The field of large language models has exploded, and Llama is a standout. With Llama 3, possibilities have soared. Explore its capabilities, learn to use it with llama-cpp-python, and understand how to control the model's behavior by adjusting parameters and assigning specific roles to guide the conversation.

What is Llama?

Chatting with Llama 3

Extracting the response

Tuning Llama 3 parameters

Guiding customer support responses

Ensuring safe responses

Generating creative copy

Assigning chat roles

Building a conversation

System messages

Understanding LLMs and Llama

Language models can do more than just generate text - they can be guided to produce structured and context-aware responses. In this chapter, you'll explore how to leverage llama-cpp-python to generate outputs in specific formats, including JSON-compatible responses for data integration. You'll also refine Llama's output using prompting techniques to align responses with different tasks. Finally, you'll build conversations that maintain context across multiple exchanges, ensuring more natural interactions. 

Guiding unstructured responses

Formatting prompts for Llama

Few-shot prompting with Llama

Generating structured output

Creating a JSON inventory list

Specifying structured JSON schema

Building conversations

Creating a conversational class

Single-turn conversation

Multi-turn conversations

Congratulations!

Using Llama Locally

Open-source large language models like Llama can run on your own computer, helping you keep data private and reduce costs. In this course, you'll learn how to set up and use Llama locally. You'll explore simple techniques like adjusting prompts to get better responses, building conversations that remember context, and adapting outputs to fit your project's needs - whether that means generating structured data or refining responses for clarity. This course is designed for learners with experience working with Python.

<h2>Learn to use the Llama Large-Language Model (LLM)</h2>  
What is the Llama LLM, and how can you use it to enhance your projects? This course will teach you how to run Llama locally, guide its responses using prompt engineering, and build structured and context-aware conversations. <br>  
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<h2>Understand the Llama model and its applications</h2>  
You'll start with an introduction to the foundational concepts of Llama, learning how to interact with Llama models and exploring their use cases. You'll gain hands-on experience setting up, running, and interacting with the model using the llama-cpp-python library. As you progress, you'll apply techniques to refine Llama’s responses, maintain conversation history, and generate structured outputs ready to be integrated into automated workflows.<br>  
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This is an ideal introduction to Llama for developers and AI practitioners. It explores the foundations of this powerful open-source LLM and how to apply it in real-world scenarios.  

Python Toolbox

Explore the latest techniques for running the Llama LLM locally and integrating it within your stack.

Working with Llama 3

Ingénieur IA associé pour les scientifiques de données

Développer des LLM

Les fondamentaux du lama

Extracting the response

Working with Llama 3

Instructions

Exercice interactif pratique