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Copy file name to clipboardExpand all lines: articles/ai-foundry/model-inference/how-to/quickstart-ai-project.md
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@@ -141,7 +141,7 @@ Use the parameter `model="<deployment-name>` to route your request to this deplo
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## Move from Serverless API Endpoints to Azure AI model inference
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Although you configured the project to use the Azure AI model inference, existing model deployments continue to exit within the project as Serverless API Endpoints. Those deployments aren't moved for you. Hence, you can progressively upgrade any existing code that reference previous model deployments. To start moving the model deployments, we recommend the following workflow:
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Although you configured the project to use the Azure AI model inference, existing model deployments continue to exist within the project as Serverless API Endpoints. Those deployments aren't moved for you. Hence, you can progressively upgrade any existing code that reference previous model deployments. To start moving the model deployments, we recommend the following workflow:
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1. Recreate the model deployment in Azure AI model inference. This model deployment is accessible under the **Azure AI model inference endpoint**.
Copy file name to clipboardExpand all lines: articles/ai-services/content-safety/overview.md
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@@ -152,29 +152,29 @@ For more information, see [Language support](/azure/ai-services/content-safety/l
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To use the Content Safety APIs, you must create your Azure AI Content Safety resource in a supported region. Currently, the Content Safety features are available in the following Azure regions with different API versions:
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| Region | Custom Category | Groundedness | Image | Multimodal(Image with Tex) | Incident Response | Prompt Shield | Protected Material (Text) | Protected Material (Code) | Text | Unified API |
Copy file name to clipboardExpand all lines: articles/ai-services/openai/how-to/content-filters.md
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The default content filtering configuration is set to filter at the medium severity threshold for all four content harms categories for both prompts and completions. That means that content that is detected at severity level medium or high is filtered, while content detected at severity level low or safe is not filtered by the content filters. Learn more about content categories, severity levels, and the behavior of the content filtering system [here](../concepts/content-filter.md).
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Jailbreak risk detection and protected text and code models are optional and off by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default off and can be turned on per your scenario. Some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
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Jailbreak risk detection and protected text and code models are optional and on by default. For jailbreak and protected material text and code models, the configurability feature allows all customers to turn the models on and off. The models are by default on and can be turned off per your scenario. Some models are required to be on for certain scenarios to retain coverage under the [Customer Copyright Commitment](/legal/cognitive-services/openai/customer-copyright-commitment?context=%2Fazure%2Fai-services%2Fopenai%2Fcontext%2Fcontext).
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> [!NOTE]
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> All customers have the ability to modify the content filters and configure the severity thresholds (low, medium, high). Approval is required for turning the content filters partially or fully off. Managed customers only may apply for full content filtering control via this form: [Azure OpenAI Limited Access Review: Modified Content Filters](https://ncv.microsoft.com/uEfCgnITdR). At this time, it is not possible to become a managed customer.
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