input: from typing import List, Union
  
  def predict(data: List[float]) -> Union[int, str]:
      """
      Given a set of data with 4 features: Length, Width, Height, and Weight, predict the class label using a pre-trained Decision Tree Classifier model.
      
      Example usage:
      >>> predict([1.2, 2.3, 3.4, 4.5])
      0
      """
      # Load the dataset
      import pandas as pd
      csv_url = 'http://test.test/test.csv'
      df = pd.read_csv(csv_url)
  
      # Split the dataset into features and label
      X = df.iloc[:, 0:4].values
      y = df.iloc[:, 4].values
  
      # Import the ML model
      from sklearn.tree import DecisionTreeClassifier
  
      # Create and fit the model
      model = DecisionTreeClassifier()
      model.fit(X, y)
  
      # Predict the label
      predicted_label = model.predict([data])
      return predicted_label[0]
output:     # Return the predicted label as an integer or string
      if predicted_label[0] == 0:
          return "Low"
      elif predicted_label[0] == 1:
          return "Medium"
      else:
          return "High"