Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
GravitarNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_gravitar_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_gravitar_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_gravitar_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cd7c4a4972862e6e28623b473d302344d81ce96595e720b2b57992eb1879bc18
- Size of remote file:
- 7.01 MB
- SHA256:
- 564ca3aefc2a18415162f745e7b99db4a089b53bf4af3556f6dc271fda463f4b
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