Datasets:
Tasks:
Text Generation
Modalities:
Text
Formats:
arrow
Languages:
code
Size:
10M - 100M
ArXiv:
License:
| tags: | |
| - code | |
| - github | |
| - commits | |
| - multilingual | |
| license: apache-2.0 | |
| task_categories: | |
| - text-generation | |
| language: | |
| - code | |
| size_categories: | |
| - 10M<n<100M | |
| <div align="center"> | |
| # Themis-Git-Commits | |
| [](https://arxiv.org/abs/2605.00754) | |
| [](https://huggingface.co/collections/project-themis/themis-reward-model-collection) | |
| [](https://huggingface.co/collections/project-themis/themis-preference-datasets-and-benchmarks) | |
| [](https://github.com/iNeil77/Themis) | |
| [](https://hub.docker.com/repository/docker/ineil77/themis/general) | |
| </div> | |
| ## Overview | |
| **Themis-Git-Commits** is a large-scale dataset of single-file code commits mined from **permissively licensed** GitHub repositories via the [BigQuery GitHub public dataset](https://console.cloud.google.com/marketplace/product/github/github-repos). The SQL query restricts to repositories under permissive open-source licenses only (MIT, Apache-2.0, BSD-2/3-Clause, ISC, CC0-1.0, EPL-1.0, MPL-2.0, Unlicense, AGPL-3.0, LGPL-2.1, Artistic-2.0). The BigQuery snapshot used contains commits up to **early 2022** — predating the widespread availability of LLM code generation tools — ensuring that all code changes in the dataset represent **genuine human-authored preferences**. | |
| This is the **raw commit dataset** — prior to merging with pull request data to subset only for merged commits. It serves as the foundational data source for the commit-based preference pairs in [Themis-CodePreference](https://huggingface.co/datasets/project-themis/Themis-CodePreference), which is used to train the [Themis-RM](https://huggingface.co/collections/project-themis/themis-reward-model-collection) suite of multilingual code reward models. | |
| Each row represents a single commit that changes exactly one file in a repository with a permissive open-source license. The dataset includes the commit metadata (SHA, message, timestamp, license) along with the pre-commit and post-commit file contents, enabling downstream construction of code-change preference pairs across multiple quality dimensions. | |
| ## Collection Pipeline | |
| The commit mining pipeline is described in detail in the [Themis paper](https://arxiv.org/abs/2605.00754) and the [Dataset](https://github.com/iNeil77/Themis/tree/main/Dataset) folder in the GitHub repository. The BigQuery SQL query and scraping infrastructure are modified from the [OctoPack](https://arxiv.org/abs/2308.07124) pipeline ([CommitPack](https://huggingface.co/datasets/bigcode/commitpack)); the subsequent filtering, classification, and preference construction stages are original to Themis. At a high level: | |
| 1. **BigQuery Mining** — A [GoogleSQL query](https://github.com/iNeil77/Themis/blob/main/Dataset/Commit_Mining_SQL/consolidated_query.sql) (modified from [OctoPack](https://arxiv.org/abs/2308.07124)) extracts single-file commits from `bigquery-public-data.github_repos`, filtering for permissive licenses, target programming languages, and non-trivial commit messages. | |
| 2. **Repository Reputation Filtering** — Commits are subset to those originating from [curated high-reputation repositories](https://github.com/iNeil77/Themis/tree/main/Dataset/Repos) (15+ GitHub stars, 5+ contributors, 10+ issues). | |
| 3. **Content Retrieval** — The pre-commit (`old_contents`) and post-commit (`new_contents`) file contents are fetched from GitHub via shallow git fetches using [retrieve_commit_contents.py](https://github.com/iNeil77/Themis/blob/main/Dataset/Utils/retrieve_commit_contents.py). | |
| 4. **MinHash Deduplication** — Near-duplicate content is removed using [MinHash LSH deduplication](https://github.com/iNeil77/Themis/blob/main/Dataset/Utils/minHash_dedupe_local.py) (shingle size 5, 256 permutations, Jaccard threshold 0.7). | |
| ## Downstream Processing (Not in This Dataset) | |
| The steps below are applied downstream and are **not** reflected in this raw dataset: | |
| - **Extension Filtering** — Commits are filtered so the changed file's extension matches a target programming language. Applied in [Themis-Git-Commits-Merged](https://huggingface.co/datasets/project-themis/git-commits-merged). | |
