Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
AmidarNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_amidar_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_amidar_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_amidar_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 50dba775f84712e39cc93531468b49239481b53736530230872ac31b335afa11
- Size of remote file:
- 1.75 MB
- SHA256:
- ee99145890f8aceef40024b917dc2592db4f43ed356f7289a86aa65c69baf10d
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