Merge pull request #2016 from msakande/freshness-timegen1-ai-foundry

TimeGEN-1: update procedural steps to align with new UX

Author: prmerger-automator[bot]

articles/ai-studio/how-to/deploy-models-cohere-rerank.md

@@ -59,7 +59,7 @@ Rerank multilingual performs well on multilingual benchmarks such as Miracl.
 
 Certain models in the model catalog can be deployed as a serverless API with pay-as-you-go billing. This kind of deployment provides a way to consume models as an API without hosting them on your subscription, while keeping the enterprise security and compliance that organizations need. This deployment option doesn't require quota from your subscription.
 
-You can deploy the previously mentioned Cohere models as a service with pay-as-you-go billing. Cohere offers these models through the Microsoft Azure Marketplace and can change or update the terms of use and pricing of these models.
+You can deploy the previously mentioned Cohere models as a service with pay-as-you-go billing. Cohere offers these models through Microsoft Azure Marketplace and can change or update the terms of use and pricing of these models.
 
 ### Prerequisites
 
@@ -95,7 +95,7 @@ To create a deployment:
 1. Select the **Subscribe and Deploy** button. If this is your first time deploying the model in the project, you have to subscribe your project for the particular offering.
 
     > [!NOTE]
-    > This step requires that your account has the **Azure AI Developer role** permissions on the resource group, as listed in the prerequisites. Models that are offered by non-Microsoft providers (for example, Cohere models) are billed through the Azure Marketplace. For such models, you're required to subscribe your project to the particular model offering. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Currently, you can have only one deployment for each model within a project.
+    > This step requires that your account has the **Azure AI Developer role** permissions on the resource group, as listed in the prerequisites. Models that are offered by non-Microsoft providers (for example, Cohere models) are billed through Azure Marketplace. For such models, you're required to subscribe your project to the particular model offering. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Currently, you can have only one deployment for each model within a project.
 
 1. Once you subscribe the project for the particular Azure Marketplace offering, subsequent deployments of the _same_ offering in the _same_ project don't require subscribing again. If this scenario applies to you, there's a **Continue to deploy** option to select.
 
@@ -237,11 +237,11 @@ The `results` object is a dictionary with the following fields:
 
 Quota is managed per deployment. Each deployment has a rate limit of 200,000 tokens per minute and 1,000 API requests per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits aren't sufficient for your scenarios. 
 
-Cohere models deployed as serverless APIs with pay-as-you-go billing are offered by Cohere through the Azure Marketplace and integrated with Azure AI Foundry for use. You can find the Azure Marketplace pricing when deploying the model.
+Cohere models deployed as serverless APIs with pay-as-you-go billing are offered by Cohere through Azure Marketplace and integrated with Azure AI Foundry for use. You can find Azure Marketplace pricing when deploying the model.
 
-Each time a project subscribes to a given offer from the Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference; however, multiple meters are available to track each scenario independently.
+Each time a project subscribes to a given offer from Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference; however, multiple meters are available to track each scenario independently.
 
-For more information on how to track costs, see [monitor costs for models offered throughout the Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace).
+For more information on how to track costs, see [monitor costs for models offered throughout Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace).
 
 
 

articles/ai-studio/how-to/deploy-models-timegen-1.md

@@ -5,7 +5,7 @@ description: Learn how to deploy TimeGEN-1 with Azure AI Foundry.
 manager: scottpolly
 ms.service: azure-ai-studio
 ms.topic: how-to
-ms.date: 5/21/2024
+ms.date: 12/16/2024
 ms.reviewer: kritifaujdar
 reviewer: fkriti
 ms.author: mopeakande
@@ -28,23 +28,15 @@ The Nixtla TimeGEN-1 is a generative, pretrained forecasting and anomaly detecti
 
 Certain models in the model catalog can be deployed as a serverless API with pay-as-you-go billing. This kind of deployment provides a way to consume models as an API without hosting them on your subscription, while keeping the enterprise security and compliance that organizations need. This deployment option doesn't require quota from your subscription.
 
-You can deploy TimeGEN-1 as a serverless API with pay-as-you-go billing. Nixtla offers TimeGEN-1 through the Microsoft Azure Marketplace. Nixtla can change or update the terms of use and pricing of this model.
+You can deploy TimeGEN-1 as a serverless API with pay-as-you-go billing. Nixtla offers TimeGEN-1 through Microsoft Azure Marketplace. Nixtla can change or update the terms of use and pricing of this model.
 
 ### Prerequisites
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions don'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.
-- An [Azure AI Foundry project](../how-to/create-projects.md). The serverless API model deployment offering for TimeGEN-1 is only available with projects created in these regions:
 
-    > [!div class="checklist"]
-    > * East US
-    > * East US 2
-    > * North Central US
-    > * South Central US
-    > * West US
-    > * West US 3
-    > * Sweden Central
+- An [Azure AI Foundry hub](../how-to/create-azure-ai-resource.md). The serverless API model deployment offering for Nixtla's TimeGEN-1 model is only available with hubs created in specific regions. For a list of these regions, see [Region availability for models in serverless API endpoints](deploy-models-serverless-availability.md#nixtla-models).
 
