preview note

Author: eric-urban

articles/ai-studio/ai-services/connect-ai-services.md

@@ -15,7 +15,7 @@ author: eric-urban
 
 # Connect AI services to your hub in Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 You can try out AI services for free in Azure AI Studio as described in the [getting started with AI services](get-started.md) article. This article describes how to use AI services connections to do more via Azure AI Studio, SDKs, and APIs. 
 

articles/ai-studio/ai-services/get-started.md

@@ -13,7 +13,7 @@ author: eric-urban
 
 # Get started with AI services in Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 This article describes how to get started with AI services in [Azure AI Studio](https://ai.azure.com). You can connect to AI services in Azure AI Studio to use AI capabilities such as Azure OpenAI, Speech, Language, Translator, Vision, Document Intelligence, and Content Safety.
 

articles/ai-studio/how-to/deploy-jais-models.md

@@ -14,7 +14,7 @@ ms.custom: [references_regions]
 
 # How to deploy JAIS with Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn how to use Azure AI Studio to deploy the JAIS model as serverless APIs with pay-as-you-go token-based billing.
 

articles/ai-studio/how-to/deploy-models-phi-3.md

@@ -15,7 +15,7 @@ ms.custom: [references_regions]
 
 # How to deploy Phi-3 family of small language models with Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn about the Phi-3 family of small language models (SLMs). You also learn two ways to use Azure AI Studio to deploy models from this family: deploy as serverless APIs with pay-as-you-go token-based billing or deploy with hosted infrastructure in real-time endpoints.
 

articles/ai-studio/how-to/deploy-models-serverless-availability.md

@@ -18,7 +18,7 @@ ms.custom:
 
 # Region availability for models in Serverless API endpoints
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn about which regions are available for each of the models supporting serverless API endpoint deployments.
 

articles/ai-studio/how-to/deploy-models-serverless-connect.md

@@ -17,7 +17,7 @@ ms.custom:
 
 # Consume serverless API endpoints from a different Azure AI Studio project or hub
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn how to configure an existing serverless API endpoint in a different project or hub than the one that was used to create the deployment.
 

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

@@ -17,7 +17,7 @@ ms.custom:
 
 # Deploy models as serverless APIs
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn how to deploy a model from the model catalog as a serverless API with pay-as-you-go token based billing.
 

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

@@ -16,7 +16,7 @@ ms.custom: [references_regions]
 
 # How to deploy a TimeGEN-1 model with Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 In this article, you learn how to use Azure AI Studio to deploy the TimeGEN-1 model as a service with pay-as you go billing.
 You filter on the Nixtla collection to browse the TimeGEN-1 model in the [Model Catalog](model-catalog.md).

articles/ai-studio/how-to/disaster-recovery.md

@@ -13,7 +13,7 @@ ms.date: 5/21/2024
 
 # Customer enabled disaster recovery
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 To maximize your uptime, plan ahead to maintain business continuity and prepare for disaster recovery with Azure AI Studio. Since Azure AI Studio builds on [Azure Machine Learning architecture](/azure/machine-learning/concept-workspace), it's beneficial to reference the foundational architecture.
 

articles/ai-studio/how-to/model-catalog-overview.md

@@ -15,7 +15,7 @@ author: ssalgadodev
 
 # Model Catalog and Collections in Azure AI Studio
 
-[!INCLUDE [Feature preview](./includes/feature-preview.md)]
+[!INCLUDE [Feature preview](../includes/feature-preview.md)]
 
 The model catalog in Azure AI studio is the hub to discover and use a wide range of models that enable you to build Generative AI applications. The model catalog features hundreds of models across model providers such as Azure OpenAI service, Mistral, Meta, Cohere, Nvidia, Hugging Face, including models trained by Microsoft. Models from providers other than Microsoft are Non-Microsoft Products, as defined in [Microsoft's Product Terms](https://www.microsoft.com/licensing/terms/welcome/welcomepage), and subject to the terms provided with the model.