input: Write a function to create a Python class named LinearRegressionModel that models a linear regression function. The class should include an initializer to set up the weights and bias of the model and a forward method to perform the forward pass of the linear regression model. The forward method should take input data x and return the output of the linear regression model.
  
  <Input>
  
  import numpy as np
  
  
  <Output>
  assert LinearRegressionModel(2, 1)
  assert LinearRegressionModel(3, 2)
  x = np.array([[1, 2], [3, 4]])
  model = LinearRegressionModel(2, 1)
  assert np.array_equal(model.forward(x), np.array([[0], [0]]))
output: class LinearRegressionModel:
      def __init__(self, weights, bias):
          self.weights = weights
          self.bias = bias
  
      def forward(self, x):
          return np.dot(x, self.weights) + self.bias