datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
super_glue
Dataset Card for "super_glue"
Dataset Summary
SuperGLUE (https://super.gluebenchmark.com/) is a new benchmark styled after
GLUE with a new set of more difficult language understanding tasks, improved
resources, and a new public leaderboard.
Supported Tasks and Leaderboards
More Information Needed
Languages
More Information Needed
Dataset Structure
Data Instances
axb
Size of downloaded dataset files: 0.03 MB
Size of… See the full description on the dataset page: https://huggingface.co/datasets/aps/super_glue.openbookqa
Dataset Card for OpenBookQA
Dataset Summary
OpenBookQA aims to promote research in advanced question-answering, probing a deeper understanding of both the topic
(with salient facts summarized as an open book, also provided with the dataset) and the language it is expressed in. In
particular, it contains questions that require multi-step reasoning, use of additional common and commonsense knowledge,
and rich text comprehension.
OpenBookQA is a new kind of… See the full description on the dataset page: https://huggingface.co/datasets/allenai/openbookqa.MMLU-Pro
MMLU-Pro Dataset
MMLU-Pro dataset is a more robust and challenging massive multi-task understanding dataset tailored to more rigorously benchmark large language models' capabilities. This dataset contains 12K complex questions across various disciplines.
|Github | 🏆Leaderboard | 📖Paper |
🚀 What's New
[2026.03.11] Added more cutting-edge frontier models to the leaderboard, including the Claude-4.6 series, Seed2.0 series, Qwen3.5 series, and Gemini-3.1-Pro… See the full description on the dataset page: https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro.gpqa
Dataset Card for GPQA
GPQA is a multiple-choice, Q&A dataset of very hard questions written and validated by experts in biology, physics, and chemistry. When attempting questions out of their own domain (e.g., a physicist answers a chemistry question), these experts get only 34% accuracy, despite spending >30m with full access to Google.
We request that you do not reveal examples from this dataset in plain text or images online, to reduce the risk of leakage into foundation… See the full description on the dataset page: https://huggingface.co/datasets/Idavidrein/gpqa.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.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.mmlu-prox-eval-predictions
MMLU-ProX Multilingual Model Predictions
Raw per-sample model predictions on MMLU-ProX
across 29 languages and 25 open-weight LLMs, produced with
lm-evaluation-harness.
This dataset releases the full prediction logs (not just aggregate scores) so that
item-level responses can be re-analysed — e.g. for Item Response Theory (IRT) modelling
of multilingual benchmarks, error analysis, or per-item difficulty estimation.
Repository structure
mmlu_prox_<lang>/
└──… See the full description on the dataset page: https://huggingface.co/datasets/gililior/mmlu-prox-eval-predictions.distilabel-capybara-dpo-7k-binarized
Capybara-DPO 7K binarized
A DPO dataset built with distilabel atop the awesome LDJnr/Capybara
This is a preview version to collect feedback from the community. v2 will include the full base dataset and responses from more powerful models.
Why?
Multi-turn dialogue data is key to fine-tune capable chat models. Multi-turn preference data has been used by the most relevant RLHF works (Anthropic, Meta Llama2, etc.). Unfortunately, there are very few… See the full description on the dataset page: https://huggingface.co/datasets/argilla/distilabel-capybara-dpo-7k-binarized.KodCode-V1-SFT-R1
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-V1-SFT-R1.docmath-eval-failures-200
DocMath-Eval Failures 200: Agent Benchmark & Leaderboard
A curated benchmark of 200 challenging financial math questions that leading AI models
failed to answer correctly, with comprehensive evaluation results from multiple AI agents.
Leaderboard
Evaluated on 2026-02-21 using LLM-as-Judge (Qwen QwQ-32B) for soft scoring.
Rank
Agent
Model
Exact Match
Judge: Exact
Judge: Approx
Judge: Total
Wrong
Avg Duration
Avg Tool Calls
1
TRAE Agent
Opus 4.5
98/200 (49.0%)
96… See the full description on the dataset page: https://huggingface.co/datasets/Ayushnangia/docmath-eval-failures-200.legalbench
Dataset Card for Dataset Name
Homepage: https://hazyresearch.stanford.edu/legalbench/
Repository: https://github.com/HazyResearch/legalbench/
Paper: https://arxiv.org/abs/2308.11462
Dataset Description
Dataset Summary
The LegalBench project is an ongoing open science effort to collaboratively curate tasks for evaluating legal reasoning in English large language models (LLMs). The benchmark currently consists of 162 tasks gathered from 40… See the full description on the dataset page: https://huggingface.co/datasets/nguha/legalbench.stackoverflow-posts
StackOverflow Posts Markdown
Dataset Summary
This dataset contains all posts submitted to StackOverflow before the 14th of June 2023 formatted as Markdown text.
