Reinforcement Learning
sample-factory
TensorBoard
deep-reinforcement-learning
PitfallNoFrameskip-v4
Eval Results (legacy)
Instructions to use edbeeching/atari_2B_atari_pitfall_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_pitfall_1111 with sample-factory:
python -m sample_factory.huggingface.load_from_hub -r edbeeching/atari_2B_atari_pitfall_1111 -d ./train_dir
- Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c2a2eeaa8e91db42de0594b65c93f3d645bb45bd25c2412abfee74cbc6bcb13b
- Size of remote file:
- 20.8 MB
- SHA256:
- c1974e94d3252d3dee3ca9661b765dfdb8793160a88f6fac42b53244c638460d
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.