Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
AsterixNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_asterix_2222 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_asterix_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_asterix_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- ec53e7aa1ea7ba921bda8adbe3ba6629abe4f8a5aeed48377de98b828b287a7f
- Size of remote file:
- 6.99 MB
- SHA256:
- 7a18fafbe5f6292d52ceaa8c025af1a8ef79b5b77546ea0850489bccfd9f4474
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