amazon-bedrock-with-builder-and-command-patterns VS CodeGen

The second service is what’s going to make our application come alive and give it the AI functionality we need and that service is AWS Bedrock which is their new generative AI service launched in 2023. AWS Bedrock offers multiple models that you can choose from depending on the task you’d like to carry out but for us, we’re going to be making use of Meta’s Llama V2 model, more specifically meta.llama2-70b-chat-v1.

Amazon Bedrock

Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon. Each model is accessible through a common API which implements a broad set of features to help build generative AI applications with security, privacy, and responsible AI in mind.

For those keeping track, Amazon Bedrock became generally available in September of 2023. My team had access to a preview, so when the AWS Comprehend entity analysis did not lend itself well to my use case; and I didn't feel like training a model, I started to get familiar with Bedrock. The following post is a follow-on to the Community article above and fleshes out a few details that will help those newer to Amazon Bedrock navigate the product.

In this blog you will learn how to use Amazon Cognito credentials and IAM Roles to invoke Amazon Bedrock API in a react-based application with JavaScript and the CloudScape design system. You will deploy all the resources and host the app using AWS Amplify.

Working with the AWS Bedrock API is an exhilarating experience! I came across an interesting business case where I needed to develop an AI MVP. The MVP generates JSON data based on a prompt and utilizes the anthropic.claude-v2:1 model in AWS Bedrock.

CodeGen (I included this model as there's some evidence in recent months that LLMs trained on code-related tasks better capture long-range dependencies compared to LLMs trained on 'just words')

https://github.com/salesforce/CodeGen these are used in fauxpilot https://github.com/fauxpilot/fauxpilot

You can always use https://github.com/salesforce/CodeGen . But it does require managing the model hosting. You can use fauxpilot to mimic copilot functionality https://github.com/fauxpilot/fauxpilot

freediver 2 days ago | prev | next [–] Here is an example of one general purpose open source LLM, probably the best you can get: https://github.com/EleutherAI/gpt-neox To manage your expectations it is nowhere as good as ChatGPT. If you are interested in programming only: https://github.com/salesforce/CodeGen

Replit built Ghostwriter on the open source scene based on Salesforce’s Codegen, using Nvidia’s FasterTransformer and Triton server for highly optimized decoders, and the knowledge distillation process of the CodeGen model from two billion parameters to a faster model of one billion parameters.

https://github.com/moyix/fauxpilot is working on an open source variant. Based on https://github.com/salesforce/CodeGen