Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
DoubleDunkNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_doubledunk_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_doubledunk_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_doubledunk_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 6d25c012ced9f658fdf3e8e6955a000dee602cf0cba51e0122d3af86c8771330
- Size of remote file:
- 7.01 MB
- SHA256:
- 94ee34a9ab2d349c2ad5680e1cace0510ddfdfb3c00ebac12fe3413663790a55
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