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In-person
19-22 March
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Wednesday, March 20 • 14:30 - 15:05
Self-Hosted LLMs on Kubernetes: A Practical Guide - Hema Veeradhi & Aakanksha Duggal, Red Hat

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Have you ever considered deploying your own large language model (LLM), but the seemingly complex process held you back from exploring this possibility? The complexities of deploying and managing LLMs in production environments often pose significant challenges. This talk will serve as a comprehensive introductory guide, empowering beginners to commence their LLM journey by effectively hosting their own models on Kubernetes. We will discuss the process of selecting appropriate open source LLM models, containerization of the models, and creating Kubernetes deployment manifests and resource provisioning to support the LLM's computational needs. Self-hosted LLMs offer enhanced data privacy, flexibility in model training, and reduced operational costs, making them an attractive option for organizations seeking greater control over their AI infrastructure. By the end of this talk, attendees will possess the necessary skills and knowledge to navigate the exciting path of self-hosting LLMs.

Speakers
avatar for Hema Veeradhi

Hema Veeradhi

Senior Data Scientist, Red Hat
Hema Veeradhi is a Senior Data Scientist working in the Emerging Technologies team part of the office of the CTO at Red Hat. Her work primarily focuses on implementing innovative open AI and machine learning solutions to help solve business and engineering problems. Hema is a staunch... Read More →
avatar for Aakanksha Duggal

Aakanksha Duggal

Senior Data Scientist, Red Hat Inc
Aakanksha Duggal is a Senior Data Scientist in the Emerging Technologies Group at Red Hat. She is a part of the Data Science team and works on developing open source software that uses AI and machine learning applications to solve engineering problems.



Wednesday March 20, 2024 14:30 - 15:05 CET
Pavilion 7 | Level 7.1 | Room C
  ML/AI + Data Processing + Storage
  • Content Experience Level Beginner
  • Presentation Slides Attached Yes