datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
jat-dataset
JAT Dataset
Dataset Description
The Jack of All Trades (JAT) dataset combines a wide range of individual datasets. It includes expert demonstrations by expert RL agents, image and caption pairs, textual data and more. The JAT dataset is part of the JAT project, which aims to build a multimodal generalist agent.
Paper: https://huggingface.co/papers/2402.09844
Usage
>>> from datasets import load_dataset
>>> dataset =… See the full description on the dataset page: https://huggingface.co/datasets/jat-project/jat-dataset.natural_questions
Dataset Card for Natural Questions
Dataset Summary
The NQ corpus contains questions from real users, and it requires QA systems to
read and comprehend an entire Wikipedia article that may or may not contain the
answer to the question. The inclusion of real user questions, and the
requirement that solutions should read an entire page to find the answer, cause
NQ to be a more realistic and challenging task than prior QA datasets.
Supported Tasks and Leaderboards… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/natural_questions.databricks-dolly-15k
Summary
databricks-dolly-15k is an open source dataset of instruction-following records generated by thousands of Databricks employees in several
of the behavioral categories outlined in the InstructGPT paper, including brainstorming, classification,
closed QA, generation, information extraction, open QA, and summarization.
This dataset can be used for any purpose, whether academic or commercial, under the terms of the
Creative Commons Attribution-ShareAlike 3.0 Unported… See the full description on the dataset page: https://huggingface.co/datasets/databricks/databricks-dolly-15k.reddit_dataset_157
Bittensor Subnet 13 Reddit Dataset
Dataset Summary
This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed Reddit data. The data is continuously updated by network miners, providing a real-time stream of Reddit content for various analytical and machine learning tasks.
For more information about the dataset, please visit the official repository.
Supported Tasks
The versatility of this dataset allows… See the full description on the dataset page: https://huggingface.co/datasets/tensorshield/reddit_dataset_157.tiny-supervised-datasetnq_open
Dataset Card for nq_open
Dataset Summary
The NQ-Open task, introduced by Lee et.al. 2019,
is an open domain question answering benchmark that is derived from Natural Questions.
The goal is to predict an English answer string for an input English question.
All questions can be answered using the contents of English Wikipedia.
Supported Tasks and Leaderboards
Open Domain Question-Answering,
EfficientQA Leaderboard:… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/nq_open.soc-ratchakitcha
Royal Gazette Thailand (Ratchakitcha) Dataset
ชุดข้อมูลราชกิจจานุเบกษา (แบบ Machine Readable)
โครงการ Open Law Data Thailand ร่วมกับคณะกรรมาธิการการพาณิชย์และการอุตสาหกรรม วุฒิสภา ได้รับความอนุเคราะห์ข้อมูลจาก สำนักเลขาธิการคณะรัฐมนตรี (สลค.) เพื่อเผยแพร่ข้อมูลกฎหมายไทยสู่สาธารณะในรูปแบบที่ประมวลผลได้ด้วยคอมพิวเตอร์ (Machine Readable) เพื่อส่งเสริมนวัตกรรม Legal Tech และ AI ของประเทศไทย
Dataset Description
ชุดข้อมูลนี้รวบรวมรายการประกาศในราชกิจจานุเบกษา… See the full description on the dataset page: https://huggingface.co/datasets/open-law-data-thailand/soc-ratchakitcha.ZGCM-1-Data
A Fully Open and Extremely Efficient Foundation Model for Math and Agentic Search
Zhongguancun Academy · Zhongguancun Institute of Artificial Intelligence
📄 Tech Report · 🤗 Model · 🤗 Data · 📊 Results · 💻 Training Code · 💬 WeChat Community
Introduction
ZGCM-1 is a 7.39B-parameter dense language model trained from scratch, built for mathematical reasoning and tool-assisted search. It combines deliberate internal thinking with active information gathering, supporting… See the full description on the dataset page: https://huggingface.co/datasets/zgcagi/ZGCM-1-Data.dreamDREAM is a multiple-choice Dialogue-based REAding comprehension exaMination dataset. In contrast to existing reading comprehension datasets, DREAM is the first to focus on in-depth multi-turn multi-party dialogue understanding.FlashRAG_datasets
⚡FlashRAG: A Python Toolkit for Efficient RAG Research
FlashRAG is a Python toolkit for the reproduction and development of Retrieval Augmented Generation (RAG) research. Our toolkit includes 36 pre-processed benchmark RAG datasets and 16 state-of-the-art RAG algorithms.