-    For a list of  regions that are available for each of the models supporting serverless API endpoint deployments, see [Region availability for models in serverless API endpoints](deploy-models-serverless-availability.md).
+- An [Azure AI Foundry project](../how-to/create-projects.md).
 
 - 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, visit [Role-based access control in Azure AI Foundry portal](../concepts/rbac-ai-studio.md).
 
@@ -89,20 +81,26 @@ These steps demonstrate the deployment of TimeGEN-1. To create a deployment:
 
 [!INCLUDE [open-catalog](../includes/open-catalog.md)]
 
-4. Search for and select **TimeGEN-1** to open its Details page.
+4. Select the model card of the model you want to deploy. In this article, you select **TimeGEN-1** to open the Model Details page.
+
 1. Select **Deploy** to open a serverless API deployment window for the model.
-1. Alternatively, you can initiate a deployment by starting from the **Models + endpoints** page in AI Foundry portal.
-    1. From the left navigation pane of your project, select **My assets** > **Models + endpoints**.
+1. Alternatively, you can initiate a deployment from your project in the AI Foundry portal as follows: 
+
+    1. From the left sidebar of your project, select **Models + Endpoints**.
     1. Select **+ Deploy model** > **Deploy base model**.
-    1. Search for and select **TimeGEN-1**. to open the Model's Details page.
+    1. Search for and select **TimeGEN-1** to open the Model Details page.
     1. Select **Confirm** to open a serverless API deployment window for the model.
-1. Your current project is specified for the deployment. To successfully deploy the TimeGEN-1 model, your project must be in one of the regions listed in the [Prerequisites](#prerequisites) section.
-1. In the deployment wizard, select the link to **Azure Marketplace Terms**, to learn more about the terms of use.
+
+1. In the deployment wizard, select the link to **Azure Marketplace Terms** to learn more about the terms of use.
 1. Select the **Pricing and terms** tab to learn about pricing for the selected model.
-1. Select the **Subscribe and Deploy** button. If this is your first time deploying the model in the project, you have to subscribe your project for the particular offering. This step requires that your account has the **Azure AI Developer role** permissions on the resource group, as listed in the prerequisites. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Currently, you can have only one deployment for each model within a project.
+1. Select the **Subscribe and Deploy** button. If this is your first time deploying the model in the project, you have to subscribe your project for the particular offering.
+
+    > [!NOTE]
+    > This step requires that your account has the **Azure AI Developer role** permissions on the resource group, as listed in the prerequisites. Models that are offered by non-Microsoft providers (for example, Nixtla TimeGEN-1) are billed through Azure Marketplace. For such models, you're required to subscribe your project to the particular model offering. Each project has its own subscription to the particular Azure Marketplace offering of the model, which allows you to control and monitor spending. Currently, you can have only one deployment for each model within a project.
+
 1. Once you subscribe the project for the particular Azure Marketplace offering, subsequent deployments of the _same_ offering in the _same_ project don't require subscribing again. If this scenario applies to you,  there's a **Continue to deploy** option to select.
 1. Give the deployment a name. This name becomes part of the deployment API URL. This URL must be unique in each Azure region.
-1. Select **Deploy**. Wait until the deployment is ready and you're redirected to the Deployments page.
+1. Select **Deploy**. Wait until the deployment is ready and you're redirected to the **Model deployments** page.
 1. Return to the Deployments page, select the deployment, and note the endpoint's **Target** URI and the Secret **Key**. For more information on using the APIs, see the [reference](#reference-for-timegen-1-deployed-as-a-serverless-api) section.
 1. [!INCLUDE [Find your deployment details](../includes/find-deployments.md)]
 
@@ -273,11 +271,11 @@ This JSON sample is an example response:
 
 ### Cost and quota considerations for TimeGEN-1 deployed as a serverless API
 
-Nixtla offers TimeGEN-1 deployed as a serverless API through the Azure Marketplace. TimeGEN-1 is integrated with Azure AI Foundry for use. You can find more information about Azure Marketplace pricing when you deploy the model.
+Nixtla offers TimeGEN-1 deployed as a serverless API through Azure Marketplace. TimeGEN-1 is integrated with Azure AI Foundry for use. You can find more information about Azure Marketplace pricing when you deploy the model.
 
-Each time a project subscribes to a given offer from the Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference; however, multiple meters are available to track each scenario independently.
+Each time a project subscribes to a given offer from Azure Marketplace, a new resource is created to track the costs associated with its consumption. The same resource is used to track costs associated with inference; however, multiple meters are available to track each scenario independently.
 
-For more information about how to track costs, visit [monitor costs for models offered throughout the Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace).
+For more information about how to track costs, visit [monitor costs for models offered throughout Azure Marketplace](./costs-plan-manage.md#monitor-costs-for-models-offered-through-the-azure-marketplace).
 
 Quota is managed per deployment. Each deployment has a rate limit of 200,000 tokens per minute and 1,000 API requests per minute. However, we currently limit one deployment per model per project. Contact Microsoft Azure Support if the current rate limits are insufficient for your scenarios.