datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SteamScreenshots-Bugs
Samples
HDR_Pretrain
HDR-Pretrain: A Pretraining Dataset for 3D HDR Reconstruction
Paper | Code | Project page
HDR-Pretrain is a synthetic multi-view dataset for pretraining 3D high dynamic range (HDR) reconstruction models. It provides multi-exposure low dynamic range (LDR) images and corresponding HDR references to support learning 3D HDR scene representations from multi-view observations and rendering HDR images from novel viewpoints.
The dataset contains 168 Blender-rendered indoor scenes. Each… See the full description on the dataset page: https://huggingface.co/datasets/Bugjudger/HDR_Pretrain.hf-bug-templca-bug-localization
🏟️ Long Code Arena (Bug localization)
This is the benchmark for the Bug localization task as part of the
🏟️ Long Code Arena benchmark.
The bug localization problem can be formulated as follows: given an issue with a bug description and a repository snapshot in a state where the bug is reproducible, identify the files within the repository that need to be modified to address the reported bug.
The dataset provides all the required components for evaluation of bug localization… See the full description on the dataset page: https://huggingface.co/datasets/JetBrains-Research/lca-bug-localization.ntu-reconstructionrecreate-hf-upload-bug-v1-v1-trimrecreate-bug-post-fix-v1-trimThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos",
"tilt.pos"
]… See the full description on the dataset page: https://huggingface.co/datasets/VibeCuisine/recreate-bug-post-fix-v1-trim.recreate-bug-pre-fix-v1-trimThis dataset was created using LeRobot.
Dataset Structure
meta/info.json:
{
"codebase_version": "v3.0",
"fps": 20,
"features": {
"action": {
"dtype": "float32",
"names": [
"shoulder_pan.pos",
"shoulder_lift.pos",
"elbow_flex.pos",
"wrist_flex.pos",
"wrist_roll.pos",
"gripper.pos",
"tilt.pos"
]… See the full description on the dataset page: https://huggingface.co/datasets/VibeCuisine/recreate-bug-pre-fix-v1-trim.fantastic_bugs_resultbug-localization
Bug Localization
This is the data for Bug Localization benchmark.
How-to
Since the dataset is private, if you haven't used HF Hub before, add your token via huggingface-cli first:
huggingface-cli login
List all the available configs via datasets.get_dataset_config_names and choose an appropriate one
Load the data via load_dataset:
from datasets import load_dataset
# Select a configuration from ["py", "java", "kt", "mixed"]
configuration = "py"
# Select a split from… See the full description on the dataset page: https://huggingface.co/datasets/tiginamaria/bug-localization.bugbounty-hunter-v1
Bug Bounty Hunter v1 - Fine-Tuning Dataset
The largest public dataset for training AI models on bug bounty hunting expertise.
Overview
52,743 instruction-response pairs covering 40+ vulnerability types across 6 categories, extracted from real-world bug bounty writeups and security research.
Dataset Summary
This dataset is designed to fine-tune language models to become expert bug bounty hunters. Each example contains a technical instruction and a… See the full description on the dataset page: https://huggingface.co/datasets/0xn0cta/bugbounty-hunter-v1.agentmorph-bugs-v0.1
AgentMorph
AgentMorph is a trajectory-level metamorphic testing benchmark for tool-using
LLM agents. Instead of requiring a labeled correct answer for every task,
AgentMorph mutates a task in a way that should preserve the user's intent,
reruns the agent, and checks whether the original and mutated trajectories
preserve a rule-specific invariant.
This repository is the anonymous review artifact for the AgentMorph paper. It
contains synthetic e-commerce agent trajectories… See the full description on the dataset page: https://huggingface.co/datasets/Anonymous2535k/agentmorph-bugs-v0.1.SWE-universe-repaired-bug-pilot-trajectories
SWE-universe repaired BugPilot trajectories
Combined trajectory artifacts for the Qwen3.6 + mini-swe-agent evaluation of VmaxRL/SWEUniverse-Repaired-Bugpilot.
This dataset contains one row per evaluated task in metadata.jsonl, plus per-task files under trajectories//. The combined set uses the main full eval and replaces the two original infra-failure rows with the clean infra rerun trajectories.
Summary:
rows: 804
effective attempts: 804
passes: 629
pass rate: 0.782338
infra… See the full description on the dataset page: https://huggingface.co/datasets/VmaxRL/SWE-universe-repaired-bug-pilot-trajectories.eval-DCAgent_a1-bugsinpy_DCAgent2_terminal_bench_2bugpilot-bugintro-lm-modify-gpt55-1k-oracleclean-443-20260506
BugPilot LM-Modify GPT-5.5 1k Oracle-Clean 443
This dataset contains the 443 task directories from the repaired LM-modify workspace that currently pass the oracle audit.
