Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
AssaultNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_assault_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_assault_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_assault_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
File size: 132 Bytes
2f8fcd7 | 1 2 3 4 | version https://git-lfs.github.com/spec/v1
oid sha256:004d58be32a3cf3f0eb825e1ea8cc994277e29867eb964fe1c9666af183ea337
size 1800223
|