Fine-tuning Open Source LLMs with Mistral

While cutting-edge large language models can write almost any text you like, they are expensive to run. You can get the same performance for less money by using a smaller model and fine-tuning it to your needs.

In this session, Andrea, a Computing Engineer at CERN, and Josep, a Data Scientist at the Catalan Tourist Board, will walk you through the steps needed to customize the open-source Mistral LLM. You'll learn about choosing a suitable LLM, getting training data, tokenization, evaluating model performance, and best practices for fine-tuning.

Key Takeaways: