Deploying GPT & Large Language Models

This repository contains code for the O'Reilly Live Online Training for Deploying GPT & LLMs

In this training, you learn how to use GPT-4, ChatGPT, OpenAI embeddings, and other large language models to build applications for both experimenting and production. We cover the fundamentals of GPT and its applications and explore alternative generative models such as Cohere and GPT-J. You gain practical experience in building a variety of applications with these models, including text generation, summarization, question answering, and more. Learn how to leverage prompt engineering, context stuffing, and few-shot learning to get the most out of GPT-like models. Then the focus shifts to deploying these models in production, including best practices and debugging techniques. By the end of the training, you have a working knowledge of GPT and other large language models, as well as the skills to start building your own applications with them.

Notebooks

Finetuning with OpenAI

Training BERT for Classification

More Classification with BERT

Introduction to Prompt Engineering

Advanced to Prompt Engineering

Semantic Search

Extra

RAG Bot

LLM Distillation

LLM Quantization

Instructor

Sinan Ozdemir is the Founder and CTO of LoopGenius where he uses State of the art AI to help people create and run their businesses. Sinan is a former lecturer of Data Science at Johns Hopkins University and the author of multiple textbooks on data science and machine learning. Additionally, he is the founder of the recently acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a master’s degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco, CA.