Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
EnduroNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_enduro_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_enduro_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_enduro_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- cb46b11b4becafe33c6ead7da37e14b757b869a025747e1c00c8e1b72b7c5587
- Size of remote file:
- 7.9 MB
- SHA256:
- 96f38bfb8ecd185c2d320a31e63e89e0abc3045aa622a6d04af628a8788f7d0f
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