Microsoft Azure AI Engineer Associate AI-102 Practice Question
You train a custom English-to-Swedish translation model in Azure AI Custom Translator by uploading 10,000 parallel sentences. Training finishes with a quality score that meets your requirements. The next step is to connect the model to an existing web application that already sends requests to the standard Translator REST API endpoint. Which action must you take before the web application can use your custom translation model?
Export the model as an Azure Machine Learning package and deploy it to an Azure Kubernetes Service (AKS) cluster.
Register the model in Azure AI Studio and set it as the default model for the Translator resource.
Publish the trained model to obtain its Category ID, then reference that Category ID in the Translator API requests.
Add an Accept-CustomModel HTTP header that contains the model's name to every translation request.
A trained Custom Translator model is not callable through the public Translator REST API until it is published. Publishing assigns the model a Category ID (a GUID). When clients add this Category ID to the category query-string parameter of a translation request, the Translator service routes the request to the custom model. Exporting the model to Azure Machine Learning, registering it in AI Studio, or adding a proprietary HTTP header are not supported paths for making a Custom Translator model available through the Translator endpoint.
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What is a Category ID in Azure AI Custom Translator?
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How do you call a custom translation model using the Translator REST API?
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Microsoft Azure AI Engineer Associate AI-102
Implement natural language processing solutions
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