The dataset contains ~60 Million posts, totaling ~35GB in size and ~65 billion characters of text.
The data is sourced from Internet Archive StackExchange Data Dump.
Dataset Structure
Each record corresponds to one post of a particular type.
Original ordering from the data dump is not exactly preserved… See the full description on the dataset page: https://huggingface.co/datasets/mikex86/stackoverflow-posts.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.open-india-law
Open India Law
Open, structured Indian primary law - plus the scrapers that build it.
Every judgment of the Supreme Court of India and all 25 High Courts, the decisions of 15
tribunals and regulators, and Central, State and Union Territory legislation down to the
individual section. Normalized to one schema, exclusively from official government sources.
Volume
Period
Court judgments
12,848,644
1950 to 2025
Tribunal and regulator matters
813,168
1985 to 2026… See the full description on the dataset page: https://huggingface.co/datasets/vaquill/open-india-law.GUIGuard-Bench
GUIGuard-Bench (Public Ladder)
GUIGuard-Bench is a cross-platform GUI agent benchmark for studying privacy risks and privacy-preserving execution in multimodal GUI agents.
This public-ladder release contains 121 GUI interaction trajectories (68 Android + 53 PC) for benchmark evaluation, with 26,407 region-level privacy annotations across 2,002 screenshots.
For the anonymous review version of the evaluation toolkit, see GUIGaurd-Bench-CA4F.
Dataset Summary
GUI agents… See the full description on the dataset page: https://huggingface.co/datasets/ShaofantuoshuzhengzhiSha/GUIGuard-Bench.fineweb-edu
FineWeb-Edu (Lance Format)
A Lance-formatted version of FineWeb-Edu — over 1.5 billion educational web passages with cleaned text, source metadata, language detection signals, and 384-dim text embeddings — available directly from the Hub at hf://datasets/lance-format/fineweb-edu/data/train.lance.
Key features
Cleaned passage text in the text column with the source url and title carried alongside.
Language detection signals (language, language_probability) for filtered… See the full description on the dataset page: https://huggingface.co/datasets/lance-format/fineweb-edu.ShareGPT-4oLegal_Corpus_QA_SynDeepThink
🧠 Legal Corpus QA SynDeepThink Dataset
This repository contains a high-intelligence Legal Question-and-Answer dataset, generated through an advanced Iterative and Recursive Thinking process. It bridges the gap between static legal corpora and the dynamic "check-and-recheck" nature of human legal expertise. 🏛️
💡 The Concept: Iterative & Recursive Legal Logic
While standard synthetic datasets are often generated in a single pass, Legal_Corpus_QA_SynDeepThink mimics the… See the full description on the dataset page: https://huggingface.co/datasets/Azzindani/Legal_Corpus_QA_SynDeepThink.anle-toaan-gov-vn
Vietnamese Án lệ Corpus — anle.toaan.gov.vn
🇻🇳 Tóm tắt. Bộ dữ liệu các bản án + án lệ Việt Nam thu thập từ cổng
anle.toaan.gov.vn của Tòa án nhân dân tối cao.
Mỗi văn bản đi kèm markdown chuẩn hoá tiếng Việt và một lớp grounding mức câu
(mỗi trích dẫn mang sentence_id + char span trỏ ngược vào markdown). Bộ dữ
liệu là một phần của ViLA common-corpus và ship ba cấu hình HF theo chuẩn
chung: documents (bảng chính) · embeddings (vector 4096-D Nemotron-3-Embed-8B) ·
reduces (toạ… See the full description on the dataset page: https://huggingface.co/datasets/tmquan/anle-toaan-gov-vn.Gaokao-Compass-11M
English
GaokaoCompass — China College Admission Dataset
GaokaoCompass is a structured dataset of China's national college entrance examination (Gaokao) admission records, covering all 31 provinces from 2017 to 2025. It includes enrollment plans, university admission cutoff scores, major-level admission scores, and score-ranking tables. The dataset is designed to help students, parents, and researchers make informed decisions with… See the full description on the dataset page: https://huggingface.co/datasets/choucsan/Gaokao-Compass-11M.KodCode-V1-SFT-4o
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-V1-SFT-4o.PromptEval_MMLU_full
MMLU Multi-Prompt Evaluation Data
Overview
This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Understanding (MMLU) benchmark. The data is introduced in
Maia Polo, Felipe, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, and Mikhail Yurochkin. "Efficient multi-prompt evaluation of LLMs."… See the full description on the dataset page: https://huggingface.co/datasets/PromptEval/PromptEval_MMLU_full.codah
Dataset Card for COmmonsense Dataset Adversarially-authored by Humans
Dataset Summary
The COmmonsense Dataset Adversarially-authored by Humans (CODAH) is an evaluation set for commonsense
question-answering in the sentence completion style of SWAG. As opposed to other automatically generated
NLI datasets, CODAH is adversarially constructed by humans who can view feedback from a pre-trained model
and use this information to design challenging commonsense questions.… See the full description on the dataset page: https://huggingface.co/datasets/jaredfern/codah.AoPS-Scrape
AoPS-Scrape
Problems and solutions scraped from Art of Problem Solving (AoPS) Online class homework endpoints.
