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:
- dc1a4155eabef71c362ddddcf0a148f45d4e2ac51bfcd7227d336c761e58413b
- Size of remote file:
- 20.8 MB
- SHA256:
- 209e716be5451e042efd64010c1ce3a66817aa692ec24856ab4e0a2fd77313c4
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