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I have created 2 models which are not too complex and renamed them and placed them into a same location in S3 bucket.

I need to create a multi model endpoint such that the 2 models have a same end point. The model i am using is AWS in built Linear-learner model type regressor.

I am stuck as to how they should be deployed.

  • Take a look https://aws.amazon.com/blogs/machine-learning/save-on-inference-costs-by-using-amazon-sagemaker-multi-model-endpoints/ – Tuan Vo Feb 25 '20 at 00:46

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SageMaker's Linear Learner algorithm container does not currently implement the requirements for multi-model endpoints. You could request support in the AWS Forums.

You could also build your own version of the Linear Learner algorithm. To deploy the models to a multi-model endpoint you would need to build your own container that meets the requirements for multi-model endpoints and implement your own version of the Linear Learner algorithm. This sample notebook gives an example of how you would create your multi-model compatible container that serves MxNet models, but you could adapt it to implement a Linear Learner algorithm:

https://github.com/awslabs/amazon-sagemaker-examples/blob/master/advanced_functionality/multi_model_bring_your_own/multi_model_endpoint_bring_your_own.ipynb

colidyre
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