datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
OpenR1-Math-220k
OpenR1-Math-220k
Dataset description
OpenR1-Math-220k is a large-scale dataset for mathematical reasoning. It consists of 220k math problems with two to four reasoning traces generated by DeepSeek R1 for problems from NuminaMath 1.5.
The traces were verified using Math Verify for most samples and Llama-3.3-70B-Instruct as a judge for 12% of the samples, and each problem contains at least one reasoning trace with a correct answer.
The dataset consists of two… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/OpenR1-Math-220k.codeforces
Dataset Card for CodeForces
Dataset description
CodeForces is one of the most popular websites among competitive programmers, hosting regular contests where participants must solve challenging algorithmic optimization problems. The challenging nature of these problems makes them an interesting dataset to improve and test models’ code reasoning capabilities. This dataset includes more than 10k unique problems covering the very first contests all the way to 2025.… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/codeforces.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.Mixture-of-Thoughts
Dataset summary
Mixture-of-Thoughts is a curated dataset of 350k verified reasoning traces distilled from DeepSeek-R1. The dataset spans tasks in mathematics, coding, and science, and is designed to teach language models to reason step-by-step. It was used in the Open R1 project to train OpenR1-Distill-7B, an SFT model that replicates the reasoning capabilities of deepseek-ai/DeepSeek-R1-Distill-Qwen-7B from the same base model.
To load the dataset, run:
from datasets import… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/Mixture-of-Thoughts.distill_r1_qwen_math_1.5b_128_solns_math_verificationsDAPO-Math-17k-Processed
Dataset Card for DAPO-Math-17k-Processed
This is a processed version of BytedTsinghua-SIA/DAPO-Math-17k where we have:
Deduplicated the prompts
Reformatted the prompts and ground truth answers to be compatible with TRL's GRPO trainer
We have also derived pure English and Chinese subsets.
The full dataset processing logic can be found in create_dataset.py.
If you find this dataset useful in your work, please cite the original source with:
@misc{yu2025dapoopensourcellmreinforcement… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/DAPO-Math-17k-Processed.codeforces-cots
Dataset Card for CodeForces-CoTs
Dataset description
CodeForces-CoTs is a large-scale dataset for training reasoning models on competitive programming tasks. It consists of 10k CodeForces problems with up to five reasoning traces generated by DeepSeek R1. We did not filter the traces for correctness, but found that around 84% of the Python ones pass the public tests.
The dataset consists of several subsets:
solutions: we prompt R1 to solve the problem and produce code.… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/codeforces-cots.Video-R1-dataThis repository contains the data presented in Video-R1: Reinforcing Video Reasoning in MLLMs.
Code: https://github.com/tulerfeng/Video-R1
Video data folder: CLEVRER, LLaVA-Video-178K, NeXT-QA, PerceptionTest, STAR
Image data folder: Chart, General, Knowledge, Math, OCR, Spatial
Video-R1-COT-165k.json is for SFT cold start, and Video-R1-260k.json is for RL training.
Data Format in Video-R1-COT-165k:
{
"problem_id": 2,
"problem": "What appears on the screen in Russian during the… See the full description on the dataset page: https://huggingface.co/datasets/Video-R1/Video-R1-data.OpenThoughts-114k-mathThis is a filtered and metadata enriched version of open-thoughts/OpenThoughts-114k.
While the original dataset is a valuable resource containing DeepSeek-R1 outputs, it has very little metadata (only 2 fields: system and conversations). It does not contain, for instance, the original solution label, which means that we can not verify the model answers.
What we did
filtered the dataset for math content (math questions were prefixed by "Return your final response within… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/OpenThoughts-114k-math.Vad-R1OpenR1-Math-Raw
OpenR1-Math-Raw
Dataset description
OpenR1-Math-Raw is a large-scale dataset for mathematical reasoning. It consists of 516k math problems sourced from AI-MO/NuminaMath-1.5 with 1 to 8 reasoning traces generated by DeepSeek R1.
The traces were verified using Math Verify and LLM-as-Judge based verifier (Llama-3.3-70B-Instruct)
The dataset contains:
516,499 problems
1,209,403 R1-generated solutions, with 2.3 solutions per problem on average
re-parsed answers… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/OpenR1-Math-Raw.Embodied-R1.5-SFT-Dataset
Embodied-R1.5-SFT-Dataset
🌐 Project Page |
📄 arXiv |
💻 Code |
🧰 EmbodiedEvalKit |
🤗 Models & Datasets
🗓️ Update — 2026-08-20 (20260820). All 34 Stage 1 SFT JSON annotation files have been uploaded to sft_datasets_json/. The complete JSON ↔ image/video data mapping is documented in the Dataset composition table below.
