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:
- 7b3813795bb9a274fb1947a271615b9ee2e00ed9fe0a514f54475504679a7a34
- Size of remote file:
- 20.8 MB
- SHA256:
- 8a8588eb4d0a809f6584f4f5255896a6af7e0e83e79c2b13e188ac733845f255
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