Hi Mohit,
Are you interested in quantizing CV models? Are you targeting mobile devices?
If so, you can follow the tutorial here: https://pytorch.org/tutorials/advanced/static_quantization_tutorial.html 72
In general, you can start with post training quantization (the available options depend on whether it is server or mobile). You can get the recommended qconfig to use for post training quantization by calling:
# Gets the recommended qconfig for post training quantization
model.qconfig = torch.quantization.get_default_qconfig('fbgemm') #'fbgemm' for server and 'qnnpack' for mobile
#Also, remember to set your backend engine to match what you use here:
torch.backends.quantization.engine = 'fbgemm' 

If the accuracy is not good enough, you will have to do quantization aware training, which is more involved. You can see reference code at: https://github.com/pytorch/vision/blob/master/references/classification/train_quantization.py 27