fix

Author: msakande

articles/ai-foundry/how-to/deploy-models-serverless.md

@@ -32,7 +32,7 @@ In this article, you learn how to deploy a model from the model catalog as a ser
 
 - Ensure that the **Deploy models to Azure AI Foundry resources** feature is turned off in the Azure AI Foundry portal. When this feature is on, serverless API deployments are not available from the portal.
 
-    :::image type="content" source="../media/deploy-models-serverless/foundry-resources-deployment-disabled.gif" alt-text="A screenshot of the Azure AI Foundry portal showing where to disable deployment to Azure AI Foundry resources." lightbox="../media/deploy-models-serverless/foundry-resources-deployment-disabled.gif":::
+    :::image type="content" source="../media/deploy-models-serverless/foundry-resources-deployment-disabled.png" alt-text="A screenshot of the Azure AI Foundry portal showing where to disable deployment to Azure AI Foundry resources." lightbox="../media/deploy-models-serverless/foundry-resources-deployment-disabled.png":::
 
 - 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-azure-ai-foundry.md).
 
@@ -46,9 +46,9 @@ In this article, you learn how to deploy a model from the model catalog as a ser
 
 # [Models sold directly by Azure](#tab/azure-direct)
 
-4. Select the model card of the model you want to deploy. In this article, you select a **DeepSeek-R1-0528** model.
-1. Select **Use this model** and view the *Pricing and terms* tab in the window that opens.
-1. Select **Agree and Proceed** to open the deployment wizard. Here, you can name the deployment and select the deployment type.
+4. Select the model card of the model you want to deploy. In this article, you select a **DeepSeek-R1** model.
+1. Select **Use this model** to open the _Serverless API deployment_ window where you can view the *Pricing and terms* tab.
+1. In the deployment wizard, name the deployment. The **Content filter (preview)** option is enabled by default. Leave the default setting for the service to detect harmful content such as hate, self-harm, sexual, and violent content. For more information about content filtering, see [Content filtering in Azure AI Foundry portal](../concepts/content-filtering.md).
     :::image type="content" source="../media/deploy-models-serverless/deepseek-deployment-wizard.png" alt-text="Screenshot showing the deployment wizard for a model sold directly by Azure." lightbox="../media/deploy-models-serverless/deepseek-deployment-wizard.png":::
 
 
@@ -63,36 +63,34 @@ The next section covers the steps for subscribing your project to a model offeri
 
 ### Subscribe your project to the model offering
 
-Standard deployments can deploy both Microsoft and non-Microsoft offered models. For models from partners and community, e.g., the Gretel model, you must create a subscription before you can deploy them. If it's your first time deploying the model in the project, you have to subscribe your project for the particular model offering from the Azure Marketplace. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending.
+Standard deployments can deploy both Microsoft and non-Microsoft offered models. For models from partners and community, e.g., the AI21-Jamba-1.5-Large model, you must create a subscription before you can deploy them. If it's your first time deploying the model in the project, you have to subscribe your project for the particular model offering from the Azure Marketplace. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending.
 
 Furthermore, models offered through the Azure Marketplace are available for deployment to standard deployment in specific regions. Check [Model and region availability for standard deployment](deploy-models-serverless-availability.md) to verify which models and regions are available. If the one you need is not listed, you can deploy to a project in a supported region and then [consume standard deployment from a different project](deploy-models-serverless-connect.md).
 
-1. Create the model's marketplace subscription. When you create a subscription, you accept the terms and conditions associated with the model offer.
-
-    # [Azure AI Foundry portal](#tab/azure-ai-studio)
 
-    1. On the model's **Details** page, select **Use this model** to open the Serverless API deployment window. In the Serverless API deployment window, the **Azure Marketplace Terms** link provides more information about the terms of use. The **Pricing and terms** tab also provides pricing details for the selected model.
+1. On the model's **Details** page, select **Use this model** to open the Serverless API deployment window. In the Serverless API deployment window, the **Azure Marketplace Terms** link provides more information about the terms of use. The **Pricing and terms** tab also provides pricing details for the selected model.
 
