Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
KungFuMasterNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_kongfumaster_1111 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_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_kongfumaster_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9ac2020fa1eab6a72336f6da962487e1fff79aa3ca72d86d5d12e593904aef89
- Size of remote file:
- 7 MB
- SHA256:
- c25bb35e35aecf53ce010f2b52e1e3e09e2e7e87e0b710ff2300f4d2b7720a3a
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