code: def get_model(self, mname):
      model = FSMTForConditionalGeneration.from_pretrained(mname).to(
          torch_device
      )
      if torch_device == "cuda":
          model.half()
      return model
  
file_path: transformers/examples/legacy/seq2seq/old_test_fsmt_bleu_score.py
imports: import io
  import json
  import unittest
  from parameterized import parameterized
  from transformers import FSMTForConditionalGeneration, FSMTTokenizer
  from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
  from utils import calculate_bleu
label_desc: Use image node_id 2 for calling the ModelEvalTester obj's underlying member method code with example usage: obj.get_model(mname) and returns: model