code: def get_pretrained_bert_345m_uncased_model():
      model_name = "megatron-bert-345m-uncased"
      config = {
          "language_model": {"pretrained_model_name": model_name},
          "tokenizer": {},
      }
      omega_conf = OmegaConf.create(config)
      model = nemo_nlp.modules.get_lm_model(cfg=omega_conf)
      if torch.cuda.is_available():
          model = model.cuda()
      return model
  
file_path: NeMo/tests/collections/nlp/test_megatron.py
imports: import os
  import tempfile
  import onnx
  import pytest
  import torch
  from omegaconf import OmegaConf
  import nemo.collections.nlp
  from nemo.core.classes import typecheck
label_desc: Use image node_id 1 for calling a global function with example usage: get_pretrained_bert_345m_uncased_model() and returns: model