| --- |
| dataset_info: |
| features: |
| - name: code |
| dtype: string |
| - name: repo_path |
| dtype: string |
| - name: parsed_code |
| dtype: string |
| - name: quality_prob |
| dtype: float64 |
| - name: learning_prob |
| dtype: float64 |
| splits: |
| - name: train |
| num_bytes: 852705076967 |
| num_examples: 65509810 |
| download_size: 0 |
| dataset_size: 852705076967 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| --- |
| # Dataset Card for "starcoder_labeled" |
| |
| [Starcoder data](https://huggingface.co/datasets/bigcode/starcoderdata), with several popular languages selected, short sequences filtered out, then labeled based on learning quality (educational value) and code quality. |
| |
| A good heuristic is to take anything with `>.5` code quality and `>.3` learning quality. But you may want to vary the thresholds by language, depending on your target task. |
