code: def transcribe_file(model, enc, filename):
      return transcribe_waveform(
          model, enc, [load_file_waveform(filename)]
      )
  
imports: import sys
  import pathlib
  import base64
  import multiprocessing
  import numpy
  from typing import Optional, Union, Literal, List
  from tinygrad.jit import TinyJit
  from tinygrad.nn.state import torch_load, load_state_dict
  from tinygrad.helpers import getenv, DEBUG, CI, fetch
  import tinygrad.nn
  from tinygrad.shape.symbolic import Variable
  from tinygrad.tensor import Tensor
  import itertools
  import librosa
label_desc: Use image node_id 5 for calling a global function with example usage: transcribe_file(model, enc, filename) and returns: transcribe_waveform