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ppo-LunarLander-v2
moczard/ppo-LunarLander-v2
ppo-LunarLander-v2 is a reinforcement learning model from moczard. 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 17, 2024
- Updated
- Apr 17, 2024
- SHA
- 1df54ca6
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.
Usage (with Stable-baselines3)
import gymnasium as gym
from stable_baselines3 import PPO
from stable_baselines3.common.evaluation import evaluate_policy
from stable_baselines3.common.monitor import Monitor
model = PPO.load("ppo-LunarLander-v2")
eval_env = Monitor(gym.make("LunarLander-v2"))
mean_reward, std_reward = evaluate_policy(model, eval_env)
print(f"Mean reward={mean_reward} +- {std_reward}")
- Task
- Reinforcement Learning
- Library
- stable-baselines3
- Created
- Apr 17, 2024
- Updated
- Apr 17, 2024