I got it working! With the following code:
with torch.no_grad():
    setattr(net, 'fc1', nn.Linear(784, 15))
    setattr(net, 'fc2', nn.Linear(15, 10))
    for i, p in enumerate(net.parameters()):
        p.copy_(new_params[i])

The next question is, how can I target the hyper-parameters of the layers in a loop?
for name, module in net.named_modules():
     print(name) ->>> fc1 
     print(type(module)) ->>> Linear
     print(???(module)) ->>> (784, 15)

**Edit: I found how to get the type() from the module.py file.