input: Write a python function to train a linear regression model using scikit-learn and return the model's intercept and coefficient.
  ```python
  from sklearn.linear_model import LinearRegression
  import numpy as np
  
  def train_linear_regression(X, y):
      model = LinearRegression()
      model.fit(X, y)
      return model.intercept_, model.coef_
  
  # Test cases
  assert train_linear_regression(np.array([[1000], [2000], [3000]]), np.array([20000, 40000, 60000])) == (0.0, np.array([20.0]))
  assert train_linear_regression(np.array([[1], [2], [3]]), np.array([2, 4, 6])) == (0.0, np.array([2.0]))
  assert train_linear_regression(np.array([[10], [20], [30]]), np.array([30, 60, 90])) == (0.0, np.array([3.0]))
output: def train_linear_regression(X, y):
      model = LinearRegression()
      model.fit(X, y)
      return model.intercept_, model.coef_