code: def load_model(xtts_checkpoint, xtts_config, xtts_vocab):
      global XTTS_MODEL
      clear_gpu_cache()
      if not xtts_checkpoint or not xtts_config or not xtts_vocab:
          return "You need to run the previous steps or manually set the `XTTS checkpoint path`, `XTTS config path`, and `XTTS vocab path` fields !!"
      config = XttsConfig()
      config.load_json(xtts_config)
      XTTS_MODEL = Xtts.init_from_config(config)
      print("Loading XTTS model! ")
      XTTS_MODEL.load_checkpoint(
          config,
          checkpoint_path=xtts_checkpoint,
          vocab_path=xtts_vocab,
          use_deepspeed=False,
      )
      if torch.cuda.is_available():
          XTTS_MODEL.cuda()
  
      print("Model Loaded!")
      return "Model Loaded!"
  
imports: import argparse
  import os
  import sys
  import tempfile
  import gradio
  import librosa.display
  import numpy
  import os
  import torch
  import torchaudio
  import traceback
  from TTS.demos.xtts_ft_demo.utils.formatter import format_audio_list
  from TTS.demos.xtts_ft_demo.utils.gpt_train import train_gpt
  from TTS.tts.configs.xtts_config import XttsConfig
  from TTS.tts.models.xtts import Xtts
  import logging
label_desc: Use image node_id 2 for calling a global function with example usage: load_model(xtts_checkpoint, xtts_config, xtts_vocab) and returns: str, str