-        > [!TIP]
-        > For models that can be deployed via serverless API deployment or managed compute, a **Deployment options** window opens up, giving you the choice between serverless API deployment and deployment using a managed compute. From there, you can select the serverless API deployment option.
-        > 
-        > To use the serverless API deployment offering, your project must belong to one of the [regions that are supported for serverless deployment](deploy-models-serverless-availability.md) for the particular model.
-        
-    1. If you've never deployed the model in your project before, you first have to subscribe to the model's offering in the Azure Marketplace. Select **Subscribe and Deploy** to open the deployment wizard. 
-        :::image type="content" source="../media/deploy-models-serverless/model-marketplace-subscription.png" alt-text="Screenshot showing where to subscribe a model to the Azure marketplace before deployment." lightbox="../media/deploy-models-serverless/model-marketplace-subscription.png":::
+    > [!TIP]
+    > For models that can be deployed via serverless API deployment or managed compute, a **Deployment options** window opens up, giving you the choice between serverless API deployment and deployment using a managed compute. From there, you can select the serverless API deployment option.
+    > 
+    > To use the serverless API deployment offering, your project must belong to one of the [regions that are supported for serverless deployment](deploy-models-serverless-availability.md) for the particular model.
+    
+1. If you've never deployed the model in your project before, you first have to subscribe to the model's offering in the Azure Marketplace. Select **Subscribe and Deploy** to open the deployment wizard. 
+    :::image type="content" source="../media/deploy-models-serverless/model-marketplace-subscription.png" alt-text="Screenshot showing where to subscribe a model to the Azure marketplace before deployment." lightbox="../media/deploy-models-serverless/model-marketplace-subscription.png":::
 
-    1. Alternatively, if you see the note *You already have an Azure Marketplace subscription for this project*, you don't need to create the subscription since you already have one. Select **Continue to deploy** to open the deployment wizard. 
-        :::image type="content" source="../media/deploy-models-serverless/model-subscribed-to-marketplace.png" alt-text="Deployment page for a model that is already subscribed to Azure marketplace." lightbox="../media/deploy-models-serverless/model-subscribed-to-marketplace.png":::    
+1. Alternatively, if you see the note *You already have an Azure Marketplace subscription for this project*, you don't need to create the subscription since you already have one. Select **Continue to deploy** to open the deployment wizard. 
+    :::image type="content" source="../media/deploy-models-serverless/model-subscribed-to-marketplace.png" alt-text="Deployment page for a model that is already subscribed to Azure marketplace." lightbox="../media/deploy-models-serverless/model-subscribed-to-marketplace.png":::    
 
-    1. (Optional) Once you subscribe a project for the particular Azure Marketplace offering, subsequent deployments of the same offering in the same project don't require subscribing again. At any point, you can see the model offers to which your project is currently subscribed:
-      
-        1. Go to the [Azure portal](https://portal.azure.com).
-        1. Navigate to the resource group where the project belongs.
-        1. On the **Type** filter, select **SaaS**.
-        1. You see all the offerings to which you're currently subscribed.
-        1. Select any resource to see the details.
+1. (Optional) Once you subscribe a project for the particular Azure Marketplace offering, subsequent deployments of the same offering in the same project don't require subscribing again. At any point, you can see the model offers to which your project is currently subscribed:
+    
+    1. Go to the [Azure portal](https://portal.azure.com).
+    1. Navigate to the resource group where the project belongs.
+    1. On the **Type** filter, select **SaaS**.
+    1. You see all the offerings to which you're currently subscribed.
+    1. Select any resource to see the details.
 
-    1. In the deployment wizard, name the deployment. The **Content filter (preview)** option is enabled by default. Leave the default setting for the service to detect harmful content such as hate, self-harm, sexual, and violent content. For more information about content filtering, see [Content filtering in Azure AI Foundry portal](../concepts/content-filtering.md).
+1. In the deployment wizard, name the deployment. The **Content filter (preview)** option is enabled by default. Leave the default setting for the service to detect harmful content such as hate, self-harm, sexual, and violent content. For more information about content filtering, see [Content filtering in Azure AI Foundry portal](../concepts/content-filtering.md).
+    :::image type="content" source="../media/deploy-models-serverless/deploy-with-content-filter.png" alt-text="Screenshot of the deployment wizard showing the content filter enabled." lightbox="../media/deploy-models-serverless/deploy-with-content-filter.png":::
 
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