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MinhDuc4705/ppo-LunarLander-v3
ppo-LunarLander-v3 is a reinforcement learning model from MinhDuc4705. 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-v3 using the stable-baselines3 library.
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From the Hugging Face model README
This is a trained model of a PPO agent playing LunarLander-v3 using the stable-baselines3 library.
import gymnasium as gym
from stable_baselines3 import PPO
from huggingface_sb3 import load_from_hub
# 1. Load the model from Hugging Face Hub
repo_id = "MinhDuc4705/ppo-LunarLander-v3"
filename = "ppo-LunarLander-v3.zip"
checkpoint = load_from_hub(repo_id, filename)
model = PPO.load(checkpoint)
# 2. Enjoy the agent
env = gym.make("LunarLander-v3", render_mode="human")
obs, _ = env.reset()
for _ in range(1000):
action, _ = model.predict(obs)
obs, reward, done, truncated, info = env.step(action)
env.render()
if done or truncated:
obs, _ = env.reset()
env.close()