Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PitfallNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_pitfall_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_pitfall_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_pitfall_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ef7ebddcd3a187fe62f20db9a24e1f12d30b5715abe15b2369cb434a9387a841
- Size of remote file:
- 20.8 MB
- SHA256:
- b4a63ebac8200d2653c21e4b658916e869b5ccc6f05219c633d2ac16a7f19071
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