| --- |
| language: |
| - en |
| license: other |
| tags: |
| - code |
| - seeds |
| - oss-instruct |
| - dataset-curation |
| --- |
| |
| # oss-code-seeds |
|
|
| A combined dataset of open-source code snippets (seeds) curated from multiple |
| high-quality sources. The intended use is to serve as seeds for generating |
| coding instruction-response pairs via the OSS-Instruct approach — where a model |
| is prompted with a real code snippet to produce a grounded, diverse coding problem |
| and its solution. |
|
|
| ## Columns |
|
|
| - `seed`: A raw code snippet from open-source software (OSS), serving as the seed |
| - `source`: The original HuggingFace dataset the seed was taken from |
|
|
| ## Sources |
|
|
| | Dataset | Description | |
| |---|---| |
| | `ise-uiuc/Magicoder-OSS-Instruct-75K` | Seeds used to generate the Magicoder dataset via GPT-3.5, multi-language GitHub snippets | |
| | `bigcode/self-oss-instruct-sc2-concepts` | Filtered Python functions from The Stack V1 used in the SelfCodeAlign pipeline | |
|
|
| ## Intended Use |
|
|
| Feed the `seed` column into your own model API to generate coding problems and |
| solutions, effectively replicating or improving upon the OSS-Instruct pipeline |
| with your own model. |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("PursuitOfDataScience/oss-code-seeds", split="train") |
| |
| for row in ds: |
| seed = row["seed"] |
| source = row["source"] |
| # prompt your model with seed to generate a problem + solution |
| ``` |
|
|
