update card

README.md

@@ -26,12 +26,28 @@ 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 ...
 from huggingface_sb3 import load_from_hub
 
-...
+from stable_baselines3.common.env_util import make_vec_env
+from stable_baselines3 import PPO
+from stable_baselines3.common.evaluation import evaluate_policy
+
+model_checkpoint = load_from_hub(                # Download model from the hub
+	repo_id="mriusero/ppo-LunarLander-v2",
+	filename="ppo-LunarLander-v2.zip",
+)
+env = make_vec_env("LunarLander-v2", n_envs=1)   # Create a vectorized environment
+model = PPO.load(model_checkpoint, env=env)      # Load the model
+
+print("Evaluating model")                        # Evaluate the model
+mean_reward, std_reward = evaluate_policy(
+    model,
+    env,
+    n_eval_episodes=10,
+    deterministic=True,
+)
+print(f"Mean reward = {mean_reward:.2f} +/- {std_reward}")
+
 ```