# Azure ML {% hint style="info" %} **Supported labeling types**: Row labeling. {% endhint %} ML-assisted labeling supports models from Azure ML. If you already have data and training pipelines in Azure ML, you can utilize your trained models to enhance the performance. To use the Azure model, you need to select **Azure** as the service provider. Once selected, you will see the menu below:
Image of ML Assisted with Azure
* **Target text**: Select the input text used as reference. * **Target question**: Select the output column to predict. * **API URL**: The endpoint built in Azure AutoML. * **API token**: The authentication token used to access the model from external applications. * **Faster prediction speed**: Enables faster predictions by processing requests on the backend. To obtain the API URL and API token, enable authentication when building the model. After deployment, you will receive the REST endpoint as the API URL and the authentication token as the API token.
Image of Azure menu
Once you have configured the settings, click **Predict labels** to generate predictions from your model.
Image of after configure Azure
--- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.datasaur.ai/assisted-labeling/ml-assisted-labeling/azure.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.