Reinforcement Learning
stable-baselines3
deep-reinforcement-learning
LunarLander-v2
Eval Results (legacy)
Instructions to use ImaghT/ppo-LunarLander-v3-optimized with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use ImaghT/ppo-LunarLander-v3-optimized with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="ImaghT/ppo-LunarLander-v3-optimized", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download vec_normalize.pkl from ImaghT/ppo-LunarLander-v3-optimized: direct link, hf CLI and curl.
- Browser
- Download file 2.35 kB
-
https://huggingface.co/ImaghT/ppo-LunarLander-v3-optimized/resolve/main/vec_normalize.pkl
- Command line
-
hf download hf://ImaghT/ppo-LunarLander-v3-optimized/vec_normalize.pkl
-
curl -L -o vec_normalize.pkl https://huggingface.co/ImaghT/ppo-LunarLander-v3-optimized/resolve/main/vec_normalize.pkl
2.35 kB
- Xet hash:
- 17d72b001268192c19d2e7e27bbb52b38cc80c93d11f9c651780583f95bdeb4e
- Size of remote file:
- 2.35 kB
- SHA256:
- 86f1cadcfc4f8b2e63ef7558f88259b8e3e35ee8343f5048b16da891340179f7
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