code: def get_model_names():
      # Populate local copy of models
      local_model_paths = glob.glob(
          os.path.join("models", "**", "*.nemo"), recursive=True
      )
      local_model_names = list(
          sorted([os.path.basename(path) for path in local_model_paths])
      )
  
      # Populate with pretrained nemo checkpoint list
      nemo_model_names = set()
      for (
          model_info
      ) in nemo_asr.models.ASRModel.list_available_models():
          for superclass in model_info.class_.mro():
              if (
                  "CTC" in superclass.__name__
                  or "RNNT" in superclass.__name__
              ):
                  if "align" in model_info.pretrained_model_name:
                      continue
  
                  nemo_model_names.add(model_info.pretrained_model_name)
      nemo_model_names = list(sorted(nemo_model_names))
      return nemo_model_names, local_model_names
  
file_path: NeMo/tools/asr_webapp/model_api.py
imports: import contextlib
  import glob
  import os
  import torch
  import nemo.collections.asr
  from nemo.utils import logging, model_utils
label_desc: Use image node_id 1 for calling a global function with example usage: get_model_names() and returns: nemo_model_names,  local_model_names