Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
SolarisNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_solaris_2222 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_solaris_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_solaris_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8ba4c08a8824401ed84181bb4e98edc48a4a7ed8e2ff51cb82e58332c250bb56
- Size of remote file:
- 7.01 MB
- SHA256:
- 53a0bcd1a020a887ded3e581ac4723c27429b0b74a92f8bb9f99e5eb4b21ff7b
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