datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
IFEval
Dataset Card for IFEval
Dataset Summary
This dataset contains the prompts used in the Instruction-Following Eval (IFEval) benchmark for large language models. It contains around 500 "verifiable instructions" such as "write in more than 400 words" and "mention the keyword of AI at least 3 times" which can be verified by heuristics. To load the dataset, run:
from datasets import load_dataset
ifeval = load_dataset("google/IFEval")
Supported Tasks and… See the full description on the dataset page: https://huggingface.co/datasets/google/IFEval.Darwin-CCMedQA-USMLE-4-optionsOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
title={What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams},
author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},
journal={arXiv preprint arXiv:2009.13081},
year={2020}
}
glaive-function-calling-v2chm-corr-prj-giangmmlu-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.gsm-hard
Dataset Summary
This is the harder version of gsm8k math reasoning dataset (https://huggingface.co/datasets/gsm8k).
We construct this dataset by replacing the numbers in the questions of GSM8K with larger numbers that are less common.
Supported Tasks and Leaderboards
This dataset is used to evaluate math reasoning
Languages
English - Numbers
Dataset Structure
dataset = load_dataset("reasoning-machines/gsm-hard")
DatasetDict({
train: Dataset({… See the full description on the dataset page: https://huggingface.co/datasets/reasoning-machines/gsm-hard.GUIOdyssey
Dataset Card for GUIOdyssey
Repository: https://github.com/OpenGVLab/GUI-Odyssey
Paper: https://arxiv.org/pdf/2406.08451
News⭐️
Latest version of GUIOdyssey released!🎉
This updated version features a larger dataset with 8,334 episodes, as well as richer semantic annotations. Compared to the previous version, we have added more fine-grained low-level instructions, image descriptions, action intentions, and context review for each step. Additionally, we provide bounding… See the full description on the dataset page: https://huggingface.co/datasets/hflqf88888/GUIOdyssey.glaive_toolcall_enBorrowed from: https://huggingface.co/datasets/glaiveai/glaive-function-calling-v2
You can use it in LLaMA Factory by specifying dataset: glaive_toolcall_en.
GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset
📖 The Open Distillation Codex
🌌 The Ultimate Open-Source Distillation Dataset — No Skip, Full, with Attack & Defense 🌌
Where 73 open-source minds converge into one unified stream of intelligence
18M+ Distilled Signals · 7,090 Raw GitHub Repositories · 8 Curated Categories · ~76 GB+
"We did not write this dataset. We assembled it.
Every line is an echo — of a model thinking, a coder drafting, a tutor explaining, a repo breathing.
Seventy-three… See the full description on the dataset page: https://huggingface.co/datasets/Manusagents/GPT-5.5-Gemini-3.1-Pro-Grok-4-Claude-Fable-5-Mythos-5-Qwen-3.7-Max-and-more-Distillation-Dataset.wmt24pp
WMT24++
This repository contains the human translation and post-edit data for the 55 en->xx language pairs released in
the publication
WMT24++: Expanding the Language Coverage of WMT24 to 55 Languages & Dialects.
If you are interested in the MT/LLM system outputs and automatic metric scores, please see MTME.
If you are interested in the images of the source URLs for each document, please see here.
Schema
Each language pair is stored in its own jsonl file.
Each row… See the full description on the dataset page: https://huggingface.co/datasets/google/wmt24pp.GTSinger
GTSinger: A Global Multi-Technique Singing Corpus with Realistic Music Scores for All Singing Tasks
Yu Zhang*, Changhao Pan*, Wenxiang Guo*, Ruiqi Li, Zhiyuan Zhu, Jialei Wang, Wenhao Xu, Jingyu Lu, Zhiqing Hong, Chuxin Wang, LiChao Zhang, Jinzheng He, Ziyue Jiang, Yuxin Chen, Chen Yang, Jiecheng Zhou, Xinyu Cheng, Zhou Zhao | Zhejiang University
Dataset of GTSinger (NeurIPS 2024 Spotlight): A Global Multi-Technique Singing Corpus with Realistic Music Scores for All… See the full description on the dataset page: https://huggingface.co/datasets/AaronZ345/GTSinger.gspc-hub-cards
GSPC hub cards — mill cards, not board axes
SWIFT census (live): https://councilof.ai/api/swift
XRPL reader (live): https://councilof.ai/api/xrpl
One row per signed measurement card: one model, one axis, one date, Ed25519 over the body. A row is MEASURED only when a signed card verifies. Absent (model, axis) pairs are absent — not zero.
Measurement, not certification. Cards are evidence of bytes on a frozen bank at a time — never approval, rating, or safety guarantee.… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-hub-cards.tm-system_promptdrh-System-Prompt-processedMedQA-USMLE-4-options-hfOriginal dataset introduced by Jin et al. in What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams
Citation information:
@article{jin2020disease,
title={What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams},
author={Jin, Di and Pan, Eileen and Oufattole, Nassim and Weng, Wei-Hung and Fang, Hanyi and Szolovits, Peter},
journal={arXiv preprint arXiv:2009.13081},
year={2020}
}
ipo-text
SEC IPO Filings Dataset
A large-scale, comprehensive dataset of 100,000+ filings (S-1 and F-1 filings) filed with the SEC EDGAR system, spanning 1994–2026 and over 20,000 unique registrants.
