code: def init_whisper(model_name="tiny.en", batch_size=1):
      assert MODEL_URLS[model_name] is not None
  
      filename = fetch(MODEL_URLS[model_name])
      state = torch_load(filename)
      model = Whisper(state["dims"], batch_size)
      load_state_dict(model, state["model_state_dict"], strict=False)
      enc = get_encoding(
          "multilingual" if model.is_multilingual else "gpt2"
      )
      return model, enc
  
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 3 for calling a global function with example usage: init_whisper(model_name, batch_size) and returns: model,  enc