datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
ai2_arc
Dataset Card for "ai2_arc"
Dataset Summary
A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in
advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains
only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also
including a corpus of over 14 million science sentences… See the full description on the dataset page: https://huggingface.co/datasets/allenai/ai2_arc.OpenMathInstruct-2
OpenMathInstruct-2
OpenMathInstruct-2 is a math instruction tuning dataset with 14M problem-solution pairs
generated using the Llama3.1-405B-Instruct model.
The training set problems of GSM8K
and MATH are used for constructing the dataset in the following ways:
Solution augmentation: Generating chain-of-thought solutions for training set problems in GSM8K and MATH.
Problem-Solution augmentation: Generating new problems, followed by solutions for these new problems.… See the full description on the dataset page: https://huggingface.co/datasets/nvidia/OpenMathInstruct-2.squad_v2
Dataset Card for SQuAD 2.0
Dataset Summary
Stanford Question Answering Dataset (SQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable.
SQuAD 2.0 combines the 100,000 questions in SQuAD1.1 with over 50,000 unanswerable questions written adversarially by crowdworkers… See the full description on the dataset page: https://huggingface.co/datasets/rajpurkar/squad_v2.LongBench-v2
LongBench v2: Towards Deeper Understanding and Reasoning on Realistic Long-context Multitasks
🌐 Project Page: https://longbench2.github.io
💻 Github Repo: https://github.com/THUDM/LongBench
📚 Arxiv Paper: https://arxiv.org/abs/2412.15204
LongBench v2 is designed to assess the ability of LLMs to handle long-context problems requiring deep understanding and reasoning across real-world multitasks. LongBench v2 has the following features: (1) Length: Context length ranging from 8k to… See the full description on the dataset page: https://huggingface.co/datasets/zai-org/LongBench-v2.mmlu-redux-2.0
Dataset Card for MMLU-Redux-2.0
MMLU-Redux is a subset of 5,700 manually re-annotated questions across 57 MMLU subjects.
News
[2025.02.25] We corrected one annotation in Abstract Algebra subset, as noted in the Issue #2.
[2025.02.08] We corrected one annotation in High School Mathematics subset, as noted in the PlatinumBench paper.
[2025.01.23] MMLU-Redux is accepted to NAACL 2025!
Dataset Details
Dataset Description
Each data point in… See the full description on the dataset page: https://huggingface.co/datasets/edinburgh-dawg/mmlu-redux-2.0.AutoMathText-V2
🚀 AutoMathText-V2: A 2.46 Trillion Token AI-Curated STEM Pretraining Dataset
🎉 AutoMathText-v2 has surpassed 1.5 million downloads! We'd love to know how you're using it. Please take 1 minute to fill out our use case survey. Your feedback will directly shape the future roadmap of this dataset.👉 Share your use case here
📊 AutoMathText-V2 consists of 2.46 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and… See the full description on the dataset page: https://huggingface.co/datasets/OpenSQZ/AutoMathText-V2.UltraData-SFT-2605
UltraData-SFT-2605
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-SFT-2605 is the full set of core-domain SFT data used in the post-training of MiniCPM5-1B-SFT within the MiniCPM5-1B series, and a key representative of L3 refined data in the UltraData L0-L4 tiered data management framework. It covers math, code, knowledge, instruction following, and other core domains, containing over 15 million Deep… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-SFT-2605.AutoMathText-2.5
AutoMathText-2.5
🚀 AutoMathText-2.5: A Foundational High-Quality STEM Training Dataset
📊 AutoMathText-2.5 consists of over 2 trillion tokens of high-quality, deduplicated text spanning web content, mathematics, code, reasoning, and bilingual data. This dataset was meticulously curated using a three-tier deduplication pipeline and AI-powered quality assessment to provide superior training data for large language models.
Our dataset combines 50+… See the full description on the dataset page: https://huggingface.co/datasets/math-ai/AutoMathText-2.5.orca-math-word-problems-200k
Dataset Card
This dataset contains ~200K grade school math word problems. All the answers in this dataset is generated using Azure GPT4-Turbo. Please refer to Orca-Math: Unlocking the potential of
SLMs in Grade School Math for details about the dataset construction.
Dataset Sources
Repository: microsoft/orca-math-word-problems-200k
Paper: Orca-Math: Unlocking the potential of
SLMs in Grade School Math
Direct Use
This dataset has been designed to… See the full description on the dataset page: https://huggingface.co/datasets/microsoft/orca-math-word-problems-200k.UltraData-SFT-Agent-2609
UltraData-SFT-Agent-2609
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-SFT-Agent-2609 is the L3 refined data for Agent instruction-tuning within UltraData's L0-L4 tiered data management framework. Built for the post-training of MiniCPM5-2B, it complements UltraData-SFT-2605 (core-domain SFT) with executable Agent trajectories. The release contains approximately 500,000 samples spanning tool use… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-SFT-Agent-2609.JailBreakV-28k
⛓💥 JailBreakV-28K: A Benchmark for Assessing the Robustness of MultiModal Large Language Models against Jailbreak Attacks
🌐 GitHub | 🛎 Project Page ｜ 👉 Download full datasets
If you like our project, please give us a star ⭐ on Hugging Face for the latest update.
