class_docstr: ```
  predicts text classes
  ```
class_docstr_tok: ["``","`","predicts","text","classes","``","`"]
code: def _save_model(self, fpath):
      if isinstance(self.preproc, TransformersPreprocessor):
          self.model.save_pretrained(fpath)
          # As of 0.26.3, make sure we save tokenizer in predictor folder
          tok = self.preproc.get_tokenizer()
          tok.save_pretrained(fpath)
      else:
          super()._save_model(fpath)
      return
  
file_path: ktrain/ktrain/text/predictor.py
imports: from ..None import utils
  from ..imports import *
  from ..predictor import Predictor
  from .preprocessor import TextPreprocessor, TransformersPreprocessor, detect_text_format
label_desc: Use image node_id 6 for calling the TextPredictor obj's underlying member method code with example usage: obj._save_model(fpath) without return types