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Large Language Models (LLMs)

Getting Started with Llama 3

Published by O'Reilly Media, Inc.

Beginner content levelBeginner

Querying your local files privately with Llama 3

Course outcomes

  • Develop a basic understanding of the Llama 3 architecture
  • Learn to download, install, and run Llama 3 models (7B, 13B and 70B models)
  • Understand the relevance of open source LLMs, benefits and risks
  • Understand how to develop simple text-based applications using Llama 3
  • Understand how to query personal documents privately using Llama 3
  • Learn the basics of fine-tuning Llama 3 LLMs

Join expert Lucas Soares to get a solid introduction to Llama 3, the cutting-edge open source large language model developed and released by Meta. You’ll set up, download, and install Llama 3 and learn to run inference with your personal LLM hosted on your local machine. You’ll get hands-on to build simple text-based applications using Llama 3-based LLMs, including an app to query your own PDF documents privately. By the end of this four-hour course, you’ll be equipped to query your own documents, set up a simple LLM assistant locally, and build private LLM-based applications with Llama 3.

What you’ll learn and how you can apply it

  • Query your own PDF documents using Llama 3
  • Set up a simple and free LLM assistant on a local machine
  • Build simple and private LLM-based applications with Llama 3 locally

This live event is for you because...

  • You’re an AI/software engineer or developer.
  • You’re a data scientist or machine learning engineer.
  • You’re interested in learning about large language models, specifically ChatGPT, and how to build applications.

Prerequisites

  • Familiarity with Python programming
  • Some knowledge of machine learning concepts
  • Basic understanding of natural language processing

Recommended preparation:

Recommended follow-up:

Schedule

The time frames are only estimates and may vary according to how the class is progressing.

Basics of large language models and their applications (85 minutes)

  • Presentation: Introduction to large language models and their applications; getting started with Llama 3 (open source LLMs and setup)
  • Hands-on exercise: Set up Llama 2 and run inference locally with Llama2-7B-chat
  • Q&A
  • Break

Prompt engineering for Llama 3-based applications (40 minutes)

  • Presentation: Prompt engineering guide (prompting basics, best practices for prompting); prompt engineering concepts (few-shot, zero-shot, and chain-of-thought prompting); adapting to less performing models
  • Hands-on exercises: Explore prompt engineering with Llama 3; explore prompt engineering for text summarization and question answering
  • Q&A
  • Break

Querying documents locally (70 minutes)

  • Presentation: Text summarization with Llama 3; building a private Q&A system for PDFs
  • Hands-on exercises: Build a simple text summarizer; build a Q&A for private docs
  • Q&A
  • Break

Querying local files privately (55 minutes)

  • Presentation: Introduction to fine-tuning approaches with Llama 3 models
  • Hands-on exercise: Explore fine-tuning options for Llama 3-7B-chat: explore LoRa
  • Q&A

Your Instructor

  • Lucas Soares

    Lucas Soares is an AI engineer who worked as a research assistant at the Champalimaud Neuroscience Institute where he finished his masters working on an application of generative adversarial networks to predict mouse behavior. He switched his focus to industry and worked as a machine learning engineer for K1 Digital and Biometrid, developing computer vision and NLP based applications and gaining experience working with Pytorch. More recently over the last 2 years he has developed expertise working with LLM models, developing applications for his current employer Otovo as well as developing courses for OReilly Media and periodically making technical content about AI for Medium and Youtube.

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