📰 News
Date
Event
2024/07/09
🎉 Our paper is accepted by COLM 2024.
2024/06/22
🛠️ We have updated our version to V0.2, which supports users to customize their attack models… See the full description on the dataset page: https://huggingface.co/datasets/JailbreakV-28K/JailBreakV-28k.Fineweb-Edu-Chinese-V2.2
Chinese Fineweb Edu Dataset V2.2 (Instruct & Pre-train)
[[中文]] | [[English]]
OpenCSG Community | 👾 GitHub | 📖 Technical Report
Dataset Introduction: Filling the Data Puzzle for Chinese Education LLMs
Chinese Fineweb Edu Dataset V2.2is a rare high-quality dataset in the open-source community that covers the full process from Pre-training to Supervised Fine-Tuning (SFT) for the Chinese education domain.
This project aims to solve the core pain point of… See the full description on the dataset page: https://huggingface.co/datasets/opencsg/Fineweb-Edu-Chinese-V2.2.PersonaMem-v2
PersonaMem-v2: Towards Personalized Intelligence via Learning Implicit User Personas and Agentic Memory
📅 We have now released PersonaMem-v3!
🚨 The paper is now released. View the full paper here and codebase here.
Personalization is becoming the next milestone of artificial super-intelligence. AI cannot always satisfy every user, especially on tasks with subjective goals, but personalization offers a path toward pluralistic alignment.… See the full description on the dataset page: https://huggingface.co/datasets/bowen-upenn/PersonaMem-v2.UltraData-RL-2609
UltraData-RL-2609
📦 UltraData Collection |
🌐 UltraData |
🤗 MiniCPM5 Series
English |
中文
📚 Introduction
UltraData-RL-2609 is the L3 refined data for reinforcement learning within UltraData's L0-L4 tiered data management framework. Built for the RL stage of MiniCPM5-2B post-training, it complements UltraData-SFT-2605 with verifiable-reward tasks. It is also the training corpus used by JustRL II (Scaling Small LLMs to 128K Reasoning with a Critic)… See the full description on the dataset page: https://huggingface.co/datasets/openbmb/UltraData-RL-2609.mmlu-redux-2.0-okThis dataset is filtered from https://huggingface.co/datasets/edinburgh-dawg/mmlu-redux-2.0 using:
from datasets import load_dataset
from pathlib import Path
CONFIGS = ['abstract_algebra', 'anatomy', 'astronomy', 'business_ethics', 'clinical_knowledge', 'college_biology', 'college_chemistry', 'college_computer_science', 'college_mathematics', 'college_medicine', 'college_physics', 'computer_security', 'conceptual_physics', 'econometrics', 'electrical_engineering', 'elementary_mathematics'… See the full description on the dataset page: https://huggingface.co/datasets/fxmarty/mmlu-redux-2.0-ok.AIME2025
AIME 2025 Dataset
Dataset Description
This dataset contains problems from the American Invitational Mathematics Examination (AIME) 2025-I & II.
labbench2
LABBench2
LABBench2 is a benchmark for measuring real-world capabilities of AI systems performing scientific research tasks. It is an evolution of the Language Agent Biology Benchmark (LAB-Bench), comprising nearly 1,900 tasks that measure similar capabilities but in more realistic contexts.
LABBench2 provides a meaningful jump in difficulty over LAB-Bench (model-specific accuracy differences range from −26% to −46% across subtasks), underscoring continued room for improvement.… See the full description on the dataset page: https://huggingface.co/datasets/EdisonScientific/labbench2.python-codes-25k
License
MIT
This is a Cleaned Python Dataset Covering 25,000 Instructional Tasks
Overview
The dataset has 4 key features (fields): instruction, input, output, and text.It's a rich source for Python codes, tasks, and extends into behavioral aspects.
Dataset Statistics
Total Entries: 24,813
Unique Instructions: 24,580
Unique Inputs: 3,666
Unique Outputs: 24,581
Unique Texts: 24,813
Average Tokens per example: 508
Features… See the full description on the dataset page: https://huggingface.co/datasets/flytech/python-codes-25k.VDR_MEGA_2
VDR_MEGA_2
Dataset Summary
VDR_MEGA_2 is a high-quality multimodal dataset created through the merge of multiple domain-specific datasets with enhanced data processing techniques. This dataset represents our most refined approach to multimodal data generation, incorporating filtering algorithms and improved AI-assisted content generation to deliver superior quality for RAG, DSE, question answering, document search, and vision-language model training tasks.… See the full description on the dataset page: https://huggingface.co/datasets/racineai/VDR_MEGA_2.sql-create-context
Overview
This dataset builds from WikiSQL and Spider.
There are 78,577 examples of natural language queries, SQL CREATE TABLE statements, and SQL Query answering the question using the CREATE statement as context. This dataset was built with text-to-sql LLMs in mind, intending to prevent hallucination of column and table names often seen when trained on text-to-sql datasets. The CREATE TABLE statement can often be copy and pasted from different DBMS and provides table names, column… See the full description on the dataset page: https://huggingface.co/datasets/b-mc2/sql-create-context.worldcup2026
⚽ WorldCup Arena
A Leakage-Free Forecasting Benchmark on a Live Tournament
Can a language model forecast a match — when the match had not been played at the moment it was asked?
