Hello 
The best practice in pytorch is to save a model state_dict. Consider this minimal example.
import torch
import torch.nn as nn
m = nn.Linear(10, 2)
state = m.state_dict()
torch.save(state, 'm.pt')

m1 = nn.Linear(10, 2)
m2 = nn.Linear(10, 2)
for p1, p2 in zip(m1.parameters(), m2.parameters()):
    print(torch.all(p1 == p2))

prints:
tensor(False)
tensor(False)

and
state = torch.load('m.pt')
m1.load_state_dict(state)
m2.load_state_dict(state)
for p1, p2 in zip(m1.parameters(), m2.parameters()):
    print(torch.all(p1 == p2))

prints:
tensor(True)
tensor(True)