input: Write a function to create a Python class that models a linear regression function using a neural network approach. The class should include an initializer method to set up the weights and bias, and a forward method to calculate the output of the linear regression model.
  assert LinearRegressionModel(2, 1)
  x = np.array([[1, 2], [3, 4]])
  assert np.allclose(LinearRegressionModel(2, 1).forward(x), np.array([[0.0], [0.0]]))
output: class LinearRegressionModel:
      def __init__(self, input_size, output_size):
          self.weights = np.zeros((input_size, output_size))
          self.bias = np.zeros(output_size)
  
      def forward(self, x):
          return np.dot(x, self.weights) + self.bias