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:
- 4035cc3497199e57b09e13206e8fa1711e487197d5f6eea1f0c9c3abc0267099
- Size of remote file:
- 20.8 MB
- SHA256:
- aaa9532185806491a6a9053b8b9c1d2531e1088c60c2c47d317b32fe65b01eab
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