Instructions to use Epoching/rl_course_vizdoom_health_gathering_supreme with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use Epoching/rl_course_vizdoom_health_gathering_supreme with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r Epoching/rl_course_vizdoom_health_gathering_supreme -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 391f9283128db48aecf5b52a25d6bd0fb94456154c95d1e48321d0077e627b4c
- Size of remote file:
- 21.1 MB
- SHA256:
- 1838b1ce10ecb5cd4f74c8b59a2b6636ddec93c41967cb3183ba90dcfecd167c
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.