Distillation and fine-tuning of SLMs to achieve great performance in specific tasks

How to compress large language models via distillation and fine‑tuning, with code, performance metrics, data format, and a call‑center case study.

Overview

This process compresses large-scale language models into efficient, task-optimized versions, enhancing performance and adaptability.

I will present a code, an example of performance and an example of the format of the training data

Tech stack