code: def mtcars():
      "Model with common level effects only"
      data = bmb.load_data("mtcars")
      data["am"] = pd.Categorical(
          data["am"], categories=[0, 1], ordered=True
      )
      model = bmb.Model("mpg ~ hp * drat * am", data)
      idata = model.fit(tune=500, draws=500, random_seed=1234)
      return model, idata
  
file_path: bambi/tests/test_interpret_messages.py
imports: import bambi
  import pandas
  import pytest
  from bambi.interpret import plot_comparisons, plot_predictions, plot_slopes
label_desc: Use image node_id 1 for calling a global function with example usage: mtcars() and returns: model,  idata