With FlashRAG and provided resources, you can effortlessly reproduce existing SOTA works in the RAG domain or implement your custom RAG processes and components.
For more information, please view our GitHub repo… See the full description on the dataset page: https://huggingface.co/datasets/RUC-NLPIR/FlashRAG_datasets.tydiqa
Dataset Card for "tydiqa"
Dataset Summary
TyDi QA is a question answering dataset covering 11 typologically diverse languages with 204K question-answer pairs.
The languages of TyDi QA are diverse with regard to their typology -- the set of linguistic features that each language
expresses -- such that we expect models performing well on this set to generalize across a large number of the languages
in the world. It contains language phenomena that would not be found in… See the full description on the dataset page: https://huggingface.co/datasets/google-research-datasets/tydiqa.mse-text-img-dataset
Dataset Card for MSE-text-img-dataset
We have created a custom dataset
that is extracted as a subset of the Math Stack Exchange (MSE)
dataset. This text-image dataset contains 64,860 questions with
their respective list of answers, scores, acceptance marking,
and image versions of each question and answer generated
from the stored text with embedded LaTeX math markup.
In this dataset there are 117,380 answers in total, with 1.81
answers per question on average. Each image… See the full description on the dataset page: https://huggingface.co/datasets/Zenos5/mse-text-img-dataset.AIR-Bench-Dataset
AIR-Bench
Arxiv: https://arxiv.org/html/2402.07729v1This is the AIR-Bench dataset download page.AIR-Bench encompasses two dimensions: foundation and chat benchmarks.
The former consists of 19 tasks with approximately 19k single-choice questions.
The latter one contains 2k instances of open-ended question-and-answer data.For how to run AIR-Bench, Please refer to AIR-Bench github page(https://github.com/OFA-Sys/AIR-Bench)(will be public soon).
Data Sources(All come from… See the full description on the dataset page: https://huggingface.co/datasets/qyang1021/AIR-Bench-Dataset.math-dataset-measuring-mathematical-problem-solvingTo cite the dataset please reference it as
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks and Collin Burns and Saurav Kadavath and Akul Arora and Steven Basart and Eric Tang and Dawn Song and Jacob Steinhardt},
journal={NeurIPS},
year={2021}
}
medical-qa-datasets
all-processed dataset is a concatenation of of medical-meadow-* and chatdoctor_healthcaremagic datasets
The Chat Doctor term is replaced by the chatbot term in the chatdoctor_healthcaremagic dataset
Similar to the literature the medical_meadow_cord19 dataset is subsampled to 50,000 samples
truthful-qa-* is a benchmark dataset for evaluating the truthfulness of models in text generation, which is used in Llama 2 paper. Within this dataset, there are 55 and 16 questions related to Health and… See the full description on the dataset page: https://huggingface.co/datasets/lavita/medical-qa-datasets.officeqa
OfficeQA
Dataset Summary
OfficeQA is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over historical U.S. Treasury Bulletin documents (1939–2025), which contain dense financial tables, charts, and narrative text. OfficeQA is designed to test retrieval, tool use, and multi-step reasoning in… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa.Bitext-customer-support-llm-chatbot-training-dataset
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.car-bench-dataset
CAR-Bench Dataset
CAR-Bench is a benchmark for evaluating AI voice assistants in a realistic automotive (car) environment.
