the full description on the dataset page: https://huggingface.co/datasets/setrsoft/climbing-holds.fineweb-edu-climateText-to-sql-v1grad_clip0.28_mergedmedical-clinical-reasoning-sft-100k
Medical Clinical Reasoning SFT 100K
A synthetic supervised fine-tuning dataset of 100,000 high-quality medical and clinical reasoning conversations designed to train AI assistants capable of supporting clinical decision-making, documentation, and medical education.
Dataset Description
This dataset covers a broad spectrum of clinical practice scenarios across 10 medical specialty categories. Each record follows the ShareGPT conversation format with a detailed human… See the full description on the dataset page: https://huggingface.co/datasets/stindardlogic/medical-clinical-reasoning-sft-100k.ClinSeek-Bench
ClinSeek-Bench
ClinSeek-Bench is the evaluation suite introduced in
ClinSeekAgent: Automating Multimodal Evidence Seeking for Agentic Clinical
Reasoning. It evaluates clinical reasoning
under two paired settings with the same task definitions and answer labels:
Curated Input: the model answers from the evidence package provided by
the source benchmark.
Automated Evidence-Seeking: the curated context is removed, and the model
must retrieve evidence from raw clinical data using… See the full description on the dataset page: https://huggingface.co/datasets/UCSC-VLAA/ClinSeek-Bench.oac-clinical-transport-observability-synthetic
OAC Clinical Transport Observability — Synthetic
This dataset contains 1,200 fixed-seed, entirely synthetic operational
transport-health examples for the companion OAC Transport Health v1 model.
It contains no records collected from a patient, laboratory, analyzer,
instrument, LIS, EHR, network, or health-care site.
Companion model: OAC Transport Health v1.
Canonical source: szl-forge clinical gateway.
Data boundary
The closed schema contains only eight bounded… See the full description on the dataset page: https://huggingface.co/datasets/SZLHOLDINGS/oac-clinical-transport-observability-synthetic.climbmix-400b-shuffle-metadataclinical-synthetic-text-kg
Data Description
We release the synthetic data generated using the method described in the paper Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models
(ACL 2024 Findings). The external knowledge we use is based on external knowledge graphs.
Generated Datasets
The original train/validation/test data, and the generated synthetic training data are listed as follows. For each dataset, we generate 5000 synthetic… See the full description on the dataset page: https://huggingface.co/datasets/ritaranx/clinical-synthetic-text-kg.climatebot-dataclimate-fever-generated-queries
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/climate-fever-generated-queries.clinical-synthetic-text-llm
Data Description
We release the synthetic data generated using the method described in the paper Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models
(ACL 2024 Findings). The external knowledge we use is based on LLM-generated topics and writing styles.
Generated Datasets
The original train/validation/test data, and the generated synthetic training data are listed as follows. For each dataset, we generate 5000… See the full description on the dataset page: https://huggingface.co/datasets/ritaranx/clinical-synthetic-text-llm.ClimateFund
ClimateFund: An Annotated Dataset of Climate Mitigation Projects for Supporting Question Answering
This repository contains a dataset based on funding proposals of 21 climate mitigation projects, submitted to the Green Climate Fund (GCF).
Climate mitigation documentation is challenging to parse and understand, due to the length of this documents, their multi-modality (commonly comprising tables, figures and
free text), and their highly technical and domain-specific content.… See the full description on the dataset page: https://huggingface.co/datasets/JavierSanzCruza/ClimateFund.cli-commands-explained
Overview
This dataset is a collection of 16,098 command line instructions sourced from Commandlinefu and Cheatsheets. It includes an array of commands, each with an id, title, description, date, url to source, author, votes, and flag indicating if the description is AI generated. The descriptions are primarily authored by the original contributors, for entries where descriptions were absent, they have been generated using NeuralBeagle14-7B. Out of the total entries, 10,039… See the full description on the dataset page: https://huggingface.co/datasets/b-mc2/cli-commands-explained.ClickContrast
ClickContrast
ClickContrast contains 4,292 target–distractor pairs and 4,292 coverage examples from Click-100k, with 6,690 distinct screenshots.
It is the training dataset for SelectGround-8B.
File
Rows
Supervision
all_pairs
4,292
Target coordinate, target region, distractor region, candidate regions
all_replay
4,292
Target coordinate
Training uses all_pairs and all_replay with a 1:1 pair-to-coverage sampling cycle.
Pairs retain teacher-supported targets… See the full description on the dataset page: https://huggingface.co/datasets/ruotian/ClickContrast.ChainSWE
ChainSWE
ChainSWE is a benchmark of sequential, dependent bug fixes for evaluating coding agents on continuous software maintenance. It contains 100 time-ordered chains (304 bug-fix tasks) mined from six SWE-bench-family datasets across 54 Python repositories; each row is one chain over a single repository sharing one base commit and pre-built Docker image, and its bug_fixes field lists the tasks in chronological order, where each task is a self-contained SWE-bench-style… See the full description on the dataset page: https://huggingface.co/datasets/C-lister/ChainSWE.icd10-clinical-notes
ICD-10 Multilingual Clinical Notes Dataset
A comprehensive multilingual dataset of ICD-10 diagnosis codes with clinical journal notes in 34 languages.
Author: Birger Moëll, Department of Linguistics and Philology, Uppsala University
Dataset Description
This dataset provides ICD-10 codes with:
Official diagnosis names in 34 languages (24 EU + 10 major world languages)
Sample clinical journal notes (English and Swedish)
Train/test splits for classifier training… See the full description on the dataset page: https://huggingface.co/datasets/birgermoell/icd10-clinical-notes.ClinHallu
CLINHALLU Benchmark
CLINHALLU is a benchmark for diagnosing stage-wise hallucinations in medical MLLM reasoning.
Paper: CLINHALLU: A Benchmark for Diagnosing Stage-Wise Hallucinations in Medical MLLM ReasoningGitHub: alibaba-damo-academy/ClinHallu
Benchmark Results
Accuracy and stage-wise hallucination rates on CLINHALLU. We report answer accuracy (Acc) and hallucination rates for visual recognition (H^V), knowledge recall (H^K), and reasoning integration (H^R).… See the full description on the dataset page: https://huggingface.co/datasets/Alibaba-DAMO-Academy/ClinHallu.