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:
- 80522222a993b66271b31f49d4ff10af5ae6d43ea57e60a57fc4a2c6e0949725
- Size of remote file:
- 20.8 MB
- SHA256:
- 0d667a609ab4ed165a69443dd331fa44aa29d1d4425f26eae77392dd6b21b121
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