ch-bz/ppo-LunarLander-v2

PPO Agent playing LunarLander-v2

This is a trained model of a PPO agent playing LunarLander-v2 using the stable-baselines3 library.
Created during the 'Deep RL Course'(https://huggingface.co/learn/deep-rl-course/unit0/introduction). Trained with 2000000 timesteps.

Usage (with Stable-baselines3)

import gymnasium as gym
from stable_baselines3 import PPO
from stable_baselines3.common.env_util import make_vec_env
from huggingface_sb3 import load_from_hub

# Load the model
model_name = "LunarLander-v2"
model_path = load_from_hub(repo_id="ch-bz/ppo-" + model_name, filename=model_name + ".zip")
model = PPO.load(model_path)

# Demonstrate the model with 4 parallel instances
vec_env = make_vec_env(model_name, n_envs=4)

obs = vec_env.reset()
while True:
    action, _states = model.predict(obs)
    obs, rewards, dones, info = vec_env.step(action)
    vec_env.render("human")