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Fine-tuning Open Source LLMs with Mistral

Key Takeaways:
  • Learn how to fine-tune a large language model using the Hugging Face Python ecosystem.
  • Learn about the steps to prepare for fine-tuning and how to evaluate your success.
  • Learn about best practices for fine-tuning models.
Tuesday, July 16 11AM ET
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Description

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.

To code along live with us, make sure you have accounts for both Lightning AI and Hugging Face.

Presenter Bio

Andrea Valenzuela Headshot
Andrea ValenzuelaComputing Engineer at CERN

Andrea Valenzuela is currently working on the CMS experiment at the particle accelerator (CERN) in Geneva, Switzerland. With expertise in data engineering and analysis for the past six years, her duties include data analysis and software development. She is now working towards democratizing the learning of data-related technologies through the Medium publication ForCode'Sake.

She holds a BS in Engineering Physics from the Polytechnic University of Catalonia, as well as an MS in Intelligent Interactive Systems from Pompeu Fabra University. Her research experience includes professional work with previous OpenAI algorithms for image generation, such as Normalizing Flows.

Josep Ferrer Headshot
Josep FerrerData Scientist and Project Manager at Catalan Tourism Board

Josep is a Data Scientist and Project Manager at the Catalan Tourist Board, using data to improve the experience of tourists in Catalonia. His expertise includes the management of data storage and processing, coupled with advanced analytics and the effective communication of data insights.

He is also a dedicated educator, teaching the Big Data Master's program at the University of Navarra, and regularly contributing insightful articles on data science to Medium and KDNuggets.

He holds a BS in Engineering Physics from the Polytechnic University of Catalonia as well as an MS in Intelligent Interactive Systems from Pompeu Fabra University.

Currently, he is passionately committed to making data-related technologies more accessible to a wider audience through the Medium publication ForCode'Sake.

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