Apply suggestions from code review

msakande · web-flow · commit fe03dd13c68f · 2024-07-12T13:44:39.000-05:00
diff --git a/articles/ai-studio/how-to/model-catalog-overview.md b/articles/ai-studio/how-to/model-catalog-overview.md
@@ -149,7 +149,7 @@ Phi-3-mini-128k-instruct <br> Phi-3-medium-4k-instruct <br> Phi-3-medium-128k-in
 
 [!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
 
-[!INCLUDE [content-safety-serverless-models](../includes/content-safety-serverless-models.md)].
+[!INCLUDE [content-safety-serverless-models](../includes/content-safety-serverless-models.md)]
 
 
 ### Network isolation for models deployed via Serverless APIs
diff --git a/articles/ai-studio/includes/content-safety-serverless-models.md b/articles/ai-studio/includes/content-safety-serverless-models.md
@@ -20,4 +20,4 @@ For language models deployed via serverless APIs, we implement a default configu
 
 Content filtering (preview) occurs synchronously as the service processes prompts to generate content, and you might be billed separately as per [AACS pricing](https://azure.microsoft.com/pricing/details/cognitive-services/content-safety/) for such use. You can disable content filtering (preview) for individual serverless endpoints either at the time when you first deploy a language model or later in the deployment details page by selecting the content filtering toggle.
 
-Suppose, you decide to use an API other than the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api) to work with a model that's deployed via a serverless API. In such a situation, content filtering (preview) is disabled, but you can implement it separately by using Azure AI Content Safety. For more information on how to get started with content safety, see [QuickStart: Analyze text content](/azure/ai-services/content-safety/quickstart-text). If you don't use content filtering (preview) when working with models that are deployed via serverless APIs, you run a higher risk of exposing users to harmful content.
+Suppose you decide to use an API other than the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api) to work with a model that's deployed via a serverless API. In such a situation, content filtering (preview) is disabled, but you can implement it separately by using Azure AI Content Safety. For more information on how to get started with content safety, see [QuickStart: Analyze text content](/azure/ai-services/content-safety/quickstart-text). If you don't use content filtering (preview) when working with models that are deployed via serverless APIs, you run a higher risk of exposing users to harmful content.

Original file line number	Diff line number	Diff line change
`@@ -20,4 +20,4 @@ For language models deployed via serverless APIs, we implement a default configu`
`20`	`20`
`21`	`21`	`Content filtering (preview) occurs synchronously as the service processes prompts to generate content, and you might be billed separately as per [AACS pricing](https://azure.microsoft.com/pricing/details/cognitive-services/content-safety/) for such use. You can disable content filtering (preview) for individual serverless endpoints either at the time when you first deploy a language model or later in the deployment details page by selecting the content filtering toggle.`
`22`	`22`
`23`		-Suppose, you decide to use an API other than the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api) to work with a model that's deployed via a serverless API. In such a situation, content filtering (preview) is disabled, but you can implement it separately by using Azure AI Content Safety. For more information on how to get started with content safety, see [QuickStart: Analyze text content](/azure/ai-services/content-safety/quickstart-text). If you don't use content filtering (preview) when working with models that are deployed via serverless APIs, you run a higher risk of exposing users to harmful content.
	`23`	+Suppose you decide to use an API other than the [Azure AI Model Inference API](/azure/ai-studio/reference/reference-model-inference-api) to work with a model that's deployed via a serverless API. In such a situation, content filtering (preview) is disabled, but you can implement it separately by using Azure AI Content Safety. For more information on how to get started with content safety, see [QuickStart: Analyze text content](/azure/ai-services/content-safety/quickstart-text). If you don't use content filtering (preview) when working with models that are deployed via serverless APIs, you run a higher risk of exposing users to harmful content.