input: 
  def create_linear_regression_model(input_dim: int, output_dim: int) -> LinearRegressionModel:
      """Create and return an instance of a LinearRegressionModel with the given input and output dimensions.
      >>> model = create_linear_regression_model(2, 1)
      >>> model.weights
      array([[0.],
             [0.]])
      >>> model.bias
      array([[0.]])
      >>> input_data = np.array([[1, 2], [3, 4]])
      >>> model.forward(input_data)
      array([[0.],
             [0.]])
      """
      return LinearRegressionModel(input_dim, output_dim)
  
output:     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, input_data):
              return np.dot(input_data, self.weights) + self.bias