Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
KungFuMasterNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_kongfumaster_3333 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_kongfumaster_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_kongfumaster_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4ad38418ad0bf77f6e501b47717b6cc89c6d5527c7093209b13f66c8174c0806
- Size of remote file:
- 7 MB
- SHA256:
- 63b19e60a31e7869cca4a90e97aa9f9229143ca49e21021ecaf7a660ea0d6e94
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