Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
RoadRunnerNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_roadrunner_2222 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sample-factory
How to use edbeeching/atari_2B_atari_roadrunner_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_roadrunner_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 02dc63226353fdbda8994684cd34aac38cd264aaefceb5ad1a34eaf5bbb94898
- Size of remote file:
- 7.01 MB
- SHA256:
- 7c28f053f572240781f50d4602328c29f8ffc697eac6282983dcd1d58807fe48
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