input: from typing import List
  
  def distinguish_animals(images: List[np.ndarray]) -> List[str]:
      """ Collate a machine learning model in Python that distinguishes between cats and dogs.
      Each image in the input list should be of size (64, 64, 3) and already preprocessed.
      The function will return a list of labels ('cat' or 'dog') corresponding to each image.
  
      >>> distinguish_animals([np.zeros((64, 64, 3)), np.ones((64, 64, 3))])
      ['cat', 'dog']
      """
output:     from tensorflow.keras.models import load_model
      import numpy as np
  
      # Load the pre-trained model
      model = load_model('cat_dog_model.h5')
  
      # Predict the labels for each image
      predictions = model.predict(np.array(images))
  
      # Convert predictions to labels ('cat' or 'dog')
      labels = ['cat' if pred < 0.5 else 'dog' for pred in predictions]
  
      return labels