input: from typing import List
  
  def predict_class_labels(data: List[float]) -> int:
      """Given a list of data points with 4 features (Length, Width, Height, and Weight), 
      predict the class label using a pre-trained Decision Tree Classifier model.
      >>> predict_class_labels([5.1, 3.5, 1.4, 0.2])  # Example dataset values
      0
      >>> predict_class_labels([6.2, 3.4, 5.4, 2.3])  # Example dataset values
      1
      """
output:     from sklearn.tree import DecisionTreeClassifier
      model = DecisionTreeClassifier()
      # Pre-trained model with example data
      X_train = [[5.1, 3.5, 1.4, 0.2], [6.2, 3.4, 5.4, 2.3]]
      y_train = [0, 1]
      model.fit(X_train, y_train)
      return model.predict([data])[0]