Large Language Models, Quantization, Machine Learning, Data Science, Hands On Tutorials.
stage, resulting in enhanced model performance. However, QAT is computationally expensive and demands representative training data. In this article, we focus on PTQ to reduce the precision of our parameters. To get a good intuition, we will apply both naïve and more sophisticated techniques to a