docs: Added how to load the model

README.md

@@ -26,10 +26,26 @@ model-index:
   ## Usage
 
   ```python
+import gymnasium as gym
+import pickle5 as pickle
+from huggingface_sb3 import load_from_hub
+from hf_course_code import evaluate_agent # Code from the course https://huggingface.co/learn/deep-rl-course/unit2/hands-on#the-evaluation-method-
 
-  model = load_from_hub(repo_id="jostyposty/drl-course-unit-02-taxi-v3", filename="q-learning.pkl")
+model_pickle = load_from_hub(repo_id="jostyposty/drl-course-unit-02-taxi-v3", filename="q-learning.pkl")
 
-  # Don't forget to check if you need to add additional attributes (is_slippery=False etc)
-  env = gym.make(model["env_id"])
+with open(model_pickle, "rb") as f:
+    model = pickle.load(f)
+
+env = gym.make(model["env_id"])
+
+mean_reward, std_reward = evaluate_agent(
+    env,
+    model["max_steps"],
+    model["n_eval_episodes"],
+    model["qtable"],
+    model["eval_seed"],
+)
+result = mean_reward - std_reward
+print(f"Result={result:.2f}, Mean_reward={mean_reward:.2f} +/- {std_reward:.2f}")
   ```