The first line of code creates an instance of TheModelClass given the provided arguments.
The parameters of this model will be randomly initialized as was either defined by yourself in the model implementation or just using the default reset_parameter method of the used layers.
Since you’ve stored the state_dict after training (which is the recommended way of serializing the model!), you can now load the trained parameters from the state_dict into your model instance via the_model.load_state_dict(torch.load(path_to_state_dict)).