code: def text_regression_model(
      name, train_data, preproc=None, metrics=["mae"], verbose=1
  ):
      """
      ```
      Build and return a text regression model.
  
      Args:
          name (string): one of:
                        - 'fasttext' for FastText model
                        - 'nbsvm' for NBSVM model
                        - 'linreg' for linear regression using embedding layers
                        - 'bigru' for Bidirectional GRU with pretrained word vectors
                        - 'bert' for BERT Text Classification
                        - 'distilbert' for Hugging Face DistilBert model
  
          train_data (tuple): a tuple of numpy.ndarrays: (x_train, y_train)
          preproc: a ktrain.text.TextPreprocessor instance.
                   As of v0.8.0, this is required.
          metrics(list): metrics to use
          verbose (boolean): verbosity of output
      Return:
          model (Model): A Keras Model instance
      ```
      """
      if name not in TEXT_REGRESSION_MODELS:
          raise ValueError(
              "invalid name for text classification: %s" % (name)
          )
      if preproc is not None and preproc.get_classes():
          raise ValueError(
              "preproc.get_classes() is supposed to be empty for text regression tasks"
          )
      return _text_model(
          name,
          train_data,
          preproc=preproc,
          multilabel=False,
          classification=False,
          metrics=metrics,
          verbose=verbose,
      )
  
file_path: ktrain/ktrain/text/models.py
imports: from ..None import utils
  from ..imports import *
  from .None import preprocessor
label_desc: Use image node_id 14 for calling a global function with example usage: text_regression_model(name, train_data, preproc, metrics, verbose) and returns: _text_model