Cool question, I’ve tried,
I think, here’s you can solve this,
We can get weights of any model by  model.parameters() which can be append into list as below
params1 = []
for param in model1.parameters():
  params1.append(param.data)

similary do this to trained model2 and save in list params2
Now you initialize weights of model3 as
model3 = Network()
params3 = iter(params1 + params2)
for param in model3.parameters():
  param.data = next(params3)