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:
- 7ceb1b08d2991785723d515d752fc99dd8bc2b0ff50f4b4a852193dda0ca03c4
- Size of remote file:
- 20.8 MB
- SHA256:
- d5b0b6cff43bc6d1a0843424b04a1bb92ade698079cf3ce74362b7f221afea08
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