Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PongNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_pong_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_pong_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_pong_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- a253dc723d82c5cf1571547a9d7fb5aa66383d4dcdf6fab87c7dfbf8274b29af
- Size of remote file:
- 6.98 MB
- SHA256:
- 4100a488428db52ba875ed19e50b933038f3125568720a70e968ae460dcfe046
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