class_docstr: Back Translation with hugging-face translation models.
  A sentence can only be transformed into one sentence at most.
class_docstr_tok: ["Back","Translation","with","hugging-face","translation","models",".","A","sentence","can","only","be","transformed","into","one","sentence","at","most","."]
code: def get_model(self):
      # accelerate load efficiency
      from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
  
      generation = AutoModelForSeq2SeqLM
      tokenizer = AutoTokenizer
  
      """ Load models of translation. """
      self.from_tokenizer = tokenizer.from_pretrained(
          self.from_model_name
      )
      self.from_model = generation.from_pretrained(self.from_model_name)
      self.to_tokenizer = tokenizer.from_pretrained(self.to_model_name)
      self.to_model = generation.from_pretrained(self.to_model_name)
      self.from_model.to(self.device)
      self.to_model.to(self.device)
  
file_path: textflint/textflint/generation/transformation/UTCN/cn_back_trans.py
imports: import torch
  from ..transformation import Transformation
  from ....common import device
  from ....common.settings import CN_TRANS_FROM_MODEL, CN_TRANS_TO_MODEL
label_desc: Use image node_id 4 for calling the BackTrans obj's underlying member method code with example usage: obj.get_model() without return types