datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
medical-o1-reasoning-SFT
News
[2025/04/22] We split the data and kept only the medical SFT dataset (medical_o1_sft.json). The file medical_o1_sft_mix.json contains a mix of medical and general instruction data.
[2025/02/22] We released the distilled dataset from Deepseek-R1 based on medical verifiable problems. You can use it to initialize your models with the reasoning chain from Deepseek-R1.
[2024/12/25] We open-sourced the medical reasoning dataset for SFT, built on medical verifiable problems and an… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/medical-o1-reasoning-SFT.SWE-Bench-Verified-O1-reasoning-high-results
SWE-Bench Verified O1 Dataset
Executive Summary
This repository contains verified reasoning traces from the O1 model evaluating software engineering tasks. Using OpenHands + CodeAct v2.2, we tested O1's bug-fixing capabilities on the SWE-Bench Verified dataset, achieving a 28.8% success rate across 500 test instances.
Overview
This dataset was generated using the CodeAct framework, which aims to improve code generation through enhanced action-based reasoning.… See the full description on the dataset page: https://huggingface.co/datasets/AlexCuadron/SWE-Bench-Verified-O1-reasoning-high-results.ioi-eval-openrouter_openai_o1ioi-eval-openrouter_openai_o1-miniSWE-Bench-Verified-O1-native-tool-calling-reasoning-high-results
SWE-Bench Verified O1 Dataset
Executive Summary
This repository contains verified reasoning traces from the O1 model evaluating software engineering tasks. Using OpenHands + CodeAct v2.2, we tested O1's bug-fixing capabilities using their native tool calling capabilities on the SWE-Bench Verified dataset, achieving a 45.8% success rate across 500 test instances.
Overview
This dataset was generated using the CodeAct framework, which aims to improve code… See the full description on the dataset page: https://huggingface.co/datasets/AlexCuadron/SWE-Bench-Verified-O1-native-tool-calling-reasoning-high-results.OpenO1-SFTThis repository contains the dataset used for fine-tuning a language model using SFT for Chain-of-Thought Activation from the paper Generative AI Act II: Test Time Scaling Drives Cognition Engineering.
Code: https://github.com/GAIR-NLP/cognition-engineering
🎉🎉🎉This repository contains the dataset used for fine-tuning a language model using SFT for Chain-of-Thought Activation.
🌈🌈🌈The dataset is designed to enhance the model's ability to generate coherent and logical reasoning sequences.… See the full description on the dataset page: https://huggingface.co/datasets/O1-OPEN/OpenO1-SFT.medical-o1-verifiable-problem
Introduction
This dataset features open-ended medical problems designed to improve LLMs' medical reasoning. Each entry includes a open-ended question and a ground-truth answer based on challenging medical exams. The verifiable answers enable checking LLM outputs, refining their reasoning processes.
For details, see our paper and GitHub repository.
Citation
If you find our data useful, please consider citing our work!
@misc{chen2024huatuogpto1medicalcomplexreasoning… See the full description on the dataset page: https://huggingface.co/datasets/FreedomIntelligence/medical-o1-verifiable-problem.sonic-o1
SONIC-O1: A Real-World Benchmark for Evaluating Multimodal Large Language Models on Audio-Video Understanding
🎯 What is SONIC-O1?
The first open-source benchmark for evaluating omnimodal video understanding with systematic fairness analysis. SONIC-O1 requires models to jointly process audio, video, and social context from real-world interactions—not just transcripts.
Key… See the full description on the dataset page: https://huggingface.co/datasets/vector-institute/sonic-o1.o11y-bench-leaderboard
O11y Bench Leaderboard Submissions
This repository accepts leaderboard submissions for o11y-bench, Grafana's benchmark for LLM agents on observability and SRE tasks.
How to Submit
Fork this repository
Create a new branch for your submission
Add your submission under submissions/o11y-bench/1.0/<agent>__<model(s)>/
Open a Pull Request
Submission Structure
submissions/
o11y-bench/
1.0/
<agent>__<model>/
metadata.yaml #… See the full description on the dataset page: https://huggingface.co/datasets/grafanalabs/o11y-bench-leaderboard.verified-reasoning-o1-gpqa-mmlu-pro
Reasoning PRM Preference Dataset
This dataset contains reasoning traces from multiple sources (GPQA Diamond and MMLU Pro), labeled with preference information based on correctness verification.
Dataset Description
Overview
The dataset consists of reasoning problems and their solutions, where each example has been verified for correctness and labeled with a preference score. It combines data from two main sources:
GPQA Diamond
MMLU Pro
Data Fields… See the full description on the dataset page: https://huggingface.co/datasets/ariaattarml/verified-reasoning-o1-gpqa-mmlu-pro.arm_O1
REBench — arm / O1
Binary analysis dataset extracted with Ghidra 11.x from the REBench benchmark suite.
Features per row (one row = one function)
Column
Description
arch / opt_level
Architecture & optimization flag
package / binary_name
Source package and executable
original_function_name
Real symbol name (from unstripped binary)
stripped_function_name
Generic name used in stripped binary
original_code
Decompiled C with original names… See the full description on the dataset page: https://huggingface.co/datasets/Xtest/arm_O1.GPQA-Verified-Thinking-O1-RatedDataset Contains Solution to GPQA , Provided by Gemini-2.0-Thinking
Pass@1 , Prompt Engineered to Align better to solve scintefic questions
ACCURACY: 64.65
Correct-Questions: 353
Verified Using Gemini-2.0
Rated(max 10) by Gemini-2.0
Column
Description
arch / opt_level
Architecture & optimization flag
package / binary_name
Source package and executable
original_function_name
Real symbol name (from unstripped binary)
stripped_function_name
Generic name used in stripped binary
original_code
Decompiled C with original names… See the full description on the dataset page: https://huggingface.co/datasets/Xtest/x64_O1.x86_O1
REBench — x86 / O1
Binary analysis dataset extracted with Ghidra 11.x from the REBench benchmark suite.