Every filing has been downloaded and then parsed using the IPO-Mine Python Package. We have extracted three common sections found in these documents (Prospectus Summary, Risk Factors, Legal Matters), and then used an LLM classifier to group them into three categories. For this dataset, we have… See the full description on the dataset page: https://huggingface.co/datasets/gtfintechlab/ipo-text.LIMODataset for LIMO: Less is More for Reasoning
Usage
from datasets import load_dataset
dataset = load_dataset("GAIR/LIMO", split="train")
Citation
If you find our dataset useful, please cite:
@misc{ye2025limoreasoning,
title={LIMO: Less is More for Reasoning},
author={Yixin Ye and Zhen Huang and Yang Xiao and Ethan Chern and Shijie Xia and Pengfei Liu},
year={2025},
eprint={2502.03387},
archivePrefix={arXiv},
primaryClass={cs.CL}… See the full description on the dataset page: https://huggingface.co/datasets/GAIR/LIMO.editorai-telemetryGUIGuard-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.workflow-curatedgaming-500-hours
Gaming Dataset (gaming-1) — 494.7 Hours
Native PC/console gameplay screen-recordings, organized by game. Each workflow
is one play session, trimmed to pure gameplay — login screens, launchers,
desktop, collection-app references, and any watching/streaming are removed.
In-game menus, lobbies, loading, and cutscenes are retained as part of the session.
Workflows: 776
Total gameplay: 494.7 hours
Distinct games: 168
Clip duration (min): median 24.0, p90 90.9, max 457.7
Platforms:… See the full description on the dataset page: https://huggingface.co/datasets/markov-ai/gaming-500-hours.LEMUR
EU Law Dataset – Category 15.10: Environment
This dataset contains official legal documents from the European Union, collected from the EUR-Lex website, specifically under category 15.10: "Environment". The documents span from the year 1961 to 2025 and are provided in multiple European "languages. The original documents are in PDF format and have been converted into various text-based formats using OLMCR.
The dataset splits represent the different "languages available for each… See the full description on the dataset page: https://huggingface.co/datasets/G4KMU/LEMUR.social-sim-bench-gensopenassistant-guanacoThis dataset is a subset of the Open Assistant dataset, which you can find here: https://huggingface.co/datasets/OpenAssistant/oasst1/tree/main
This subset of the data only contains the highest-rated paths in the conversation tree, with a total of 9,846 samples.
This dataset was used to train Guanaco with QLoRA.
For further information, please see the original dataset.
License: Apache 2.0
Opus-WritingPrompts
Opus Writing Prompts
This is a dataset containing 3008 short stories, generated by an unrestrained Claude Opus using Reddit's Writing Prompts as a source. Each sample is generally between 4000-6000 characters long.
These stories were thoroughly cleaned and then further enriched with a title and a series of applicable genres.
Disclaimer: This dataset is extremely varied and includes erotica. You have been warned.
Three files are included:
A ShareGPT dataset, ready to be used for… See the full description on the dataset page: https://huggingface.co/datasets/Gryphe/Opus-WritingPrompts.gspc-boards
GSPC signed board archive
SWIFT census (live): https://councilof.ai/api/swift
XRPL reader (live): https://councilof.ai/api/xrpl
Snapshot/archive of board payloads. Printer language only.
Not a certificate. Hub is a printer of live GET, not a second engine. Fetch fail → UNCHECKABLE.
The live board is the authority
GET https://councilof.ai/api/gspc — quote totals.public_count. This Hub card is a printer of that GET, never a second
engine. If the fetch fails… See the full description on the dataset page: https://huggingface.co/datasets/csoai/gspc-boards.GSM-Symbolic
GSM-Symbolic
This project accompanies the research paper, GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language Models.
Getting Started
In our first release, we provide data for GSM-Symbolic, GSM-Symbolic-P1, and GSM-Symbolic-P2 variants. For each variant, we have released both templates (available on Github), and a sample of generated data that can be used for evaluation.
To load the data, you can use the following code. Note that in… See the full description on the dataset page: https://huggingface.co/datasets/apple/GSM-Symbolic.ChatGPT-4o-Writing-Prompts
ChatGPT-4o Writing Prompts
This is a dataset containing 3746 short stories, generated with OpenAI's chatgpt-4o-latest model and using Reddit's Writing Prompts subreddit as a source. Each sample is generally between 6000-8000 characters long.
These stories were thoroughly cleaned and then further enriched with a title and a series of applicable genres.
Note that I did not touch the Markdown ChatGPT-4o produced by itself to enrich its output, as I very much enjoy the added flavour… See the full description on the dataset page: https://huggingface.co/datasets/Gryphe/ChatGPT-4o-Writing-Prompts.rl-run-archive-2026
RL run archive 2026
Archived raw run artifacts (rollout trajectories, rendered frames, policy and optimizer
checkpoints, configs, logs) from simulation reinforcement-learning experiments, published for
long-term preservation and reproducibility.
Layout mirrors the verified backup trees they were copied from:
tilde/20260915-102000/ and taurus/20260915-085631/: batched tar archives. Every archive
carries a per-file SHA-256 manifest inside it; the batch inventories (9998.json.gz… See the full description on the dataset page: https://huggingface.co/datasets/gavinlaw/rl-run-archive-2026.