Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
HeroNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_hero_3333 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_hero_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_hero_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- f3c97ff5eb8b03b0cda0fa08b81615f5921a70f2937120483b213859aeb45009
- Size of remote file:
- 7.01 MB
- SHA256:
- 253693b028372ba852cc5657361af7944f1bfc1c114f350b2b16b5ff33ef870b
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