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:
- 9cdac43c1bc6da8031bc936816142e72a6d805eab5d6d0c3cfaac398a9695498
- Size of remote file:
- 20.8 MB
- SHA256:
- 87223564c3a18b82f52832c402ca1e3610d7aef1a607dc8870fc6fab1121a165
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.