Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
AtlantisNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_atlantis_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_atlantis_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_atlantis_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 696f9730744517dde89e71f4962d67c8f33c224fa01a1d629d86854d39e710ce
- Size of remote file:
- 6.98 MB
- SHA256:
- eefa148d8ed2e5eac3d87460142c5463601a5a74db4df7ec653d11211118a1da
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