Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PhoenixNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_phoenix_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_phoenix_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_phoenix_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
Download agent.pt from edbeeching/atari_2B_atari_phoenix_1111: direct link, hf CLI and curl.
- Browser
- Download file 6.99 MB
-
https://huggingface.co/edbeeching/atari_2B_atari_phoenix_1111/resolve/main/agent.pt
- Command line
-
hf download hf://edbeeching/atari_2B_atari_phoenix_1111/agent.pt
-
curl -L -o agent.pt https://huggingface.co/edbeeching/atari_2B_atari_phoenix_1111/resolve/main/agent.pt
6.99 MB
- Xet hash:
- 5f19041ec61e6ec9b79527d003b425a329a715eaebb94933e304c670b3a30055
- Size of remote file:
- 6.99 MB
- SHA256:
- 253907ec85de120918c12c39bbeddca9381a3cc6ed72c5ca01f9a2f8783a4ed3
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