Instructions to use Haricot24601/rl_course_doom_health_gathering_supreme_v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use Haricot24601/rl_course_doom_health_gathering_supreme_v4 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r Haricot24601/rl_course_doom_health_gathering_supreme_v4 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 1f6e27410585c2c5ef8fd5bd65cbc9c619f5d9274fe07a7655aa9f77049431d0
- Size of remote file:
- 2.16 kB
- SHA256:
- b7becfec9b071c981833b321087aaa26e0ea337075abd2c2089e575e54549b42
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.