--- dataset_info: - config_name: annotated features: - name: messages list: - name: role dtype: string - name: content dtype: string - name: language dtype: string - name: prompt_type dtype: string - name: lint_errors dtype: int64 - name: cyclomatic_complexity dtype: int64 - name: license dtype: string - name: commit dtype: string - name: repos dtype: string - name: new_file dtype: string - name: status dtype: string - name: error dtype: string - name: is_valid_syntax dtype: bool splits: - name: train num_bytes: 338825015 num_examples: 145058 download_size: 291448763 dataset_size: 338825015 - config_name: sft features: - name: messages list: - name: role dtype: string - name: content dtype: string - name: language dtype: string - name: prompt_type dtype: string - name: lint_errors dtype: int64 - name: cyclomatic_complexity dtype: int64 - name: license dtype: string - name: commit dtype: string - name: repos dtype: string - name: new_file dtype: string splits: - name: train num_bytes: 276611786 num_examples: 122018 download_size: 242436696 dataset_size: 276611786 configs: - config_name: annotated data_files: - split: train path: annotated/train-* - config_name: sft data_files: - split: train path: sft/train-* language: - code - en license: other source_datasets: - bigcode/commitpackft task_categories: - text-generation pretty_name: CodeAlign curated CommitPackFT license_name: per-sample-permissive tags: - code - sft - commitpackft - code-quality --- # CodeAlign — curated CommitPackFT (8 languages) Instruction/code pairs from [`bigcode/commitpackft`](https://huggingface.co/datasets/bigcode/commitpackft), filtered for syntax validity (tree-sitter), per-language lint errors, cyclomatic complexity, internal duplication and cross-sample near-duplicates (MinHash/LSH). Built as the SFT set of [CodeAlign](https://github.com/Sergasgr/codealign); the pipeline, thresholds and the full curation report live in that repository. | config | rows | contents | |---|---|---| | `sft` (default) | 122,018 | accepted samples — the SFT training set minus the rows dropped for secrets (see Privacy) | | `annotated` | 145,058 | every processed sample with its curation verdict (`status`, `error`) | ```python from datasets import load_dataset sft = load_dataset("Sergasgr/codealign-commitpackft", "sft", split="train") ``` ## Format `messages` is ChatML (`user` prompt, `assistant` target file). Two prompt types, derived from the commit itself: `new_file` (write-from-spec; commit created the file) and `edit` (existing file + commit message as instruction). 84.6% of `sft` rows are `edit`. ## Languages (`sft`) | language | rows | |---|---| | javascript | 45,084 | | python | 39,725 | | java | 15,779 | | c_sharp | 8,062 | | typescript | 4,339 | | cpp | 3,668 | | go | 3,034 | | rust | 2,327 | ## Licensing and provenance Only samples whose upstream `license` is one of apache-2.0, bsd-2-clause, bsd-3-clause, cc0-1.0, isc, mit, unlicense are included; the licence of every sample is in its `license` column and applies to that sample's code. | license | `sft` rows | |---|---| | mit | 76,499 | | apache-2.0 | 26,849 | | bsd-3-clause | 11,913 | | bsd-2-clause | 3,887 | | isc | 1,423 | | unlicense | 985 | | cc0-1.0 | 462 | As in CommitPackFT, each row keeps its source `commit` and `repos` so the copyright holder can be identified (100.0% of `sft` rows carry provenance). Code authors who want their code removed can open an issue on the GitHub repository. ## Known issues in the quality columns `lint_errors` holds the values computed by the v1.0 curation run, which had linter bugs (the data was not re-curated): - **C++, JavaScript, TypeScript:** `lint_errors` is always 0, so these languages were filtered on syntax, complexity and duplication only. cpplint's total was parsed from the wrong output stream (fixed in the repository afterwards); ESLint ≥ 9 rejects the `--no-eslintrc` command line (still open). - **Python:** every value includes ruff's summary line (+1, or +2 when ruff also printed a fix hint), so the actual number of violations is 1–2 lower (fixed in the repository afterwards). ## Privacy - Rows containing a high-confidence secret (private key blocks, AWS / GitHub / Slack / Google / Stripe credentials) were dropped: 48 from `sft`, 56 from `annotated`. - E-mail addresses (other than documentation and GitHub no-reply domains) were replaced with `` in 8,272 `sft` rows. - Detection is pattern-based and will miss some personal data; do not use this dataset to identify individuals. ## Decontamination 13-gram overlap of every HumanEval and MBPP problem (prompt + canonical solution) against the Python samples is reported in `src/notebooks/01_curation_report.ipynb` of the GitHub repository. ## Citation Upstream data: Muennighoff et al., *OctoPack: Instruction Tuning Code Large Language Models* (2023), arXiv:2308.07124.