Update README.md

README.md

@@ -26,12 +26,41 @@ 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
+TODO: Diego's code
 
 
 ```python
-from stable_baselines3 import ...
-from huggingface_sb3 import load_from_hub
+import gymnasium as gym
+from stable_baselines3.common.vec_env import DummyVecEnv
+from stable_baselines3.common.env_util import make_vec_env
+
+from huggingface_sb3 import package_to_hub
+
+## TODO: Define a repo_id
+## repo_id is the id of the model repository from the Hugging Face Hub (repo_id = {organization}/{repo_name} for instance ThomasSimonini/ppo-LunarLander-v2
+repo_id = 
+
+# TODO: Define the name of the environment
+env_id = 
+
+# Create the evaluation env and set the render_mode="rgb_array"
+eval_env = DummyVecEnv([lambda: Monitor(gym.make(env_id, render_mode="rgb_array"))])
+
+
+# TODO: Define the model architecture we used
+model_architecture = ""
+
+## TODO: Define the commit message
+commit_message = ""
+
+# method save, evaluate, generate a model card and record a replay video of your agent before pushing the repo to the hub
+package_to_hub(model=model, # Our trained model
+               model_name=model_name, # The name of our trained model 
+               model_architecture=model_architecture, # The model architecture we used: in our case PPO
+               env_id=env_id, # Name of the environment
+               eval_env=eval_env, # Evaluation Environment
+               repo_id=repo_id, # id of the model repository from the Hugging Face Hub (repo_id = {organization}/{repo_name} for instance ThomasSimonini/ppo-LunarLander-v2
+               commit_message=commit_message)
 
 ...
 ```