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:
- 11e9111f7c915126be4ab8c7a2763677ff6402129c4a87a041fb3495d6978c04
- Size of remote file:
- 20.8 MB
- SHA256:
- e0531d7dcb144d68d20615671b4e2483d23a6df668c902bda433dccf91e87f9a
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