Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
RiverraidNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_riverraid_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_riverraid_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_riverraid_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 35a89a0d727589d26dd3516eadecdea1faaf1328586fe80cf236ad421b774df8
- Size of remote file:
- 7.01 MB
- SHA256:
- 00391a403c517f3613c82eb773e826ca4334a1150310beb762f7dfe98cd7a076
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