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:
- c79ce06bbc84c4ecd66ec050dedc2b0d2f765669451c77c261ee3dbd6d139a30
- Size of remote file:
- 20.8 MB
- SHA256:
- 5d66925fb0b0d7b52e4d5311af24566ae2791cff924ced07b0efa0b9c2458e57
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