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README.md

@@ -22,8 +22,8 @@ model-index:
     - type: mean_reward
       value: -0.31
       name: mean_reward
-predict_config:
-  preview_file: replay.mp4
+
+
 ---
 
 # PPO on RBC2D-hard-v0 (FluidGym)
@@ -52,6 +52,23 @@ Each seed is contained in its own subdirectory. You can load a model using:
 ```python
 from stable_baselines3 import PPO
 model = PPO.load("0/ckpt_latest.zip")
+
+**Important:** The models were trained using ```fluidgym==0.0.2```. In order to use
+them with newer versions of FluidGym, you need to wrap the environment with a
+`FlattenObservation` wrapper as shown below:
+```python
+import fluidgym
+from fluidgym.wrappers import FlattenObservation
+from stable_baselines3 import PPO
+
+env = fluidgym.make("RBC2D-hard-v0")
+env = FlattenObservation(env)
+model = PPO.load("path_to_model/ckpt_latest.zip")
+
+obs, info = env.reset(seed=42)
+
+action, _ = model.predict(obs, deterministic=True)
+obs, reward, terminated, truncated, info = env.step(action)
 ```
 
 ## References