input: Write a python function to fit a linear regression model using sklearn and return the slope and intercept.
  assert line_fit([1, 2, 3], [2, 3, 4]) == (1.0, 1.0)
  assert line_fit([1, 2, 3, 4], [3, 5, 7, 9]) == (2.0, 1.0)
  assert line_fit([0, 1, 2, 3], [1, 2, 3, 4]) == (1.0, 1.0)
output: def line_fit(x, y):
      from sklearn.linear_model import LinearRegression
      import numpy as np
  
      x = np.array(x).reshape(-1, 1)
      y = np.array(y)
      
      model = LinearRegression().fit(x, y)
      
      slope = model.coef_[1]
      intercept = model.intercept_
      
      return slope, intercept