code: def find_pretrained_model(src_lang: str, tgt_lang: str) -> List[str]:
      """Find models that can accept src_lang as input and return tgt_lang as output."""
      prefix = "Helsinki-NLP/opus-mt-"
      model_list = list_models()
      model_ids = [
          x.modelId
          for x in model_list
          if x.modelId.startswith("Helsinki-NLP")
      ]
      src_and_targ = [
          remove_prefix(m, prefix).lower().split("-")
          for m in model_ids
          if "+" not in m
      ]  # + cant be loaded.
      matching = [
          f"{prefix}{a}-{b}"
          for (a, b) in src_and_targ
          if src_lang in a and tgt_lang in b
      ]
      return matching
  
imports: import argparse
  import json
  import os
  import socket
  import time
  import warnings
  from pathlib import Path
  from typing import Dict, List, Union
  from zipfile import ZipFile
  import numpy
  import torch
  from torch import nn
  from tqdm import tqdm
  from huggingface_hub.hf_api import list_models
  from transformers import MarianConfig, MarianMTModel, MarianTokenizer
label_desc: Use image node_id 5 for calling a global function with example usage: find_pretrained_model(src_lang, tgt_lang) and returns: matching