Features per row (one row = one function)
Column
Description
arch / opt_level
Architecture & optimization flag
package / binary_name
Source package and executable
original_function_name
Real symbol name (from unstripped binary)
stripped_function_name
Generic name used in stripped binary
original_code
Decompiled C with original names… See the full description on the dataset page: https://huggingface.co/datasets/Xtest/x86_O1.GPQA-Thinking-O1mips_O1
REBench — mips / O1
Binary analysis dataset extracted with Ghidra 11.x from the REBench benchmark suite.
Features per row (one row = one function)
Column
Description
arch / opt_level
Architecture & optimization flag
package / binary_name
Source package and executable
original_function_name
Real symbol name (from unstripped binary)
stripped_function_name
Generic name used in stripped binary
original_code
Decompiled C with original names… See the full description on the dataset page: https://huggingface.co/datasets/Xtest/mips_O1.o1-journeyDataset for O1 Replication Journey: A Strategic Progress Report
Usage
from datasets import load_dataset
dataset = load_dataset("GAIR/o1-journey", split="train")
Citation
If you find our dataset useful, please cite:
@misc{o1journey,
author = {Yiwei Qin and Xuefeng Li and Haoyang Zou and Yixiu Liu and Shijie Xia and Zhen Huang and Yixin Ye and Weizhe Yuan and Zhengzhong Liu and Yuanzhi Li and Pengfei Liu},
title = {O1 Replication Journey: A Strategic Progress Report –… See the full description on the dataset page: https://huggingface.co/datasets/GAIR/o1-journey.llamav-o1-instruct-stage2
LlamaV-o1 Stage 2 Instruction Train set
This dataset is the same as the LLaVa-CoT train set but in multi-turn format. Here is a sample
{
"image": <image>,
"id": 10,
"conversations": [
{
"from": "human",
"value": "Question: Which country is highlighted?\nContext: N/A\nOptions: (A) Solomon Islands (B) Nauru (C) Vanuatu (D) Fiji\nSummarize how you will approach the problem and explain the steps you will take to reach the answer."
},
{
"from": "gpt"… See the full description on the dataset page: https://huggingface.co/datasets/ahmedheakl/llamav-o1-instruct-stage2.o1js-clinicversion https://git-lfs.github.com/spec/v1
oid sha256:4bcf87ecfbbb8e07a01b21415a970c8b53a5283bf6872b657040d3f45c9241f7
size 31
o1x-think-v1OpenO1-SFT-Ultra
openo1-sft-ultra-35m-data
Instruction
We have released the openo1-sft-ultra-35m-data, which contains 35 million data points. It is based on existing open-source datasets and synthesized using the openo1-qwen-sft model. We first collected open-source datasets and then annotated the data based on difficulty, quality, and question types using the qwen-2.5-72b-instruct model. To ensure the difficulty and quality of the data, we only retained data where both the difficulty and… See the full description on the dataset page: https://huggingface.co/datasets/O1-OPEN/OpenO1-SFT-Ultra.medical-o1-reasoning-SFT-Ko
Introduction
The original data was used to fine-tune HuatuoGPT-o1, a medical LLM designed for advanced medical reasoning. Original dataset was constructed using GPT-4o, which searches for solutions to verifiable medical problems and validates them through a medical verifier.
For details, see their paper and GitHub repository.
Translation
For translation into Korean, I used gemini-2.0-flash-exp model w/ temperature=0.5 setting.
Prompt
You are a highly… See the full description on the dataset page: https://huggingface.co/datasets/ChuGyouk/medical-o1-reasoning-SFT-Ko.llamav-o1-instruct-stage1
LlamaV-o1 Stage 1 Train set
This the training set for the curriculum learning stage of LlamaV-o1. The dataset is curated from Geo170k (50k samples) and PixmoCapQA (30k samples). Here is a sample of the dataset:
{
"image": <image>,
"id": 20,
"conversations: [
{
"from": "human",
"value": "<image>If in the provided figure,CA and CB have the same length, AD and BD have the same length, M is the midpoint of CA, N is the midpoint of CB, and angle ADN measures 80… See the full description on the dataset page: https://huggingface.co/datasets/ahmedheakl/llamav-o1-instruct-stage1.LASA_rl_2reverse_engineering_code_dataset_O1_x64_O1Qwen2.5-Math-7B-Instruct-Skywork-o1-Open-PRM-Qwen-2.5-7B-best_of_n-completionso1x_big_v1_cleanOpenO1-SFT-Prodpo-medical-o1-synthMagpie-Reasoning-V2-250K-CoT-Skywork-O1-Llama-3.1-8B
Project Web: https://magpie-align.github.io/
Arxiv Technical Report: https://arxiv.org/abs/2406.08464
Codes: https://github.com/magpie-align/magpie
Abstract
Click Here
High-quality instruction data is critical for aligning large language models (LLMs). Although some models, such as Llama-3-Instruct, have open weights, their alignment data remain private, which hinders the democratization of AI. High human labor costs and a limited, predefined scope for prompting prevent… See the full description on the dataset page: https://huggingface.co/datasets/Magpie-Align/Magpie-Reasoning-V2-250K-CoT-Skywork-O1-Llama-3.1-8B.