Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
CrazyClimberNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_crazyclimber_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_crazyclimber_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_crazyclimber_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8b049e68aa9db8ee07b24ed9d4473e48ebaedd405dcf04b82cc9b203cee1fac0
- Size of remote file:
- 6.99 MB
- SHA256:
- f20a943a4a6f11f13e94fda6375c3e99b068ae195bec49c752ec9a22e956e379
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