Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PitfallNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_pitfall_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_pitfall_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_pitfall_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ec3d9a28d7e5c6d8aa2c7662f21dcef821ea14df9083e9aa78750a1331104c0
- Size of remote file:
- 20.8 MB
- SHA256:
- 1bfb27fa76f0bacf2beddd4a0a345bf4af48740ecb0dc6a8aed945b10f8c63e2
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