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June 19-20, 2024
Paris, France
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Wednesday, June 19 • 11:20 - 11:50
Applying Open Source Methods to Building and Training Large Language Models - Carol Chen, Red Hat & Mark Sturdevant, IBM

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Several open models of varying size, quality, and performance have been released over the past twelve months. We are working on a project that allows contribution of skills to an existing model without the need to fully fork and fine-tune. This project will create the establishment of an upstream community built on contributing acceptance workflows for models. This exciting technology aims to make open source AI more approachable. In this session we'll explain how communities and individuals can contribute domain knowledge to models incrementally, in a unified and open way, while reducing model variations and resulting in an improved version by augmenting what’s already there.
Speakers
avatar for Carol Chen

Carol Chen

Principal Community Architect, Red Hat
Carol Chen is a Community Architect at Red Hat, supporting several upstream communities such as Ansible and ManageIQ. She has been actively involved in open source communities while working for Jolla and Nokia previously. In addition, she also has experiences in software development/integration... Read More →
avatar for Mark Sturdevant

Mark Sturdevant

Software Developer, IBM
Mark Sturdevant is an open source software engineer and advocate at IBM. He has worked on a variety of open source projects and created many open source code patterns and tutorials to help developers get started with artificial intelligence, data science, and databases.

Wednesday June 19, 2024 11:20 - 11:50 CEST
Sorbonne Descartes & Lutèce (Level 5)
  AI Research & Methodologies
  • Audience Experience Level Any
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