Finetuning Large Language Models

Overview

Class Central Tips

In this short course, you’ll learn essential finetuning concepts and how to train a large language model using your own data. You’ll be equipped to incorporate the latest techniques to optimize your model and produce transformative results. When you complete this course, you will be able to: Understand when to apply finetuning on LLMs Prepare your data for finetuning Train and evaluate an LLM on your data With finetuning, you’re able to take your own data to train the model on it, and update the weights of the neural nets in the LLM, changing the model compared to other methods like prompt engineering and Retrieval Augmented Generation. Finetuning allows the model to learn style, form, and can update the model with new knowledge to improve results.

Syllabus

Project Overview

Join our new short course, Finetuning Large Language Models! Learn from Sharon Zhou, Co-Founder and CEO of Lamini, and instructor for the GANs Specialization and How Diffusion Models Work. When you complete this course, you will be able to:(1) Understand when to apply finetuning on LLMs.(2) Prepare your data for finetuning.(3) Train and evaluate an LLM on your data.With finetuning, you’re able to take your own data to train the model on it, and update the weights of the neural nets in the LLM, changing the model compared to other methods like prompt engineering and Retrieval Augmented Generation. Finetuning allows the model to learn style, form, and can update the model with new knowledge to improve results.