⚠️ Partial release. This repository currently contains only a subset of the full Stage 1 SFT… See the full description on the dataset page: https://huggingface.co/datasets/IffYuan/Embodied-R1.5-SFT-Dataset.R1LiteR1-Distill-SFT
🔉 𝗦𝗟𝗔𝗠 𝗹𝗮𝗯 - 𝗥𝟭-𝗗𝗶𝘀𝘁𝗶𝗹𝗹-𝗦𝗙𝗧 Dataset
Lewis Tunstall, Ed Beeching, Loubna Ben Allal, Clem Delangue 🤗 and others at Hugging Face announced today that they are - 𝗼𝗽𝗲𝗻𝗹𝘆 𝗿𝗲𝗽𝗿𝗼𝗱𝘂𝗰𝗶𝗻𝗴 𝗥𝟭 🔥
We at 𝗦𝗟𝗔𝗠 𝗹𝗮𝗯 (ServiceNow Language Models) have been cooking up something as well.
Inspired by Open-r1, we have decided to open source the data stage-by-stage to support the open source community.
𝗕𝗼𝗼𝗸𝗺𝗮𝗿𝗸 this page!
KEY DETAILS:
⚗️ Distilled… See the full description on the dataset page: https://huggingface.co/datasets/ServiceNow-AI/R1-Distill-SFT.openthoughts_18K_solutions_R1_distill_Llama_8BR1-Code-Interpreter-Data
R1-Code-Interpreter: Training LLMs to Reason with Code via Supervised and Reinforcement Learning
Our code is based on Llama-factory/VeRL/Search-R1 for the SFT and RL training and SymBench/BIG-Bench-Hard/reasoning-gym for datasets/benchmarks of reasoning/planning tasks.
📝 Introduction
R1-Code-Interpreter is the first framework to train LLMs for step-by-step code reasoning using multi-turn supervised fine-tuning and reinforcement learning. By curating 144 diverse… See the full description on the dataset page: https://huggingface.co/datasets/yongchao98/R1-Code-Interpreter-Data.aime_1983_2023_deepseek-r1_traces_16384verifiable-coding-problems-python
Dataset Card for Verifiable Coding Problems Python 10k
This dataset contains all Python problems from PrimeIntellect's verifiable-coding-problems dataset. We have formatted the verification_info and metadata columns to be proper dictionaries, but otherwise the data is the same. Please see their dataset for more details.
openverifiable-enwiki-20260901-20260918-r1-evidence
OpenVerifiableLLM Wikipedia provenance evidence
Development in progress. No production-trained or end-to-end verified model is
published here yet. Synthetic test results do not establish Wikipedia training.
This new AOSSIE repository is reserved for publicly reconstructible inputs,
checkpoints and reports for the OpenVerifiableLLM Wikipedia base model and its
conversational derivative. The governing goal and code are maintained at
AOSSIE-Org/OpenVerifiableLLM.
The intended… See the full description on the dataset page: https://huggingface.co/datasets/AOSSIE/openverifiable-enwiki-20260901-20260918-r1-evidence.Mobile-R1
Dataset Card for Mobile-R1
Dataset Structure
images/: All the screenshots
data.jsonl: The trajectory data
Data Fields
All screenshots are stored in the images/ directory.
We describe the structure of a single trajectory entry from the file data.jsonl, which contains the full interaction trajectories and action history.
app_name: String. The name of the mobile application (e.g., "闲鱼" / Xianyu) where the task is performed.
trajectory_length: Integer. Number of… See the full description on the dataset page: https://huggingface.co/datasets/Mobile-R1/Mobile-R1.multi_SWE_Bench_Rust
multi_SWE_Bench_Rust
数据集描述...
apex-r1-real-world-documents
Apex-R1 Real-World Benchmark Documents
This dataset stores real-world document/data assets collected for Apex-R1 synthetic long-horizon agentic RL workspace generation.
The files are intended as seed workspace materials, not as benchmark task labels. They can be injected into APEX-style filesystem/ or .apps_data/ environments to create more realistic and diverse professional-domain tasks.
Contents
benchmark_documents/
EnterpriseBench/ # CRM invoices… See the full description on the dataset page: https://huggingface.co/datasets/mtybilly/apex-r1-real-world-documents.SEED-Bench-R1This repository contains the datasets presented in Exploring the Effect of Reinforcement Learning on Video Understanding: Insights from SEED-Bench-R1.
distill_r1_qwen_math_1.5b_128_solns_math_trainAM-DeepSeek-R1-Distilled-1.4MFor more open-source datasets, models, and methodologies, please visit our GitHub repository.
AM-DeepSeek-R1-Distilled-1.4M is a large-scale general reasoning task dataset composed of
high-quality and challenging reasoning problems. These problems are collected from numerous
open-source datasets, semantically deduplicated, and cleaned to eliminate test set contamination.
All responses in the dataset are distilled from the reasoning model (mostly DeepSeek-R1) and have undergone
rigorous… See the full description on the dataset page: https://huggingface.co/datasets/a-m-team/AM-DeepSeek-R1-Distilled-1.4M.codeforces-submissions
Dataset Card for CodeForces-Submissions
Dataset description
CodeForces is one of the most popular websites among competitive programmers, hosting regular contests where participants must solve challenging algorithmic optimization problems. The challenging nature of these problems makes them an interesting dataset to improve and test models’ code reasoning capabilities.
This dataset includes millions of real user (human) code submissions to the CodeForces website.… See the full description on the dataset page: https://huggingface.co/datasets/open-r1/codeforces-submissions.physics-r1-eval-outputssn38-submission-r10sn38-submission-r10sn38-r11-sub-80