Hello. Thanks for the reply. I think the easiest way is to try the PyTorch post-quantization tutorial ((beta) Static Quantization with Eager Mode in PyTorch — PyTorch Tutorials 1.7.1 documentation 1) where I can reproduce the most extreme case of this behaviour (list(myModel.named_parameters()) == []), ‘myModel’ being the quantized version of the full precision model. I try listing the parameters right after ‘torch.quantization.convert(myModel, inplace=True)’.