This LLM for beginners course offers a working knowledge of the capabilities and types of LLM and practical experience of fine-tuning GPT2 on specific datasets.

llm.tar.gz

gpt-2-demo

dataset-demo-1

jupy

gpt2-demo-2

dataset-demo-1-copy

In this course, you will acquire a working knowledge of the capabilities and types of LLMs, along with their importance and limitations in various applications. You will gain valuable hands-on experience by fine-tuning LLMs to specific datasets and evaluating their performance. 

You will start with an introduction to large language models, looking at components, capabilities, and their types. Next, you will be introduced to GPT-2 as an example of a large language model. Then, you will learn how to fine-tune a selected LLM to a specific dataset, starting from model selection, data preparation, model training, and performance evaluation. You will also compare the performance of two different LLMs. 

By the end of this course, you will have gained practical experience in fine-tuning LLMs to specific datasets, building a comprehensive skill set for effectively leveraging these generative AI models in diverse language-related applications.

Essentials of Large Language Models: A Beginner’s Journey

Learn the best practices for preparing data for model training.

Course Overview

Getting Started with LLMs

Fine-Tuning LLMs

Wrap Up

Data Preparation

Best practices for data preparation

Dataset quality