code: def predict_proba(self, text):
          
          assert isinstance(text, str)
  
          words = self.tokenizer(text)
          X = self.preprocessor.transform([words])
          y = self.model.predict(X)
          y = y[0]  # reduce batch dimension.
  
          return y
docs: Probability estimates.
  
          The returned estimates for all classes are ordered by the
          label of classes.
  
          Args:
              text : string, the input text.
  
          Returns:
              y : array-like, shape = [num_words, num_classes]
              Returns the probability of the word for each class in the model,