Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use jdawnduan/jddppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use jdawnduan/jddppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="jdawnduan/jddppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download jddppo-LunarLander-v1.zip from jdawnduan/jddppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 147 kB
-
https://huggingface.co/jdawnduan/jddppo-LunarLander-v2/resolve/main/jddppo-LunarLander-v1.zip
- Command line
-
hf download hf://jdawnduan/jddppo-LunarLander-v2/jddppo-LunarLander-v1.zip
-
curl -L -o jddppo-LunarLander-v1.zip https://huggingface.co/jdawnduan/jddppo-LunarLander-v2/resolve/main/jddppo-LunarLander-v1.zip
147 kB
- Xet hash:
- 65d0fb29e370aa5d271fb29aa575b659f13a38f18e27332e36ca29829108fa9a
- Size of remote file:
- 147 kB
- SHA256:
- 5099c7c185892ee8520698c5dd7defbea45d677825b922286ed44383c946e1a1
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