datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
PatchBench
PatchBench
PatchBench is a benchmark for evaluating AI agents on realistic vulnerability patching tasks: 213 tasks drawn from 32 popular GitHub C/C++ projects. It selects vulnerabilities whose ground-truth fixes lie outside the crash stack, and uses vulnerability transplant plus code mutation to mitigate surface-level fixes and patch memorization.
This repository holds the task metadata, one row per task to identify the project, the exact repository state, the crash, and the… See the full description on the dataset page: https://huggingface.co/datasets/ai-sec-lab/PatchBench.Patchnoisseur
Patchnoisseur
A connoisseur's cellar of CVEs: every NVD CVE joined to its fixing-commit
diff (when one could be found), its NVD description, and its
associated CWE(s) (id, name, short description) — served as a single
Parquet dataset.
351 884 CVEs · 25 015 with a real git diff attached · CVE-1999 → CVE-2026
· ~744 MB on disk (zstd-compressed Parquet, sharded ~300 MB each).
What's in it
One row per CVE in the NVD feed. CVEs without a retrievable patch are… See the full description on the dataset page: https://huggingface.co/datasets/michoo42/Patchnoisseur.nixpkgs-security-patches
nixpkgs-security-patches
Training dataset for fine-tuning LLMs on nixpkgs security patch generation. Derived from real merged security PRs in NixOS/nixpkgs.
Dataset Details
588 training examples / 66 eval examples (654 total)
Format: Multi-turn tool-calling conversations in ChatML JSONL
Each example is a realistic agent session: the model reads the package file, finds the upstream fix, computes hashes via tools, and submits the fix for approval
Hashes and URLs… See the full description on the dataset page: https://huggingface.co/datasets/adastracomputing/nixpkgs-security-patches.act_patch_llama_3.1_8b_counterfact
Training Language Models to Explain Their Own Computations
Paper | Code
This dataset contains activation patching results used for training explainer models to predict how internal interventions affect target model outputs. It was introduced in the paper "Training Language Models to Explain Their Own Computations".
Dataset Summary
The dataset covers the Activation Patching task for the Llama-3.1-8B target model, where explainer models learn to predict the effects of… See the full description on the dataset page: https://huggingface.co/datasets/Transluce/act_patch_llama_3.1_8b_counterfact.dx7-patches-and-prompts
Yamaha DX7 Synthesizer Patches with AI-Generated Prompts
Dataset Description
This is a comprehensive, multi-task dataset designed for fine-tuning language models to understand and generate synthesizer patches for the Yamaha DX7.
The dataset contains over 20,000 examples across three distinct but related tasks, making it ideal for creating models that can not only generate patches but also understand and reason about their structure and validity.
How the Data Was… See the full description on the dataset page: https://huggingface.co/datasets/ccerati/dx7-patches-and-prompts.patch_db
PatchDB: A Large-Scale Security Patch Dataset
Description
To foster large-scale research on vulnerability mitigation and to enable a comparison of different detection approaches, we make our dataset PatchDB from our DSN'21 paper publicly available.
PatchDB is a large-scale security patch dataset that contains around 12,073 security patches and 23,742 non-security patches from the real world.
You can find more details on the dataset in the paper "PatchDB: A Large-Scale… See the full description on the dataset page: https://huggingface.co/datasets/sunlab/patch_db.patchpilot-patchgen
PatchPilot patch-generation dataset
Supervised fine-tuning chats for PatchPilot's patch generator (A2). Each chat is exactly the
prompt PatchPilot's agent sends to its model, followed by the developers' real fix written in the
agent's SEARCH/REPLACE edit format.
Source
Built by scripts/build_patchgen_data.py (seed 42) from the SWE-bench training split
(princeton-nlp/SWE-bench, train) and the gold files' contents from princeton-nlp/SWE-bench_oracle.
The same seeded… See the full description on the dataset page: https://huggingface.co/datasets/Tejaswiniprabhakaran19/patchpilot-patchgen.act_patch_qwen3_8b_counterfact
Training Language Models to Explain Their Own Computations
This dataset is part of the work presented in the paper "Training Language Models To Explain Their Own Computations".
Code | Paper
Introduction
Language models (LMs) can learn to faithfully describe their internal computations. This dataset contains results from Activation Patching interventions on the Qwen3-8B target model using CounterFact data. Explainer models are trained on this data to predict how… See the full description on the dataset page: https://huggingface.co/datasets/Transluce/act_patch_qwen3_8b_counterfact.PatchBPptdbench-llama-dapo-implementation-task-monkey-patch-011-dataset
PTDBench dataset snapshot: task_monkey_patch_011
This repository stores the immutable runtime dataset snapshot for one
materialized PTDBench task. It intentionally excludes model weights and
training checkpoints.
PTDBench family: llama_dapo_implementation
Source evaluation metric: val-core/math_dapo/acc/mean@1
Provenance: Processed from BytedTsinghua-SIA/DAPO-Math-17k; task-specific bytes are pinned.
License: Apache-2.0
The artifact manifest records every hydrated runtime path… See the full description on the dataset page: https://huggingface.co/datasets/LIF1014/ptdbench-llama-dapo-implementation-task-monkey-patch-011-dataset.