code: def get_labels(self, include_freq=False, on_unicode_error='strict'):
          
          a = self.f.getArgs()
          if a.model == model_name.supervised:
              pair = self.f.getLabels(on_unicode_error)
              if include_freq:
                  return (pair[0], np.array(pair[1]))
              else:
                  return pair[0]
          else:
              return self.get_words(include_freq)
docs: Get the entire list of labels of the dictionary optionally
          including the frequency of the individual labels. Unsupervised
          models use words as labels, which is why get_labels
          will call and return get_words for this type of
          model.