Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use sternn/atari_unit3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use sternn/atari_unit3 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="sternn/atari_unit3", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- aacc09a766322d16e734eca1be4e5a43f4c2012a89f48b7387c1c52ff96605e9
- Size of remote file:
- 34.9 kB
- SHA256:
- b14c0b74edf4000de4038e4c049e6bffa96f9dfaf8f0064649e6e55452512351
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.