Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
GravitarNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_gravitar_3333 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_gravitar_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_gravitar_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 16f4f84549c4e89600be171cb8f985b69bcc7addfb464b3fcfde329427ac75e7
- Size of remote file:
- 7.01 MB
- SHA256:
- a1c2659244d864f5cb235c96f17d8e015e3259f7adaa7f264804a3c96c9db86a
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