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:
- 8f3de5bd1e9751413218f8ad8363a41b6a026b22ad1efd0cec99957ad33f415a
- Size of remote file:
- 6.99 MB
- SHA256:
- 647ded072e5876e4c2cc6aa2aa3070903b88cca5f62827bd52a44dabc4980724
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