HandsOnLLM/Hands-On-Large-Language-Models

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

57
/ 100
Established

This project provides practical code examples for understanding and working with Large Language Models (LLMs). It helps data scientists, machine learning engineers, and researchers explore how LLMs function and apply them to various text-based tasks. Users input text data and receive classified text, clustered topics, generated content, or search results powered by LLMs.

23,351 stars.

Use this if you are a machine learning practitioner looking for hands-on code examples and explanations to grasp the core concepts and applications of Large Language Models, particularly when following the O'Reilly book 'Hands-On Large Language Models'.

Not ideal if you are a business user looking for a no-code solution or a complete application to solve a specific business problem without needing to understand the underlying machine learning implementation.

natural-language-processing text-analytics machine-learning-engineering data-science prompt-engineering
No Package No Dependents
Maintenance 6 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 25 / 25

How are scores calculated?

Stars

23,351

Forks

5,423

Language

Jupyter Notebook

License

Apache-2.0

Last pushed

Dec 17, 2025

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/transformers/HandsOnLLM/Hands-On-Large-Language-Models"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.