Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
BeamRiderNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_beamrider_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_beamrider_3333 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_beamrider_3333 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- fe5c481467a490cbd1d46025bf05822e4467d77ffaf75a6fcc468224fde02b32
- Size of remote file:
- 7.53 MB
- SHA256:
- bc265f43a44da7905c098366eb7fd6615d94fa24a1ab49d108da996eada1fd03
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