hi, i save the quantization model with
torch.save(model.state_dict(),"quanted_model.pkl"

and load it with
model.fuse_model()
model.encoder.qconfig = torch.quantization.get_default_qconfig('fbgemm')
torch.quantization.prepare(model.encoder, inplace=True)
torch.quantization.convert(model.encoder, inplace=True)
model.load_state_dict(torch.load(modelfile,map_location='cpu'))


the quantization step is same.
when i pass the calibrate step, i can get the same output from the load model, however , after i do the calibrate, the output is different betwen the reloaded model and the quantization model.
I compare the state_dict() and the metadata, but, they are same.
my model is transformer.