Predefined models

Disclaimer: Use of Third-Party Models

By using this sample, you agree that you may be deploying third-party models (“Third-Party Model”) into your specified user account. AWS does not own and does not exercise any control over these Third-Party Models. You should perform your own independent assessment, and take measures to ensure that you comply with your own specific quality control practices and standards, and the local rules, laws, regulations, licenses and terms of use that apply to you, your content, and the Third-Party Models, and any outputs from the Third-Party Models. AWS does not make any representations or warranties regarding the Third-Party Models.

Bedrock Model access

Provider	Model	Instance / Size	Notes
`SageMaker`	Falcon Lite	`ml.g5.12xlarge`	Quite stable and great for general purpose, flexible prompt engineering
`SageMaker`	Falcon 7B	`ml.g5.16xlarge`	Prefer Lite version
`SageMaker`	Falcon 40B	`ml.g5.48xlarge`	Expensive for unquantifiable benefits, Lite version is preferred at this time
`SageMaker`	LLama2	`ml.g5.12xlarge`	Followup questions are inconsistent, and formatting markup in responses - complex prompt engineer
`Bedrock`	Claude V2	-	Good results and easy to work with
`Bedrock`	Jurassic	-	Should work
`Bedrock`	Titan	-	Should work

Service Quotas

Ensure the necessary Service Quota limits for SageMaker models meet the capacity of your deployment configurations (<instance> for endpoint usage).

Status Keys

Model Status: Defines stability of deployment/integration with model and model/endpoint kwargs configuration optimization.
Prompt Status: Defines robustness and adaptability of prompt templates and engineering for this model.

Status	Description
-	Not applicable
	Not tested yet, might work, might not
	Very experimental, with high probability of undesirable results or errors
	Works for specific use case, but not vetted in the wild
	Should work for general use cases, but not fully battle tested
	Awesome, battled tested and ready for use