Deploying Custom Model Serving Endpoints for LLMs on Databricks

The aim of this article is to guide readers through the process of leveraging Databricks Marketplace to deploy and utilize pre-trained Large Language Models (LLMs) effectively. By providing clear instructions and insights, we seek to simplify and expedite the setup process, ensuring a smoother journey for our readers.

Intro

Welcome to the cutting-edge landscape of AI innovation found within Databricks Marketplace! Here, we dive deep into the dynamic realm of Language Models (LLMs), spotlighting a range of chat and embeddings models including Llama2, Mistral, dbrx, BGE, and more.

Databricks Marketplace offers a gateway to a wealth of AI tools, promising limitless potential for data enthusiasts and developers alike. From speech recognition to text generation, these models stand poised to revolutionize our data interaction experience.

Let’s delve into the process of deploying these openly available models from Databricks Marketplace, creating endpoints, and seamlessly integrating them into various applications like Retrieval Augmented Generation.

A step-by-step guide:

Navigate to the Databricks Marketplace.