Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
KungFuMasterNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_kongfumaster_2222 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_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_kongfumaster_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6e064cf6a8ca711df41ce6b9afea8991778b17ba0e24cf8519f01cad1b1a34c4
- Size of remote file:
- 7 MB
- SHA256:
- a4ca219e16a538f61acef4e0d3b19c43342275eff5686a523857f6b343799257
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