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/pytorch_variables.pth from DarkRodry/ppo-LunarLander-v2: direct link, hf CLI and curl.
- Browser
- Download file 431 Bytes
-
https://huggingface.co/DarkRodry/ppo-LunarLander-v2/resolve/main/base_tutorial_model/pytorch_variables.pth
- Command line
-
hf download hf://DarkRodry/ppo-LunarLander-v2/base_tutorial_model/pytorch_variables.pth
-
curl -L -o pytorch_variables.pth https://huggingface.co/DarkRodry/ppo-LunarLander-v2/resolve/main/base_tutorial_model/pytorch_variables.pth
431 Bytes
- Xet hash:
- 75f010d6d2240b1b0a5dca21c00213fbdcfd1593ec2ecca829b524a798d89bf8
- Size of remote file:
- 431 Bytes
- SHA256:
- d030ad8db708280fcae77d87e973102039acd23a11bdecc3db8eb6c0ac940ee1
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