Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
FreewayNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_freeway_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_freeway_2222 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_freeway_2222 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 88a0486220552c69ca6901a72728ce2642ac23f5744a29537bc51fec78d23be7
- Size of remote file:
- 6.98 MB
- SHA256:
- 2137c4d7eee5d54d663cb593c7100d3e8ad9470433774e886494f83103b77465
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.