Update README.md

README.md

@@ -25,12 +25,22 @@ This is a trained model of a **PPO** agent playing **LunarLander-v2**
 using the [stable-baselines3 library](https://github.com/DLR-RM/stable-baselines3).
 
 ## Usage (with Stable-baselines3)
-TODO: Add your code
-
 
 ```python
-from stable_baselines3 import ...
+import gym
+
 from huggingface_sb3 import load_from_hub
 
-...
+from stable_baselines3 import PPO
+from stable_baselines3.common.evaluation import evaluate_policy
+from stable_baselines3.common.env_util import make_vec_env
+
+env = make_vec_env('LunarLander-v2', n_envs=16)
+model = PPO('MlpPolicy', env, verbose=1)
+
+model.learn(total_timesteps=5 * 10**5)
+
+eval_env = gym.make('LunarLander-v2')
+mean_reward, std_reward = evaluate_policy(model, env, n_eval_episodes=10, deterministic=True)
+print(f"Reward mean: {mean_reward:.2f}, Reward STD: {std_reward:.2f}")
 ```