Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
FishingDerbyNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_fishingderby_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_fishingderby_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_fishingderby_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ba1740b4b8efeb0502ee249d80409023514002af22b903c1a7e98662130ffa12
- Size of remote file:
- 7.01 MB
- SHA256:
- 0b093a970a99333e1b0c0ec5df45ce105c4ac479a5363719e8ec24289bc6fd3f
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