Datasets:
File size: 5,115 Bytes
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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 `<EMAIL>` 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.
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