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:
- c69942f235d98cf45013f492eff30929af479365464b3efe5c1ad54a03a6c69f
- Size of remote file:
- 6.99 MB
- SHA256:
- a43bb5c5496751692823adb9df9fc914466ad61e045e0ac4392bd4ca5dc92524
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