Source workspace: /data/augustine/demiurge/projects/experimental/training_swe_skrl_tinker/audits/lm_modify_target600_repair_workspace_20260506_v4
Source audit: full_oracle_postswaps_20260506_multinode32_c4
Export date: 2026-05-06
The directory layout matches the original task dataset layout: one task directory per… See the full description on the dataset page: https://huggingface.co/datasets/VmaxRL/bugpilot-bugintro-lm-modify-gpt55-1k-oracleclean-443-20260506.rl_rl-conf_24GP_base-yaml_mode-path_r2eg-nl2b-stac-bugs-fixt_trai-data_exp_rpt_stac-php-largBilge-Turkish-CoT-50K
Bilge: Turkish Chain-of-Thought Dataset (50K)
50,000 örneklik Türkçe Chain-of-Thought (CoT) reasoning fine-tuning veri seti.
Bilge, Türkçe büyük dil modellerinin adım adım düşünme (reasoning) kapasitesini
geliştirmek amacıyla hazırlanmış bir Chain-of-Thought veri setidir.
Veri setindeki her örnek, modelin önce <think> blokları içinde görünür bir
muhakeme süreci yürütmesini, ardından kullanıcıya yapılandırılmış ve detaylı
bir cevap vermesini öğretmek üzere tasarlanmıştır.
Bu… See the full description on the dataset page: https://huggingface.co/datasets/bugrabilge/Bilge-Turkish-CoT-50K.bug-bounty-pentest-en
Bug Bounty & Pentesting Methodologies
Methodologies (OWASP, PTES), checklists by app type, attack techniques, platforms, report templates and tools.
Links
French version
AYI NEDJIMI Consultants
DCAgent2_swebench-verified-random-100-folders_DCAgent_nl2bash-nl2bash-bugsseq_Qac56e7c8SWEUniverse-Repaired-Bugpilot
SWEUniverse Repaired Bugpilot
Reformatted repaired dataset from VmaxRL/SWEUniverse-Repaired-Bugpilot.
Rows: 804
Columns are exactly:
Task id
initial p2p
new p2p
initial f2p
new f2p
default test command
new test command
test parser
image name
patch
problem statement
repo
initial f2p/initial p2p are the source labels before repair; new f2p/new p2p are the repaired labels used for evaluation.
Bugzilla_Eclipse_Bug_Reports_Dataset
Special Thanks
Special thanks to Lamkanfi, Ahmed; Pérez, Javier; and Demeyer, Serge for their contributions. Please cite their paper, as this dataset is the processed part of their dataset.
Citation
@INPROCEEDINGS{6624028,
author={Lamkanfi, Ahmed and Pérez, Javier and Demeyer, Serge},
booktitle={2013 10th Working Conference on Mining Software Repositories (MSR)},
title={The Eclipse and Mozilla defect tracking dataset: A genuine dataset for mining bug information}… See the full description on the dataset page: https://huggingface.co/datasets/AliArshad/Bugzilla_Eclipse_Bug_Reports_Dataset.SWE-bench_mini_bug_input_check_bug_report__fs-oraclesynthetic_on-site_rebar_data
Synthetic On-site Rebar Data (SORD)
This dataset accompanies the published paper: https://doi.org/10.1016/j.autcon.2024.105953.
Dataset Details
Dataset Description
SORD is a synthetic dataset of on-site rebar images with instance segmentation annotations. It comprises over 25,000 images generated using Autodesk Revit, featuring various rebar structure types (columns, beams, slabs, and walls) with diverse diameters, spacing configurations, and… See the full description on the dataset page: https://huggingface.co/datasets/bugwei/synthetic_on-site_rebar_data.SWE-bench_validated_12_18_bug_report_bug_report__fs-oracleierd-codeforces-subtle-bugs
IERD Codeforces subtle bugs
This public dataset contains 682 generated buggy C++ solutions for 682 Codeforces
problems. Each solution passes most tests in the frozen source corpus and fails from
one to five stored human or Hugging Face tests. The package also contains the frozen
manifest, provenance files, and aggregate reports from the final test generation
study.
Source and version
The problems, tests, and reference solution candidates come from… See the full description on the dataset page: https://huggingface.co/datasets/shivank21/ierd-codeforces-subtle-bugs.benchname-bug-localization
🥷 BenchName (Bug localization)
This is the benchmark for the Bug localization task as part of the
🥷 BenchName benchmark.
The bug localization problem can be formulated as follows: given an issue with a bug description and a repository snapshot in a state where the bug is reproducible, identify the files within the repository that need to be modified to address the reported bug.
The dataset provides all the required components for evaluation of bug localization approaches in… See the full description on the dataset page: https://huggingface.co/datasets/anon-iclr-submission/benchname-bug-localization.BuggedPythonLeetCode
Dataset Description
edit: fixed some bugs with datasets not handling all pyarrow types.
Dataset Summary
This dataset consists of Python coding problems from LeetCode, which have been bugged using the OpenBugger package. This dataset provides a unique opportunity to study the debugging process in a controlled and replicable environment.
For each correct code snippet, 15 bugged versions were attempted. For each succesfully bugged version, a corresponding question mimicking… See the full description on the dataset page: https://huggingface.co/datasets/NeuroDragon/BuggedPythonLeetCode.SWE-bench_4o_bug_input_check_bug_report__fs-oracleSWE-bench_asterinas_bug_report__fs-oraclerl_rl-conf_24GP_base-yaml_mode-path_r2eg-nl2b-stac-bugs-fixt_trai-data_exp_rpt_stac-self-larg