Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PhoenixNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_phoenix_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_phoenix_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_phoenix_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6348ba7103ec6f6df4c1f230a8ef424aa14a5741550127142f070f931cad74ce
- Size of remote file:
- 5.7 MB
- SHA256:
- c2206cbc2787566fb5655ae8a93afb827529e467f6db704f8f544edaee396787
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