code: def _model(c: Configs):
      """
      Create classification model
      """
      m = TransformerMLM(
          encoder=c.transformer.encoder,
          src_embed=c.transformer.src_embed,
          generator=c.transformer.generator,
      ).to(c.device)
  
      return m
  
imports: from typing import List
  import torch
  from torch import nn
  from labml import experiment, tracker, logger
  from labml.configs import option
  from labml.logger import Text
  from labml_helpers.metrics.accuracy import Accuracy
  from labml_helpers.module import Module
  from labml_helpers.train_valid import BatchIndex
  from labml_nn.experiments.nlp_autoregression import NLPAutoRegressionConfigs
  from labml_nn.transformers import Encoder, Generator
  from labml_nn.transformers import TransformerConfigs
  from labml_nn.transformers.mlm import MLM
label_desc: Use image node_id 3 for calling a global function with example usage: _model(c) and returns: m