🌐 Language / 语言 : 中文 ▾
📊 四张表
点开本页顶部的 Data Studio 标签即可浏览，也可以直接按名字加载。
Config
行数
内容
fixtures
104
基准本体 —— 喂给模型的头部信息，以及结算后的 90 分钟赛果，七个盘口全部推导好（outcome_1x2、over_2_5、both_score、odd_total）
dossiers
2,208
简报索引 —— 46 快照 × 48… See the full description on the dataset page: https://huggingface.co/datasets/Social-AI-2026/worldcup2026.Edge-Agent-Reasoning-WebSearch-260K
Edge Agent Reasoning WebSearch 260K
Abstract
The Edge-Agent-Reasoning-WebSearch-260K dataset is a massive, synthetically expert-engineered corpus of over 700 Million tokens, designed to train small, local models (SLMs) and edge-deployed agents in advanced problem deconstruction and self-aware reasoning.
Rather than training a model to execute instructions directly—which often leads to hallucinations when context is missing—this dataset trains a model to act as a… See the full description on the dataset page: https://huggingface.co/datasets/yatin-superintelligence/Edge-Agent-Reasoning-WebSearch-260K.t2-ragbench
Dataset Card for T2-RAGBench
Project Page | Paper | Code
IMPORTANT NOTICE:
We deleted VQAonBD from the dataset due to low quality of the question reformulations. If you still want to use it you will find the data in the previous commit history.
Dataset Description
Dataset Summary
T2-RAGBench is a benchmark dataset designed to evaluate Retrieval-Augmented Generation (RAG) on financial documents containing both text and tables. It consists of 23,088… See the full description on the dataset page: https://huggingface.co/datasets/G4KMU/t2-ragbench.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.corpus-oct-2024
Dataset Card for FreshStack (Corpus)
Homepage |
Repository |
Paper
FreshStack is a holistic framework to construct challenging IR/RAG evaluation datasets that focuses on search across niche and recent topics.
This dataset (October 2024) contains the query, nuggets, answers and nugget-level relevance judgments of 5 niche topics focused on software engineering and machine learning.
The queries and answers (accepted) are taken from Stack Overflow, GPT-4o generates the nuggets and… See the full description on the dataset page: https://huggingface.co/datasets/freshstack/corpus-oct-2024.MMFineReason-Full-2.3M-Qwen3-VL-235B-Thinking
MMFineReason-Full-2.3M
The Complete Pre-Selection Dataset — Before Quality Filtering
📖 Overview
MMFineReason-Full-2.3M is the complete pre-selection dataset containing 2.3M samples and 8.8B solution tokens, generated through our reasoning distillation pipeline before the data selection stage. This dataset includes all samples that passed basic template and length validation, but have not undergone correctness verification filtering.
🎯 Key Characteristics… See the full description on the dataset page: https://huggingface.co/datasets/OpenDataArena/MMFineReason-Full-2.3M-Qwen3-VL-235B-Thinking.Omnimodal-Agent-SFT-2K
OmniGAIA: Omni-Modal General AI Assistant Benchmark
📄 Paper
•
💻 Code & Demo
•
🤗 Dataset & Model
•
📈 Leaderboard
This dataset contains omni-modal agent supervised fine-tuning (SFT) trajectories in the LlamaFactory SFT data format. You can directly follow LlamaFactory's instructions to fine-tune your omni-modal LLMs.OmniGAIA is a benchmark for Omni-Modal General AI Assistants that jointly reason over vision, audio, and language with external tools. It is… See the full description on the dataset page: https://huggingface.co/datasets/RUC-NLPIR/Omnimodal-Agent-SFT-2K.SFT-Collection-v2
SFT-Collection-v2: A Unified Reasoning Corpus for Supervised Fine-Tuning
SFT-Collection-v2 is a large-scale, curated corpus for supervised fine-tuning (SFT)
of reasoning-oriented language models. It combines, filters, deduplicates, and
language-extends a broad set of public reasoning datasets into a single,
consistent schema. The collection focuses on chain-of-thought reasoning
traces across math, code, science, and general reasoning, covering English and
five additional languages… See the full description on the dataset page: https://huggingface.co/datasets/ahmad21omar/SFT-Collection-v2.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.cybersecurity-qa-v2
Cybersecurity Q&A Dataset v2 — 2.6M Examples
A large-scale cybersecurity Q&A dataset for fine-tuning LLMs on security topics.
2,621,468 examples covering vulnerabilities, attack techniques, weaknesses, and defensive strategies.
Statistics
Source
Examples
Description
NIST NVD CVE Database
~1,954,225
All CVEs (2002–2025): overview, severity, detection, remediation
AlicanKiraz0/All-CVE-Records-Training-Dataset
~297,441
Detailed CVE analysis with markdown… See the full description on the dataset page: https://huggingface.co/datasets/rezaduty/cybersecurity-qa-v2.