Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PrivateEyeNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_privateye_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_privateye_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_privateye_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 346e4447e3572bbb25e451c9522c35b73cf6982d70773902f79d2f99e205380e
- Size of remote file:
- 7.01 MB
- SHA256:
- 2d4d43a80c52b98539484ee34990b546f03c54877acbf114b029ea8992fcdf9b
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