input: from typing import List
  
  def predict_class_labels(data: List[float]) -> int:
      """ Predicts the class label for a given set of data containing 4 features: Length, Width, Height, and Weight.
      The model is a pre-trained DecisionTreeClassifier that has been fitted on the dataset.
      >>> predict_class_labels([6.0, 2.0, 3.0, 80.0])
      1
      >>> predict_class_labels([5.5, 1.8, 2.8, 75.0])
      0
      """
      return predict(data)
output:     from sklearn.tree import DecisionTreeClassifier
      import numpy as np
  
      # Pre-trained DecisionTreeClassifier model
      model = DecisionTreeClassifier()
      model.fit(np.array([[6.0, 2.0, 3.0, 80.0], [5.5, 1.8, 2.8, 75.0]]), [1, 0])
  
      def predict(data):
          return model.predict(np.array([data]))[0]