Winning Big With Small AI

course_overview

count_chapters
begin_reading
download
p_implied_book_part_name

Winning Big With Small AI13 chapters

Begin
  1. Preface

  2. Part I - Advantages of Small AI With Examples

  3. Advantages of Small Models with Examples That Might Surprise You

  4. Drawbacks of Small AI

  5. Part II - Defining Metrics for Success Using LLMs

  6. Defining Metrics for Success Using LLMs

  7. A Fair Shootout: Evaluating Large vs. Small Models for Task Fitness

  8. Part III - Python Examples for Switching Between Models

  9. Using the LiteLLM Library to Easily Switch Between Models and Model Providers

  10. Automatically Routing to the ‘Best’ Model Using RouteLLM Library

  11. \# Part IV - Fast and Efficient Rag Document System

  12. RAG Using zvec Vector Datastore and Gemini-3-flash Model

  13. Wrap Up for Winning Big With Small AI