Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
FreewayNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_freeway_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_freeway_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_freeway_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 5d67bc8b2c2575032ec8fcc4028cfbeabc251ad7dceafc6aab2d49313d817fb6
- Size of remote file:
- 6.98 MB
- SHA256:
- af1943a3f7cab57e29e2f1e46d183b1706661f02275bb412251dc0f8adf273de
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.