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Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-models-managed.md
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In this article, you learn how to deploy models using the Azure Machine Learning SDK. The article also covers how to perform inference on the deployed model.
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## Prerequisites
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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- If you don't have one, [create a [!INCLUDE [hub-project-name](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
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- Marketplace purchases enabled for your Azure subscription. Learn more [here](/azure/cost-management-billing/manage/enable-marketplace-purchases).
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## Get the model ID
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You can deploy managed compute models using the Azure Machine Learning SDK, but first, let's browse the model catalog and get the model ID you need for deployment.
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-models-serverless-availability.md
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Standard billing is available only to users whose Azure subscription belongs to a billing account in a country/region where the model provider has made the offer available (see "offer availability region" in the table in the next section). If the offer is available in the relevant region, the user then must have a Hub/Project in the Azure region where the model is available for deployment or fine-tuning, as applicable (see "Hub/Project Region" columns in the following tables).
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> [!NOTE]
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> If you plan to access your deployed models in Azure Machine Learning Studio, you must use a **[!INCLUDE [hub](../includes/hub-project-name.md)]**, rather than a **[!INCLUDE [fdp](../includes/fdp-project-name.md)]**. For more information, see [Project types](../what-is-azure-ai-foundry.md#project-types).
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-models-serverless-connect.md
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- An [Azure AI Foundry hub](create-azure-ai-resource.md), if you're using a **[!INCLUDE [hub](../includes/hub-project-name.md)]**. A **[!INCLUDE [fdp](../includes/fdp-project-name.md)]** does not use a hub. For more information, see [Project types](../what-is-azure-ai-foundry.md#project-types).
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-An [Azure AI Foundry project](create-projects.md).
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-If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
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- A model [deployed to a standard deployments](deploy-models-serverless.md). This article assumes that you previously deployed the **Meta-Llama-3-8B-Instruct** model. To learn how to deploy this model as a standard deployment, see [Deploy models as standard deployments](deploy-models-serverless.md).
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-models-serverless.md
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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-An [Azure AI Foundry project](create-projects.md).
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-If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
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- Ensure that the **Deploy models to Azure AI model inference service** feature is turned off in the Azure AI Foundry portal. When this feature is on, standard deployments are not available for deployment when using the portal.
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/deploy-nvidia-inference-microservice.md
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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-An [Azure AI Foundry project](create-projects.md).
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-If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
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- Marketplace purchases enabled for your Azure subscription. Learn more [here](/azure/cost-management-billing/manage/enable-marketplace-purchases).
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/healthcare-ai/deploy-cxrreportgen.md
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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-An [Azure AI Foundry project](../create-projects.md).
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-If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
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- Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/healthcare-ai/deploy-medimageinsight.md
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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- An [Azure AI Foundry project](../create-projects.md).
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- If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
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- Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
Copy file name to clipboardExpand all lines: articles/ai-foundry/how-to/healthcare-ai/deploy-medimageparse.md
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- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
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-An [Azure AI Foundry project](../create-projects.md).
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-If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
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- Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
Copy the **Azure AI Foundry project endpoint** in the **Overview** section of your project. You'll use it in a moment.
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:::image type="content" source="../media/how-to/projects/fdp-project-overview.png" alt-text="Screenshot shows the project overview for a Foundry project.":::
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> [!TIP]
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> If you don't see the **Azure AI Foundry project endpoint**, you're using a [!INCLUDE [hub-project-name](hub-project-name.md)]. (See [Types of projects](../what-is-azure-ai-foundry.md#project-types)). Switch to a [!INCLUDE [fdp-project-name](fdp-project-name.md)], or use the preceding steps to create one.
1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your Python scripts.
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> [!TIP]
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> [!NOTE]
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> All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/python/mslearn-resources/quickstart).
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# [Java (preview)](#tab/java)
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1. [Install Java and Azure CLI](../how-to/develop/install-cli-sdk.md?pivots=programming-language-java).
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1. [!INCLUDE [find-endpoint](find-endpoint.md)]
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1. Set these environment variables to use in your scripts:
1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your Java scripts.
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1. Download [POM.XML](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/java/mslearn-resources/quickstart/pom.xml) to your Java IDE.
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> [!TIP]
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> [!NOTE]
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> All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/java/mslearn-resources/quickstart).
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# [JavaScript (preview)](#tab/javascript)
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1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your JavaScript scripts.
> All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/javascript/mslearn-resources/quickstart).
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# [C#](#tab/csharp)
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1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your C# scripts.
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> All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/csharp/mslearn-resources/quickstart).
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# [REST API](#tab/rest)
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1. Save the results as the environment variable `AZURE_AI_AUTH_TOKEN`.
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> [!NOTE]
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> All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/REST/mslearn-resources/quickstart).
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# [Python](#tab/python)
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Substitute your endpoint for the `endpoint` in this code:
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