@Ednaunfortunately it seems that the only way to load a model logged using the Feature Store client to perform batch scoring is by using using fe.score_batch(model_uri, df).

If you need to use the model to predict probabilities, then maybe you can log a custom pyfunc.ModelWrapper (https://mlflow.org/docs/latest/python_api/mlflow.pyfunc.html#pyfunc-create-custom) and in the predict() function you return the result of model.predict_proba().