October 29 from 10am - 11am PT
As small language models (SLMs) become a critical part of today’s AI toolkit, teams need reliable and scalable serving infrastructure to meet growing demands. The Predibase Inference Engine simplifies serving infrastructure, making it easier to move models into production faster.
In this webinar, you’ll learn how to speed up deployments, improve reliability, and reduce costs—all while avoiding the complexity of managing infrastructure.
You'll learn how to:
- 4x your SLM throughput with Turbo LoRA, FP8 and Speculative Decoding
- Effortlessly manage traffic surges with GPU autoscaling
- Ensure high availability SLAs with multi-region load balancing, automatic failover, and more
- Deploy into your VPC for enhanced security and flexibility
Join us to discover practical strategies for optimizing SLM serving infrastructure and streamlining your model deployments.
Featured Speakers:
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Travis Addair Co-Founder & CTO, Predibase |
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Noah Yoshida Staff Software Engineer, Predibase |
