| dataset_info: | |
| features: | |
| - name: lang | |
| dtype: string | |
| - name: seed | |
| dtype: string | |
| splits: | |
| - name: train | |
| num_bytes: 3114466 | |
| num_examples: 10000 | |
| download_size: 1629429 | |
| dataset_size: 3114466 | |
| configs: | |
| - config_name: default | |
| data_files: | |
| - split: train | |
| path: data/train-* | |
| This dataset contains 10000 random snippets of 5-15 lines parsed from [`bigcode/starcoderdata`](https://huggingface.co/datasets/bigcode/starcoderdata). | |
| Specifically, I consider 10 languages: Haskell, Python, cpp, java, typescript, shell, csharp, rust, php, and swift. And, I collect 1000 documents for each language, and then extract 5-15 random lines from the document to create this dataset. | |
| See MagiCoder and their [seed collection](https://github.com/ise-uiuc/magicoder/blob/main/experiments/collect_seed_documents.py#L35) process. In my usecase, I needed some inspiration documents for generating synthetic datasets. |