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ppo-LunarLander-v2
Sun0901/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from Sun0901. Use it for the reinforcement learning task on the model card, and read the license before you ship it in a product. It is set up for stable-baselines3.
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
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At a glance
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Access
- Public
- Created
- Apr 23, 2025
- Updated
- Apr 23, 2025
- SHA
- eb85b8de
Model card
From the Hugging Face model README
PPO Agent playing LunarLander-v2
This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
It was part of a reinforcement learning study exercise using stable-baselines3.
- Environment:
LunarLander-v2fromgymnasium - Algorithm: PPO
- Timesteps: 1,000,000
- Platform: Local Jupyter (Windows, Python 3.10)
This is a study log, not intended for deployment.
Usage (with Stable-baselines3)
You can use the following code to load the trained agent from the Hugging Face Hub:
from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub
# Load model from Hub
repo_id = "Sun0901/ppo-LunarLander-v2"
filename = "ppo-LunarLander-v2.zip"
checkpoint = load_from_hub(repo_id, filename)
model = PPO.load(checkpoint)
# Now you can use `model.predict()` to evaluate or deploy the agent.
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Apr 23, 2025
- Updated
- Apr 23, 2025