this works, can you give a repro?
model = nn.Sequential(torch.quantization.QuantStub(), torch.nn.Conv2d(2,2,2))
model.qconfig = torch.quantization.get_default_qconfig()
modelp = torch.quantization.prepare(model)
modelp(torch.randn(1,2,32,32))
modelq = torch.quantization.convert(modelp)
modelj = torch.jit.script(modelq)
print(modelq[1].scale)
print(modelj[1].scale)

also it looks like QFunctionals should still work in the same way (pytorch/functional_modules.py at 22ec6250283568fc475d030dc0b15eda5d13b00b · pytorch/pytorch · GitHub 1)
so you should be able to inspect them directly.