Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
EnduroNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_enduro_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_enduro_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_enduro_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a805a3d0d677f7ffe6c321c32c785525bde4ee61974246b04e626bf0334ccb5b
- Size of remote file:
- 6.99 MB
- SHA256:
- 6d6c9f1ca55606e2b7faa28d0ece3e031e451f6eb280e1a1f78c25c6072a2b2c
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