Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
EnduroNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_enduro_3333 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_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_enduro_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 4943f7067dbb8a8d42bc3097b4161f2fba0e994394125bd80cf5a559b3f0247f
- Size of remote file:
- 6.99 MB
- SHA256:
- 2f1a1d796c439ff45373ccfc04a0aaed6d6753e0d439b4e69d2a047279c5924f
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