Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
BoxingNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_boxing_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_boxing_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_boxing_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
Commit History
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Add `agent.pt` and tag the environment
Verified signatureThis commit adds a model that is compatible with the [🥇 Open RL Leaderboard 🥇](https://huggingface.co/spaces/open-rl-leaderboard/leaderboard).425dd29
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Upload replay.mp4 with huggingface_hub
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Upload README.md with huggingface_hub
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Upload cfg.json with huggingface_hub
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Upload checkpoint_p0 with huggingface_hub
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Upload .summary with huggingface_hub
70aeeb2 -
initial commit
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