Reinforcement Learning
stable-baselines3
LunarLander-v2
deep-reinforcement-learning
Eval Results (legacy)
Instructions to use DanielPaull/ppo-LunarLander-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- stable-baselines3
How to use DanielPaull/ppo-LunarLander-v2 with stable-baselines3:
from huggingface_sb3 import load_from_hub checkpoint = load_from_hub( repo_id="DanielPaull/ppo-LunarLander-v2", filename="{MODEL FILENAME}.zip", ) - Notebooks
- Google Colab
- Kaggle
Download ppo-LunaLander-V2-DP.zip from DanielPaull/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 147 kB
-
https://huggingface.co/DanielPaull/ppo-LunarLander-v2/resolve/main/ppo-LunaLander-V2-DP.zip
- Command line
-
hf download hf://DanielPaull/ppo-LunarLander-v2/ppo-LunaLander-V2-DP.zip
-
curl -L -o ppo-LunaLander-V2-DP.zip https://huggingface.co/DanielPaull/ppo-LunarLander-v2/resolve/main/ppo-LunaLander-V2-DP.zip
147 kB
- Xet hash:
- e9e0dd1053d66475d0c81207539a4d2d5a4aa454a981aa8fda739090b4fda13a
- Size of remote file:
- 147 kB
- SHA256:
- 41bcc80339a4e39c3c22c1e07e77a026740faac37f540a95c9af89a81338402e
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