Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
RoadRunnerNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_roadrunner_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_roadrunner_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_roadrunner_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 540fec0608118ed25b25a59e3e0fa035099680892e71171d5e24b080d2848485
- Size of remote file:
- 7.01 MB
- SHA256:
- e4f80cff7018ea100a3f0acfdef79b51faf817d17ee09ad15d4276c173ba49db
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