license: other
task_categories:
- text-generation
language:
- en
tags:
- code
- kernel
- osdev
- linux
- freebsd
- openbsd
- netbsd
- rust
- systems-programming
pretty_name: KernelLLM-2
size_categories:
- 100K<n<1M
KernelLLM-2 Dataset
A high-quality raw dataset for training and fine-tuning LLMs on Operating System Development, significantly expanded for the second version.
Overview
This dataset combines raw source code from a variety of mature and hobbyist operating system kernels with thousands of expert-level technical discussions and critiques from the Linux Kernel Mailing List, plus unique Git logic-diff traces.
The source code included in this dataset represents the latest stable versions of the respective repositories as of February 27th 2026.
Dataset Structure
The dataset is provided in Parquet format for optimal compression and integration with the datasets library.
1. kernelllm_dataset_v2.parquet (~1.8 GB)
Unified Knowledge Base:
- Files/Entries: 367,769
- Size: ~1.8 GB (Parquet), ~6.1 GB (Raw JSONL)
- Sources: 20+ Kernel and System Projects.
- Cleaning:
- Preserved
SPDX-License-IdentifierandCopyrightlines while removing generic licensing boilerplate headers to prioritize logic. - Exact and "smart" deduplication across repositories.
- Excluded files < 100 characters to remove boilerplate headers.
- Preserved
Repository Distribution:
| Repository | Entry Count |
|---|---|
| NetBSD | 83,959 |
| Linux | 69,197 |
| FreeBSD | 50,127 |
| OpenBSD | 27,522 |
| illumos | 24,703 |
| Zephyr | 19,066 |
| ReactOS | 17,688 |
| Haiku | 15,472 |
| U-Boot | 12,674 |
| Coreboot | 12,082 |
| SerenityOS | 9,159 |
| QEMU | 7,029 |
| EDK2 | 5,869 |
| Xen Hypervisor | 2,311 |
| musl libc | 1,875 |
| GRUB | 1,706 |
| Asterinas | 1,417 |
| seL4 | 641 |
| Limine | 151 |
| Redox OS | 34 |
2. Specialized Data Types
git_logdiff: (234 entries) Pairs commit messages with filtered logic-diffs to show how code evolves.lkml_critique: (~26,600 pairs) Contentious technical discussions pairing code snippets with maintainer feedback.
3. Dataset Schema
The unified dataset contains three primary data types, each with a specific schema:
Source Code (data_type: "source")
{
"data_type": "source",
"source": "repository_name",
"filepath": "relative/path/to/file.c",
"code": "cleaned_source_code_content"
}
Git Commit Diffs (data_type: "git_logdiff")
{
"data_type": "git_logdiff",
"commit": "commit_sha_hash",
"source": "repository_name",
"message": "commit_message",
"code": "git_diff_output"
}
LKML Critiques (data_type: "lkml_critique")
{
"data_type": "lkml_critique",
"source": "mailing_list_name",
"subject": "[PATCH] subject_line",
"code": "patch_content",
"critique": "maintainer_feedback",
"metadata": {
"author": "reviewer_email",
"date": "email_date",
"thread_id": "thread_identifier",
"is_openbsd": boolean
}
}
Data Processing Features
- Deduplication: Content-based hashing with normalized whitespace
- License Header Cleaning: Preserves SPDX identifiers and copyright lines while removing generic boilerplate
- Size Filtering: Excludes files under 100 characters
- Git-specific: Deduplicates by commit SHA when available
- Critique-specific: Deduplicates based on code + critique content pairs
Dataset Release Strategy
This is the Raw version of the dataset. It is intended for:
- Intermediate Training: Pre-training on high-quality systems code.
- Fine-Tuning: Instruction-tuning models to act as "Kernel Maintainers".
- Research: Analyzing developer communication patterns in low-level systems.
Licensing and Usage
This dataset is a collection of publicly available open-source code and mailing list archives. It contains content governed by multiple licenses. For full details, see the LICENSE file.
- GNU General Public License (GPL) v2/v3 (Linux, seL4, Xen, QEMU, coreboot, GRUB, U-Boot, ReactOS)
- Common Development and Distribution License (CDDL) (illumos)
- BSD 2-Clause / 3-Clause / 4-Clause & ISC (FreeBSD, NetBSD, OpenBSD, SerenityOS, Limine)
- MIT License (Redox, Haiku, musl)
- Apache License 2.0 (Zephyr)
- Mozilla Public License (MPL) 2.0 (Asterinas)
- BSD-2-Clause-Patent (EDK2)
Disclaimer
- Original Licenses Apply: The individual source code files and mailing list archives contained in this dataset remain governed by their original respective licenses.
- Attribution: The
sourceandauthorfields (where available) facilitate attribution. - Research & Ethics: This dataset is provided primarily for research and educational purposes in the field of LLM training and systems programming analysis.
- License Compliance: Users of this dataset are responsible for ensuring that their use of the data complies with all applicable licenses.
Opt-out
If you are a maintainer of one of the included repositories and would like your data removed from future versions of this dataset, please open an issue on the Hugging Face dataset page.