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:
- 8ed808f6b6969e490d694a2f4e3a0ca03a4b24fdaba523067ce6e0d2789b4a59
- Size of remote file:
- 20.8 MB
- SHA256:
- a43774d5db99709eb6043dd5761f115dd8e1a8c205261ca27ed7611a3e19409f
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