Creating an Endpoint for Custom Classification - Amazon Comprehend

Creating an Endpoint for Custom Classification

Once you have a custom model created and trained, all you need is an endpoint to enable real-time analysis using that model.

To create an endpoint (console)

  1. Sign in to the AWS Management Console and open the Amazon Comprehend console.

  2. From the left menu, choose Customization and then choose Custom Classification.

  3. From the Classifiers list, choose the name of the custom model for which you want to create the endpoint and follow the link. The Endpoints list on the custom model details page is displayed.


    Previously created endpoints are shown on the models detail page, along with the model with which they're associated.

  4. Under Endpoints, choose Create endpoint.

  5. Give the endpoint a name. The name must be unique within the AWS Region and account.

  6. Enter the number of inference units to assign to the endpoint. Each unit represents a throughput of 100 characters per second for up to 2 documents per second. You can assign up to a maximum of 10 inference units per endpoint.


    The throughput you assign the endpoint affects your costs. For more details, see Amazon Comprehend Pricing.

  7. (Optional) To add a tag to the endpoint, enter a key-value pair under Tags and choose Add tag. To remove this pair before creating the endpoint, choose Remove tag.

  8. Choose Create endpoint. The Endpoints list is displayed, with the new endpoint showing Creating. Once it shows Ready, the endpoint can be used for real-time analysis.

To create an endpoint (AWS CLI)

The following example demonstrates using the CreateEndpoint operation with the AWS CLI.

The example is formatted for Unix, Linux, and macOS. For Windows, replace the backslash (\) Unix continuation character at the end of each line with a caret (^).

aws comprehend create-endpoint \ --desired-inference-units number of inference units \ --endpoint-name endpoint name \ --model-arn arn:aws:comprehend:region:account-id:model/example \ --tags Key=My1stTag,Value=Value1

Amazon Comprehend responds with the following:

{ "EndpointArn": "Arn" }