According to their docs[1], three different ways of quantizing your model are supported - one of which is quantization-aware training (3).
[1] - https://pytorch.org/docs/master/quantization.html#quantizati...
https://arxiv.org/abs/1906.04721 is an example paper where they perform data-free quantization after training (using batchnorm parameters to get information about the data distribution) without large performance drops.
However I'm a bit skeptical about doing quantization after training, in my experience you have to do quantization-aware training for there not be a large performance decrease. I guess it works though otherwise they wouldn't have released it?