Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use DarkRodry/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use DarkRodry/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="DarkRodry/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download base_tutorial_model/policy.optimizer.pth from DarkRodry/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 87.9 kB
-
https://huggingface.co/DarkRodry/ppo-LunarLander-v2/resolve/main/base_tutorial_model/policy.optimizer.pth
- Command line
-
hf download hf://DarkRodry/ppo-LunarLander-v2/base_tutorial_model/policy.optimizer.pth
-
curl -L -o policy.optimizer.pth https://huggingface.co/DarkRodry/ppo-LunarLander-v2/resolve/main/base_tutorial_model/policy.optimizer.pth
87.9 kB
- Xet hash:
- 019833c2b90e12fb5561f7b3cea51ba7fbe3c92b6b39248c56cc873ba84141e9
- Size of remote file:
- 87.9 kB
- SHA256:
- b4253deee1456965e614a19012791a4c1dc52b75138dfaed6dc6cfdee884792e
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