Do not use torch.save() on your the class object. Either save the state_dict or use the a traced version of the model.
Saving the model with JIT:
traced_model = torch.jit.trace(model, torch.randn(1, 16, 50, 100))
torch.jit.save(traced_model, output_path)

Loading the model in  the server code:
model = torch.jit.load(model_path, map_location='cpu')

The rest should be the same.
Just a tip on your code style: do not start class names with lowercase, it’s not pythonic