input: 
  def create_regression_model(input_dim: int, output_dim: int) -> LinearRegressionModel:
      """ Creates a LinearRegressionModel class for modeling a linear regression function.
      >>> model = create_regression_model(3, 1)
      >>> model.weights
      array([[0.],
             [0.],
             [0.]])
      >>> model.bias
      array([[0.]])
      >>> model.forward(np.array([[1, 2, 3]]))
      array([[0.]])
      """
      return LinearRegressionModel(input_dim, output_dim)
  
output:     
      class LinearRegressionModel:
          def __init__(self, input_dim: int, output_dim: int):
              self.weights = np.zeros((input_dim, output_dim))
              self.bias = np.zeros((1, output_dim))
  
          def forward(self, x: np.ndarray) -> np.ndarray:
              return np.dot(x, self.weights) + self.bias
  