input: Write a python function to implement a simple linear regression model using the provided class, and test it with some sample data.
  assert np.allclose(LinearRegressionModel(2, 1).forward(np.array([[1, 2], [3, 4]])), np.array([[0], [0]]))
  assert np.allclose(LinearRegressionModel(3, 1).forward(np.array([[1, 2, 3], [4, 5, 6]])), np.array([[0], [0]]))
  assert np.allclose(LinearRegressionModel(2, 2).forward(np.array([[1, 2], [3, 4]])), np.array([[0, 0], [0, 0]]))
output: import numpy as np
  
  class LinearRegressionModel:
      def __init__(self, input_dim, output_dim):
          self.weights = np.zeros((input_dim, output_dim))
          self.bias = np.zeros((1, output_dim))
      
      def forward(self, x):
          return np.dot(x, self.weights) + self.bias