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Fine-Tuning LLMs: Use Case Examples
Latest   Machine Learning

Fine-Tuning LLMs: Use Case Examples

Last Updated on February 24, 2024 by Editorial Team

Author(s): Leo Tisljaric, PhD

Originally published on Towards AI.

From LLM-based machine translations to text generation fine-tuning, find all the theory, examples, and code in one place.
Working on AI (Image by: Author)

In one of his recent interviews, famous AI scientist Yann LeCun said that we do not have to seek general intelligence because even humans do not have it as β€žmachinesβ€œ that have very specific and limited knowledge and skills. I totally agree with that statement, and this article will show you how to apply this paradigm to LLMs by fine-tuning and specializing them to do only one task. The main finetuning goal is to adapt the base LLM, which is not great in generating even simple statements, to generate a meaningful text according to the finetuning objective that can be question answering, summarization, chat, translation, or similar.

Before we continue, give me a second of your time. If you want to support my work, you can do it through a secure PayPal link :

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You can use this article as a knowledge base with finetuning examples which you use in your daily work, or as a learning material that will help you to grasp the quite complicated finetuning process.

Article’s content:

About FinetuningHow to finetune?Use cases (translation, text classification, text generation)CodeConclusion

If… Read the full blog for free on Medium.

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