Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
SeaquestNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_seaquest_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_seaquest_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_seaquest_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
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