| We also released [Github code dataset](https://huggingface.co/datasets/codeparrot/github-code), a 1TB of code data from Github repositories in 32 programming languages. It was created from the public GitHub dataset on Google [BigQuery](https://cloud.google.com/blog/topics/public-datasets/github-on-bigquery-analyze-all-the-open-source-code). The dataset can be loaded in streaming mode if you don't want to download it because of memory limitations, this will create an iterable dataset: |
|
|
| ```python |
| from datasets import load_dataset |
| |
| ds = load_dataset("codeparrot/github-code", streaming=True, split="train") |
| print(next(iter(ds))) |
| |
| #OUTPUT: |
| { |
| 'code': "import mod189 from './mod189';\nvar value=mod189+1;\nexport default value;\n", |
| 'repo_name': 'MirekSz/webpack-es6-ts', |
| 'path': 'app/mods/mod190.js', |
| 'language': 'JavaScript', |
| 'license': 'isc', |
| 'size': 73 |
| } |
| |
| ``` |
| You can see that in addition to the code, the samples include some metadata: repo name, path, language, license, and the size of the file. Below is the distribution of programming languages in this dataset. |
|
|
| <p align="center"> |
| <img src="https://huggingface.co/datasets/codeparrot/github-code/resolve/main/github-code-stats-alpha.png" alt="drawing" width="650"/> |
| </p> |
| |
| For model-specific information about the pretraining dataset, please select a model below: |
