Deploy Cohere Rerank #Multilingual From #AWS Marketplace Onto SageMaker (with Demo) — #generativeai

Discover how to deploy Cohere's Rerank 3 model on Amazon SageMaker in this step-by-step guide. Learn about the model's key features, including its ability to enhance enterprise search and RAG systems, reduce costs, and support multiple languages. Follow along as we navigate the AWS Marketplace, subscribe to the model, and use Python to set up and deploy a SageMaker endpoint. See the model in action with a multilingual example, and understand why Rerank models are crucial in modern AI stacks. Perfect for developers and data scientists looking to optimize their search and retrieval systems on AWS. Notebook link: https://github.com/ystoneman/cohere-examples/blob/main/sagemaker/deploy-rerank-sagemaker-demo.ipynb 00:00 Introduction to Cohere's Rerank 3 00:12 Top 6 reasons to be excited about Rerank 3 01:02 Subscribing to the model on AWS Marketplace 01:45 Setting up the development environment 02:01 Configuring AWS credentials and IAM roles 02:17 Finding the model ARN in AWS Marketplace 02:55 Choosing the right SageMaker instance type 03:31 Creating the SageMaker model and endpoint configuration 03:56 Deploying the SageMaker endpoint 04:10 Running an inference example 04:54 SageMaker Jumpstart? 05:07 Why use a Rerank model when you have embeddings? Disclaimer: Although I work for Cohere as a Staff Solutions Architect and previously at AWS, this content is just my own effort to learn by sharing.