| - **Pull Request Cross-Referencing** — Commits are cross-referenced with [GHTorrent](https://ghtorrent.org/) pull request data (through end of 2021) to retain only non-reverted commits that are part of successfully merged pull requests, ensuring implicit human validation. Applied in [Themis-Git-Commits-Merged](https://huggingface.co/datasets/project-themis/git-commits-merged). | |
| - **Temporal Subsetting** — For training data ([Themis-CodePreference](https://huggingface.co/datasets/project-themis/Themis-CodePreference)), only commits pushed before **March 2019** are retained. For benchmark data ([Themis-CodeRewardBench](https://huggingface.co/datasets/project-themis/Themis-CodeRewardBench)), commits are scoped to **June 2019 – January 2021** from disjoint repositories. | |
| - **Aspect Classification** — Commits are assigned to quality dimensions (Functional Correctness, Runtime Efficiency, Memory Efficiency, Security Hardness, Readability & Maintainability) using criteria-specialized [ModernBERT](https://huggingface.co/answerdotai/ModernBERT-base) commit classifiers, trained on seed positives retrieved via [curated term lists](https://github.com/iNeil77/Themis/tree/main/Dataset/Commit_Mining_Terms). | |
| - **LLM Scoring & Instruction Synthesis** — Frontier LMs validate preference strength and generate realistic inverse instructions. | |
| - **LLM-as-a-Judge Preference Labelling** — Multi-sample voting with frontier LMs produces consensus preference labels. | |
| ## Dataset Schema | |
| <div align="center"> | |
| | Column | Type | Description | | |
| |:---|:---:|:---| | |
| | `commit` | string | Git commit SHA | | |
| | `subject` | string | First line of the commit message | | |
| | `message` | string | Full commit message body | | |
| | `repos` | string | Comma-separated list of repository names containing this commit | | |
| | `file_path` | string | Path of the changed file | | |
| | `license` | string | SPDX license identifier of the source repository | | |
| | `unix_time` | int64 | Committer timestamp (seconds since epoch) | | |
| | `new_contents` | string | File contents after the commit (post-commit) | | |
| | `old_contents` | string | File contents before the commit (pre-commit) | | |
| </div> | |
| ## Filters Applied During Mining | |
| <div align="center"> | |
| | Filter | Purpose | | |
| |:---|:---| | |
| | **License allowlist** | MIT, Apache-2.0, BSD-2-Clause, BSD-3-Clause, ISC, CC0-1.0, EPL-1.0, MPL-2.0, Unlicense, AGPL-3.0, LGPL-2.1, Artistic-2.0 | | |
| | **Language allowlist** | Python, Java, JavaScript, C, C#, C++, TypeScript, Go, Ruby | | |
| | **Message length** | 10 < length < 15,000 characters | | |
| | **Message blocklist** | ~50 low-signal messages excluded (e.g., "initial commit", "wip", "yolo") | | |
| | **Pattern exclusion** | Merge commits and CI push messages filtered out | | |
| | **Same-path constraint** | `old_path = new_path` — file was modified in place, not renamed or moved | | |
| | **Single-file constraint** | Commit touches exactly one file | | |
| | **Content retrieval** | Both pre-commit and post-commit file contents successfully fetched | | |
| | **Near-deduplication** | MinHash LSH with Jaccard threshold 0.7 | | |
| </div> | |
| ## Usage | |
| ```python | |
| from datasets import load_dataset | |
| dataset = load_dataset("project-themis/git-commits") | |
| # Inspect a sample | |
| sample = dataset["train"][0] | |
| print(f"Commit: {sample['commit']}") | |
| print(f"Subject: {sample['subject']}") | |
| print(f"License: {sample['license']}") | |
| print(f"File: {sample['file_path']}") | |
| print(f"Old contents length: {len(sample['old_contents'])}") | |
| print(f"New contents length: {len(sample['new_contents'])}") | |
| ``` | |
| ## License | |
| This dataset is released under the [Apache 2.0 License](https://www.apache.org/licenses/LICENSE-2.0). The source commits are drawn exclusively from repositories with permissive open-source licenses (see filter table above). | |
| ## Citation | |
| ```bibtex | |
| @article{themis2025, | |
| title={Themis: Training Robust Multilingual Code Reward Models for Flexible Multi-Criteria Scoring}, | |
| author={Paul, Indraneil and Gurevych, Iryna and Glava\v{s}, Goran}, | |
| journal={arXiv preprint arXiv:2605.00754}, | |
| year={2025} | |
| } | |
| ``` |