Merge branch 'main' into release-may-2024-openai

Author: v-alje

.openpublishing.redirection.json

@@ -1,5 +1,15 @@
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+    {
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+      "redirect_url": "/previous-versions/azure/network-watcher/network-watcher-security-group-view-powershell",
+      "redirect_document_id": false
+    },
+    {
+      "source_path": "articles/network-watcher/network-watcher-security-group-view-cli.md",
+      "redirect_url": "/previous-versions/azure/network-watcher/network-watcher-security-group-view-cli",
+      "redirect_document_id": false
+    },
     {
       "source_path": "articles/storage/blobs/blob-v11-samples-dotnet.md",
       "redirect_url": "/previous-versions/azure/storage/blobs/blob-v11-samples-dotnet",
@@ -3430,12 +3440,6 @@
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articles/active-directory-b2c/custom-policies-series-sign-up-or-sign-in-federation.md

@@ -225,7 +225,7 @@ Notice the claims transformations we defined in [step 3.2](#step-32---define-cla
 
 Just like in sign-in with a local account, you need to configure the [Microsoft Entra Technical Profiles](active-directory-technical-profile.md), which you use to connect to Microsoft Entra ID storage, to store or read a user social account. 
 
-1. In the `ContosoCustomPolicy.XML` file, locate the `AAD-UserRead` technical profile and then add a new technical profile by using the following code: 
+1. In the `ContosoCustomPolicy.XML` file, locate the `AAD-UserRead` technical profile and then add a new technical profile below it by using the following code: 
 
     ```xml
         <TechnicalProfile Id="AAD-UserWriteUsingAlternativeSecurityId">
@@ -517,6 +517,7 @@ Use the following steps to add a combined local and social account:
     ```xml
         <OutputClaim ClaimTypeReferenceId="authenticationSource" DefaultValue="localIdpAuthentication" AlwaysUseDefaultValue="true" />
     ```
+   Make sure you also add the `authenticationSource` claim in the output claims collection of the `UserSignInCollector` self-asserted technical profile.
 
 1. In the `UserJourneys` section, add a new user journey, `LocalAndSocialSignInAndSignUp` by using the following code: 
 

articles/ai-services/openai/how-to/fine-tuning.md

@@ -7,10 +7,10 @@ manager: nitinme
 ms.service: azure-ai-openai
 ms.custom: build-2023, build-2023-dataai, devx-track-python
 ms.topic: how-to
-ms.date: 02/22/2024
+ms.date: 05/03/2024
 author: mrbullwinkle
 ms.author: mbullwin
-zone_pivot_groups: openai-fine-tuning
+zone_pivot_groups: openai-fine-tuning-new
 ---
 
 # Customize a model with fine-tuning
@@ -26,10 +26,15 @@ In contrast to few-shot learning, fine tuning improves the model by training on
 
 We use LoRA, or low rank approximation, to fine-tune models in a way that reduces their complexity without significantly affecting their performance. This method works by approximating the original high-rank matrix with a lower rank one, thus only fine-tuning a smaller subset of "important" parameters during the supervised training phase, making the model more manageable and efficient. For users, this makes training faster and more affordable than other techniques.
 
-
 ::: zone pivot="programming-language-studio"
 
-[!INCLUDE [Studio fine-tuning](../includes/fine-tuning-studio.md)]
+[!INCLUDE [Azure OpenAI Studio fine-tuning](../includes/fine-tuning-studio.md)]
+
+::: zone-end
+
+::: zone pivot="programming-language-ai-studio"
+
+[!INCLUDE [AI Studio fine-tuning](../includes/fine-tuning-openai-in-ai-studio.md)]
 
 ::: zone-end
 
@@ -65,8 +70,8 @@ If your file upload fails, you can view the error message under “data files”
 
 - **Bad data:** A poorly curated or unrepresentative dataset will produce a low-quality model. Your model may learn inaccurate or biased patterns from your dataset. For example, if you are training a chatbot for customer service, but only provide training data for one scenario (e.g. item returns) it will not know how to respond to other scenarios. Or, if your training data is bad (contains incorrect responses), your model will learn to provide incorrect results.
 
-
 ## Next steps
 
 - Explore the fine-tuning capabilities in the [Azure OpenAI fine-tuning tutorial](../tutorials/fine-tune.md).
 - Review fine-tuning [model regional availability](../concepts/models.md#fine-tuning-models)
+- Learn more about [Azure OpenAI quotas](../quotas-limits.md)

articles/ai-services/openai/includes/create-resource-portal.md

@@ -89,7 +89,9 @@ As an option, you can add a private endpoint for access to your resource. Select
 
 1. Confirm your configuration settings, and select **Create**.
 
-The Azure portal displays a notification when the new resource is available.
+1. The Azure portal displays a notification when the new resource is available. Select **Go to resource**.
+
+   :::image type="content" source="../media/create-resource/create-resource-go-to-resource.png" alt-text="Screenshot showing the Go to resource button in the Azure portal.":::
 
 ## Deploy a model