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Towards Understanding Large Language Models: Fine-Tuning
Data Science   Latest   Machine Learning

Towards Understanding Large Language Models: Fine-Tuning

Author(s): Mohamed Mamoun Berrada

Originally published on Towards AI.

Fine-Tuning LLMs to shape your own GenAI tools — Part of a Series

Large language models, or LLMs, are undoubtedly the stars of 2023. Since then, it has taken on an incredible pace. Chat GPT,, Bard, etc.—all these tools that are a few months old are powered by these models. They are becoming part of our day-to-day lives, and it is not pacing down. Today, the exciting path lies in your ability to create tools tailored to your needs.

Photo by Mojahid Mottakin on Unsplash

How, you might ask?

Well, one particular great thing about computer science and data science is the open source community—some amazing and selfless people that are developing and building great things for everyone to use. LLMs, as part of that, have their own community that is continuously developing and sharing open-source algorithms and models. To name a few recent examples: Phi2 from Microsoft or Mixtral 8x7b.

These open-source models allow you to build tools that meet your needs without starting from scratch.

The purpose of this article will be to explore and explain the technique enabling that, also known as fine-tuning.At the end of this article, you should be able to understand what this technique is, specifically what it means for LLMs, and how it unravels. Therefore, the answer to:

How can you… Read the full blog for free on Medium.

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Published via Towards AI

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