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:
- 12a24ae1d14a0772b5efca2947017fc537dd070749c15d238d66bb33d88b40e1
- Size of remote file:
- 20.8 MB
- SHA256:
- ff39076f9dc8727c58d5814ca28bd0f3707ab4a1e70d0ebb2e3cd4b3b5d8b56b
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