It tests an agent's ability to correctly use vehicle control tools, handle disambiguation, and avoid hallucinations.
Dataset Structure
The dataset is organized into task configs and mock data configs:
Tasks
Each task defines a user persona, an instruction, the initial vehicle/environment context, and the ground-truth sequence of tool-call… See the full description on the dataset page: https://huggingface.co/datasets/johanneskirmayr/car-bench-dataset.x_dataset_39
Bittensor Subnet 13 X (Twitter) Dataset
Dataset Summary
This dataset is part of the Bittensor Subnet 13 decentralized network, containing preprocessed data from X (formerly Twitter). The data is continuously updated by network miners, providing a real-time stream of tweets for various analytical and machine learning tasks.
For more information about the dataset, please visit the official repository.
Supported Tasks
The versatility of this… See the full description on the dataset page: https://huggingface.co/datasets/futuremoon/x_dataset_39.llm-election-data-2024
Data Release for Large-Scale, Longitudinal Survey of Large Language Models (LLMs) During the 2024 US Elections
Overview
This repository contains the questions asked of and responses given by LLMs during the 2024 US elections, collected for a longitudinal survey conducted from July 23, 2024 to November 12, 2024. The study is described in detail in the paper "Large-Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season" by Sarah H. Cen, Andrew… See the full description on the dataset page: https://huggingface.co/datasets/sarahcen/llm-election-data-2024.Trendyol-Cybersecurity-Instruction-Tuning-Dataset
Trendyol Cybersecurity Defense Instruction-Tuning Dataset (v2.0)
🚀 TL;DR
53,202 meticulously curated system/user/assistant instruction-tuning examples covering 200+ specialized cybersecurity domains. Built by the Trendyol Security Team for training state-of-the-art defensive security AI assistants. Expanded from 21K to 53K rows with comprehensive coverage of modern security challenges including cloud-native threats, AI/ML security, quantum computing risks… See the full description on the dataset page: https://huggingface.co/datasets/Trendyol/Trendyol-Cybersecurity-Instruction-Tuning-Dataset.OpenCLAW-SEED-data
🧬 P2PCLAW Research Papers Dataset
The First Decentralized AI Research Benchmark
📊 Dataset Overview
Metric
Value
Total Papers
116
Total Words
355,795
Total Tokens
473,208
Scored Papers
98
Average Score
5.24 / 10
Lean4 Verified
113
Research Fields
8
Unique Authors/Agents
28
🧠 What is P2PCLAW?
P2PCLAW (Peer-to-Peer Collaborative Learning and Academic Work) is the world's first decentralized… See the full description on the dataset page: https://huggingface.co/datasets/Agnuxo/OpenCLAW-SEED-data.docinsights-2026-shared-task-data
DocInsights 2026 Shared Task: DocSem
Document-grounded quantitative reasoning with evidence attribution
DocSem is the shared task of DocInsights 2026, the Workshop on Document Intelligence and Understanding co-located with EMNLP 2026 in Budapest, Hungary. The workshop theme is Beyond Plain Text: Bridging NLP and Document AI.
Workshop shared task | Source repository | Submission portal | Participant guide
Participants receive a PDF document and a paraphrased user_query. Systems… See the full description on the dataset page: https://huggingface.co/datasets/amitbcp/docinsights-2026-shared-task-data.Nemotron-AIQ-Agentic-Safety-Dataset-1.0
Nemotron-AIQ Agentic Safety Dataset
Dataset Summary
Nemotron-AIQ-Agentic-Safety-Dataset is a comprehensive dataset that captures a broad range of novel safety and security contextual risks that can emerge within agentic systems. It highlights the robustness of NVIDIA's open model, llama-3.3-nemotron-super-49b-v1, when deployed as a research assistant inside AIQ, demonstrating its ability to handle a diverse spectrum of agentic safety and security challenges. The dataset… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/Nemotron-AIQ-Agentic-Safety-Dataset-1.0.Ground3D_Dataset
Ground3D Dataset
A large-scale 3D vision-language question-answering dataset for point-grounded,
metric-aware 3D scene understanding. Built on ScanNet and ScanNet++
with dense object and part annotations, the dataset spans eight downstream
reasoning tasks at both object and part granularity, plus multi-turn
dialogue that composes them.
