code: def get_wavlm(device="cpu"):
      """Download the model and return the model object."""
  
      output_path = get_user_data_dir("tts")
  
      output_path = os.path.join(output_path, "wavlm")
      if not os.path.exists(output_path):
          os.makedirs(output_path)
  
      output_path = os.path.join(output_path, "WavLM-Large.pt")
      if not os.path.exists(output_path):
          print(f" > Downloading WavLM model to {output_path} ...")
          urllib.request.urlretrieve(model_uri, output_path)
  
      checkpoint = torch.load(
          output_path, map_location=torch.device(device)
      )
      cfg = WavLMConfig(checkpoint["cfg"])
      wavlm = WavLM(cfg).to(device)
      wavlm.load_state_dict(checkpoint["model"])
      wavlm.eval()
      return wavlm
  
imports: import os
  import urllib.request
  import torch
  from TTS.utils.generic_utils import get_user_data_dir
  from TTS.vc.modules.freevc.wavlm.wavlm import WavLM, WavLMConfig
label_desc: Use image node_id 1 for calling a global function with example usage: get_wavlm(device) and returns: wavlm