AntonDergunov/LunarLander_PPO
This model was trained with PPO using Stable-Baselines3 on LunarLander-v3.
Usage
import gymnasium as gym
from stable_baselines3 import PPO
from huggingface_hub import hf_hub_download
model_path = hf_hub_download(repo_id="AntonDergunov/LunarLander_PPO", filename="model.zip")
model = PPO.load(model_path, device="cpu")
env = gym.make("LunarLander-v3")
obs, info = env.reset()
for _ in range(1000):
action, _ = model.predict(obs, deterministic=True)
obs, reward, terminated, truncated, info = env.step(action)
if terminated or truncated:
obs, info = env.reset()
Evaluation results
- Mean Reward on LunarLander-v3self-reported264.910
- Std Reward on LunarLander-v3self-reported19.753