Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
DemonAttackNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_demonattack_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_demonattack_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_demonattack_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 050c1285143e8d24374c9dddee5adff7d4df55dabccc613034ad40a87b06526f
- Size of remote file:
- 22 MB
- SHA256:
- ea918b2f8693170c8d6d28ede3b6a8dd44da77920b5445de7263b990e86a6a66
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