input: from typing import List
  
  
  def predict_labels(features: List[List[float]]) -> List[str]:
      """ Predict the class labels for a given set of data using a pre-trained DecisionTreeClassifier.
      The dataset has 4 features: Length, Width, Height, and Weight.
      >>> predict_labels([[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0]])
      ['Label1', 'Label2']
      """
output:     from sklearn.tree import DecisionTreeClassifier
      import joblib
  
      # Load the pre-trained model
      model = joblib.load('decision_tree_model.pkl')
  
      # Predict the labels
      labels = model.predict(features)
  
      # Convert numerical labels to string labels
      label_map = {0: 'Label1', 1: 'Label2'}
      predicted_labels = [label_map[label] for label in labels]
  
      return predicted_labels