We also released [Github code dataset](https://huggingface.co/datasets/lvwerra/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("lvwerra/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/lvwerra/github-code/resolve/main/github-code-stats-alpha.png" alt="drawing" width="650"/>
</p>

Below is the distribution of the pretraining data size of some code models:
<p align="center">
    <img src="https://huggingface.co/datasets/loubnabnl/repo-images/resolve/main/data_distrub.png" alt="drawing" width="450"/>
</p>

For detailed model-specific information about the pretraining dataset, please select a model below: