Reinforcement Learning
stable-baselines3
SpaceInvadersNoFrameskip-v4
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use pm390/dqn-SpaceInvadersNoFrameskip-v4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use pm390/dqn-SpaceInvadersNoFrameskip-v4 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="pm390/dqn-SpaceInvadersNoFrameskip-v4", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download dqn-SpaceInvadersNoFrameskip-v4.zip from pm390/dqn-SpaceInvadersNoFrameskip-v4: direct link, hf CLI and curl.
- Browser
- Download file 13.7 MB
-
https://huggingface.co/pm390/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/dqn-SpaceInvadersNoFrameskip-v4.zip
- Command line
-
hf download hf://pm390/dqn-SpaceInvadersNoFrameskip-v4/dqn-SpaceInvadersNoFrameskip-v4.zip
-
curl -L -o dqn-SpaceInvadersNoFrameskip-v4.zip https://huggingface.co/pm390/dqn-SpaceInvadersNoFrameskip-v4/resolve/main/dqn-SpaceInvadersNoFrameskip-v4.zip
13.7 MB
- Xet hash:
- 706e0e2b81023c69ec40514488830bb79ef034006103f8bb4b2a81cd71e684e6
- Size of remote file:
- 13.7 MB
- SHA256:
- 5d93b4bc6f502280afcef9a5de726103b6b742cf2566c4b933a4d77ec030baee
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