Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
RobotankNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_robotank_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_robotank_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_robotank_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 23e20c020f60b41cd53e293453801d2d777a75c8b09b600267e5adfbd8aea09b
- Size of remote file:
- 1.95 MB
- SHA256:
- 49db7ad05235a02b737f3f27f99354b12655075c4c854a21e56cf4eae8910bc6
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.