Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
DemonAttackNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_demonattack_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_demonattack_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_demonattack_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 9f088d322f0a82f2682a4450d1851bbaa1a405b7b22b8d269dce26d6e96afec3
- Size of remote file:
- 6.98 MB
- SHA256:
- 743e86d6fac135e1497f84a6e0e08d5f03635c1e5f228307b5c097286f140e92
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