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:
- 9885e8c318592e947217f3dedfe7a745c014954baeb2512f46cffaff3245937c
- Size of remote file:
- 20.8 MB
- SHA256:
- 714671e2ad4aaf854ec9b56527448d7cd895790f07a874524fc7abe331fc85e9
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