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:
- 9380f5e2271450c269fce305d5d4c4b1761965aeb52398f0c7aaa48ca61387b7
- Size of remote file:
- 20.7 MB
- SHA256:
- 3e875d6966baf15a6bac13c0148ddb8c26d0e8f5ecae1a257b4c0ef0b97b186e
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