Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
CrazyClimberNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_crazyclimber_1111 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_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_crazyclimber_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- af1c6f5464ac685be7cd7947cfb2629074ec5ef4afb539d41ee3fa65963778cc
- Size of remote file:
- 1.21 MB
- SHA256:
- 020caa76295a64b041e5af1552ae17bc71714723cddbbc096e4ed817b287a038
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