class_docstr: predicts  classes for string-representation of sentence
class_docstr_tok: ["predicts","classes","for","string-representation","of","sentence"]
code: def __init__(self, model, preproc, batch_size=U.DEFAULT_BS):
      if not isinstance(model, keras.Model):
          raise ValueError("model must be of instance keras.Model")
      if not isinstance(preproc, NERPreprocessor):
          # if type(preproc).__name__ != 'NERPreprocessor':
          raise ValueError("preproc must be a NERPreprocessor object")
      self.model = model
      self.preproc = preproc
      self.c = self.preproc.get_classes()
      self.batch_size = batch_size
  
file_path: ktrain/ktrain/text/ner/predictor.py
imports: from ...None import utils
  from ...imports import *
  from ...predictor import Predictor
  from ..None import textutils
  from .preprocessor import NERPreprocessor
label_desc: Use image node_id 1 to create a new NERPredictor object from inherited base classes: Predictor with example: obj = NERPredictor(model, preproc, batch_size)