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:
- fdd67ca4c2f2e0888bbfb7d327ae59ec4ab72ef9a2a0778f4ceec7f229ba882a
- Size of remote file:
- 20.8 MB
- SHA256:
- 0effca1231bf6b3c1409af61d83a0839b0b9ef1f8173994b8cbe0dd67f06d91d
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