Answers are both:
point-grounded: explicitly tied to the referred 3D region via
<p>label</p><SEG> markup, and
metric: physical quantities (size… See the full description on the dataset page: https://huggingface.co/datasets/amolharsh/Ground3D_Dataset.EASI-Leaderboard-Data
EASI Leaderboard Data
A consolidated dataset for the EASI Leaderboard, containing the evaluation data (inputs/prompts) actually used on the leaderboard across spatial reasoning benchmarks for VLMs.
Looking for the Spatial Intelligence leaderboard?https://huggingface.co/spaces/lmms-lab-si/EASI-Leaderboard
🔎 Dataset Summary
Question types: MCQ (multiple choice) and NA (numeric answer).
File format: TSV only.
Usage: These TSVs are directly consumable by the EASI… See the full description on the dataset page: https://huggingface.co/datasets/lmms-lab-si/EASI-Leaderboard-Data.Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection
🧬 Omni-Frontier Collection
Cybersecurity · Coding · Math · Science · RSI Reasoning — one unified SFT package
A unified, deduplicated, fully-browsable distillation & SFT corpus — every row real, every row visible.
📖 Jump to
What's inside · 🔁 Aggregation audit · 🛡 Cybersecurity · 💻 Coding · 🏭 Distillation deep-dive · 🔁 RSI · 🧮 Math/Science/More · 🎓 Training guide · 🔎 Browsing · 🧹 Quality · 🗺 Roadmap · 📄 License… See the full description on the dataset page: https://huggingface.co/datasets/SHSLab/Omni-Frontier-Distillation-SFT-Cyber-Coding-Med-dataset-collection.databench
💾🏋️💾 DataBench 💾🏋️💾
New! All the splits from the SemEval competition, including the test set, are now available in this page.
This repository contains the original 80 datasets used for the paper Question Answering over Tabular Data with DataBench:
A Large-Scale Empirical Evaluation of LLMs which appeared in LREC-COLING 2024 and the associated SemEval 2025 Task 8 competition.
Large Language Models (LLMs) are showing emerging abilities, and one of the latest recognized ones is… See the full description on the dataset page: https://huggingface.co/datasets/cardiffnlp/databench.ClinFusion-Eval-Data
🏥 ClinFusion-Eval-Data
The Holistic Evaluation Suite for Vision-Centric Medical Multimodal LLMs
ClinFusion-Eval-Data is the unified evaluation corpus used to benchmark the ClinFusion model series (ClinFusion-8B, ClinFusion-32B). It packages 211,810 evaluation records spanning 22 public medical benchmarks into a single, consistently-formatted suite, together with 509 GiB of the underlying 2D images and native 3D CT volumes they refer to.
The goal is reproducibility:… See the full description on the dataset page: https://huggingface.co/datasets/Alibaba-DAMO-Academy/ClinFusion-Eval-Data.TempPerturb-Eval-data
TempPerturb-Eval-data
Summary
TempPerturb-Eval-data is the released output dataset for TempPerturb-Eval, a benchmark for analyzing the robustness of Retrieval-Augmented Generation (RAG) systems under both internal variation and external perturbation.
This is an evaluation-artifact dataset: it stores model outputs and experiment metadata for controlled robustness analysis, rather than a new QA training corpus.
The release covers:
5 models
11 temperatures from 0.0 to 2.0
4… See the full description on the dataset page: https://huggingface.co/datasets/yongxin2020/TempPerturb-Eval-data.