| --- |
| pretty_name: Code Reasoning Data |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - code |
| - sft |
| - reinforcement-learning |
| license: other |
| license_name: source-specific-licenses |
| license_link: LICENSE |
| size_categories: |
| - 10K<n<100K |
| configs: |
| - config_name: kodcode_sft |
| default: true |
| data_files: |
| - split: train |
| path: data/kodcode/sft/train.parquet |
| - split: validation |
| path: data/kodcode/sft/validation.parquet |
| - config_name: kodcode_rl |
| data_files: |
| - split: train |
| path: data/kodcode/rl/train.parquet |
| - split: validation |
| path: data/kodcode/rl/validation.parquet |
| - config_name: taco_leetcode_sft |
| data_files: |
| - split: train |
| path: data/taco_leetcode/sft/train.parquet |
| - split: validation |
| path: data/taco_leetcode/sft/validation.parquet |
| - config_name: taco_leetcode_rl |
| data_files: |
| - split: train |
| path: data/taco_leetcode/rl/train.parquet |
| - split: validation |
| path: data/taco_leetcode/rl/validation.parquet |
| --- |
| |
| # Code Reasoning Data |
|
|
| Code-training data with SFT answers, executable RL tests, and category labels. |
|
|
| | Configuration | Train | Validation | |
| |---|---:|---:| |
| | `kodcode_sft` | 35,974 | 100 | |
| | `kodcode_rl` | 35,974 | 100 | |
| | `taco_leetcode_sft` | 21,779 | 100 | |
| | `taco_leetcode_rl` | 17,249 | 100 | |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("./dataset", "kodcode_sft") |
| # After upload, replace ./dataset with your Hugging Face dataset repository ID. |
| ``` |
|
|
| SFT: use `messages` or `prompt` / `response`. RL: use `prompt` and |
| `reward_model.ground_truth`. Apply the target model's template at training time. |
| Use only the documented input/target fields; labels and tests are metadata. |
|
|
| KodCode uses ten primary categories; TACO/LeetCode uses seven category-removal |
| groups. Their taxonomies and historical ablation memberships are separate. |
|
|
| The TACO SFT validation split is new in this release. Other splits are historical. |
| These configurations are separate experiments, not a joint SFT-to-RL split. |
| Historical TACO RL validation overlaps the original SFT pool on 71 problems. |
| See [TACO/LeetCode notes](docs/taco_leetcode.md) for historical export. |
|
|
| ```bash |
| pip install -r requirements.txt |
| python scripts/validate_release.py --hf |
| ``` |
|
|
| Source-specific licenses apply; see [LICENSE](LICENSE) and [NOTICE](NOTICE.md). |
| Reward scripts require Linux; usage and limits are in [verification notes](docs/rl_verification.md). |
|
|
