You could either load the state_dict into the model before applying any manipulations, change the state_dict keys to map your new modules names, or load the parameters layer-wise, which would most likely also need a mapping between the currently modified model and the pretrained state_dict.
I don’t know how you are manipulating the model, but I think the first approach might be the easiest one.
E.g. you could write a custom nn.Module, use the pretrained model inside it, add the new layer(s), and change the forward method as needed.