input: Write a python function to generate a linear model using numpy and return its slope and intercept.
  assert generate_model([1, 2, 3, 4, 5, 1, 2, 4, 8, 16]) == (3.6, -4.8)
  assert generate_model([1, 2, 3, 4, 5, 2, 4, 6, 8, 10]) == (2.0, 0.0)
  assert generate_model([1, 2, 3, 4, 5, 5, 7, 9, 11, 13]) == (2.0, 3.0)
output: import numpy as np
  
  def generate_model(data):
      x = np.array(data[:len(data)//2])
      y = np.array(data[len(data)//2:])
      A = np.vstack([x, np.ones(len(x))]).T
      slope, intercept = np.linalg.lstsq(A, y, rcond=None)[0]
      return slope, intercept