Abstract

This session focuses on practical techniques for using small open-source language models (SLMs) in enterprise settings. We first highlight the limitations of proprietary models in terms of privacy, compliance, and cost. Then, we explore modern workflows for adapting SLMs with domain-specific pre-training, instruction fine-tuning, and alignment. Along the way, we will introduce and demonstrate open-source tools like DistillKit, Spectrum, and MergeKit, which implement advanced techniques that are critical in achieving task-specific accuracy while optimizing computational costs. We'll also discuss some of the models and enterprise solutions built by Arcee AI. Join us to learn how small, efficient, and adaptable models can transform your AI applications.

Speaker

Julien Simon

Chief Evangelist @ Arcee AI

Julien Simon, the Chief Evangelist at Arcee.ai, is dedicated to helping enterprise clients develop top-notch and cost-efficient AI solutions using open-source small language models. With over 30 years of tech experience, including more than a decade in cloud computing and machine learning, Julien is committed to daily learning and is passionate about sharing his expertise through code demos, blogs, and YouTube videos. Before joining Arcee.ai, he was the Chief Evangelist at Hugging Face and the Global Technical Evangelist at Amazon Web Services. He also served as a CTO at prominent startups.