Thank you for time and response. You have shown the weights of the fc layer of the quantized model. And here is my question. The weights are float value. Why is it so? Should not be it in the range of  0 to 255? I think I misunderstood something. Please clarify.
If I run this :print(model_fp32.fc.weight)
Parameter containing:
tensor([[ 0.1790, -0.3491, -0.1060,  0.0618],
[ 0.4251, -0.0054, -0.4578,  0.0406],
[-0.2153, -0.1724, -0.1873, -0.2386],
[-0.3372, -0.2659, -0.4900, -0.2144]], requires_grad=True)
If I run this: print(model_int8.fc.weight())
tensor([[ 0.1806, -0.3497, -0.1076,  0.0615],
[ 0.4266, -0.0038, -0.4573,  0.0423],
[-0.2152, -0.1729, -0.1883, -0.2383],
[-0.3382, -0.2652, -0.4919, -0.2152]], size=(4, 4), dtype=torch.qint8,
quantization_scheme=torch.per_tensor_affine, scale=0.0038432059809565544,
zero_point=0)
For both fp32 and int8 model. the weights are almost similar. And both the weights are floating point numbers.