Obtained legally in accordance with AoPS's Terms of Service. This is not unauthorized redistribution of pirated material — access was through a legitimate authenticated AoPS Online class session.
Splits
Splits are named by scrape date (YYYY_MM_DD), plus a cross-date content-deduplicated split:
Split
Rows
Notes
deduplicated
29,964
One row per… See the full description on the dataset page: https://huggingface.co/datasets/hudsongouge/AoPS-Scrape.UnsolvedMath🌐 Browse UnsolvedMath online
✅ Paper: Open Mathematical Problems as an AI Reasoning Benchmark
UnsolvedMath Dataset
A comprehensive curated collection of 15,458 open, partially solved, and solved mathematics problems across all domains and difficulty levels, including the largest collection of Erdős problems available in machine-readable format. Available for browsing at unsolvedmath.com.
Paper: "Open Mathematical Problems as an AI Reasoning Benchmark"
Dataset… See the full description on the dataset page: https://huggingface.co/datasets/ulamai/UnsolvedMath.KodCode-Light-RL-10K
🐱 KodCode: A Diverse, Challenging, and Verifiable Synthetic Dataset for Coding
KodCode is the largest fully-synthetic open-source dataset providing verifiable solutions and tests for coding tasks. It contains 12 distinct subsets spanning various domains (from algorithmic to package-specific knowledge) and difficulty levels (from basic coding exercises to interview and competitive programming challenges). KodCode is designed for both supervised fine-tuning (SFT) and RL tuning.
🕸️… See the full description on the dataset page: https://huggingface.co/datasets/KodCode/KodCode-Light-RL-10K.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.Belle_1.4M-SLAM-Omni
Belle_1.4M
This dataset is prepared for the reproduction of SLAM-Omni.
This is a multi-round Chinese spoken dialogue training dataset. For code and usage examples, please refer to the related GitHub repository: X-LANCE/SLAM-LLM (examples/s2s)
🔧 Modifications
Data Filtering: We removed samples with excessively long data.
Speech Response Tokens: We used CosyVoice to synthesize corresponding semantic speech tokens for the speech response. These tokens, represented as… See the full description on the dataset page: https://huggingface.co/datasets/worstchan/Belle_1.4M-SLAM-Omni.xcopa
Dataset Card for "xcopa"
Dataset Summary
XCOPA: A Multilingual Dataset for Causal Commonsense Reasoning
The Cross-lingual Choice of Plausible Alternatives dataset is a benchmark to evaluate the ability of machine learning models to transfer commonsense reasoning across
languages. The dataset is the translation and reannotation of the English COPA (Roemmele et al. 2011) and covers 11 languages from 11 families and several areas around
the globe. The dataset is… See the full description on the dataset page: https://huggingface.co/datasets/cambridgeltl/xcopa.PromptEval_MMLU_correctness
MMLU Multi-Prompt Evaluation Data (correctness scores)
Overview
This dataset contains the results of a comprehensive evaluation of various Large Language Models (LLMs) using multiple prompt templates on the Massive Multitask Language Understanding (MMLU) benchmark. The data is introduced in
Maia Polo, Felipe, Ronald Xu, Lucas Weber, Mírian Silva, Onkar Bhardwaj, Leshem Choshen, Allysson Flavio Melo de Oliveira, Yuekai Sun, and Mikhail Yurochkin. "Efficient multi-prompt… See the full description on the dataset page: https://huggingface.co/datasets/PromptEval/PromptEval_MMLU_correctness.