Welcome to an exciting journey into the world of open-source AI with reinforcement learning! This chapter is designed to help students understand reinforcement learning and its role in LLMs.
We will also explore Open R1, a groundbreaking community project that’s making advanced AI accessible to everyone. Specifically, this course is to help students and learners to use and contribute to Open R1.
In this chapter, we’ll break down complex concepts into easy-to-understand pieces and show you how you can be part of this exciting project. Whether you’re new to AI or have some experience, you’ll find something valuable here.
As a student, understanding Open R1 and the role of reinforcement learning in LLMs is valuable because:
This chapter is divided into four sections, each focusing on a different aspect of Open R1:
We’ll explore the basics of Reinforcement Learning (RL) and its role in training LLMs.
We’ll break down the research paper that inspired Open R1:
We’ll get practical with code examples:
We’ll look at a practical use case to align a model using Open R1.
To get the most out of this chapter, it’s helpful to have:
Don’t worry if you’re missing some of these – we’ll explain key concepts as we go along! 🚀
If you don’t have all the prerequisites, check out this course from units 1 to 11
Let’s begin our exploration of Open R1 and discover how you can be part of making AI more accessible to everyone! 🚀
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