Merge branch 'main' into patch-35

Author: ssalgadodev

articles/ai-services/openai/api-version-deprecation.md

@@ -16,8 +16,9 @@ ms.custom:
 
 This article is to help you understand the support lifecycle for the Azure OpenAI API previews. New preview APIs target a monthly release cadence. Whenever possible we recommend using either the latest GA, or preview API releases.
 
+
 > [!NOTE]
-> The `2023-06-01-preview` API and the `2023-10-01-preview` API remain supported at this time.
+> New API response objects may be added to the API response without version changes. We recommend you only parse the response objects you require. 
 
 ## Latest preview API releases
 

articles/ai-services/openai/concepts/fine-tuning-considerations.md

@@ -66,9 +66,9 @@ Here’s an example: A customer wanted to use GPT-3.5-Turbo to turn natural lang
 **If you are ready for fine-tuning you:**
 
 - Have clear examples on how you have approached the challenges in alternate approaches and what’s been tested as possible resolutions to improve performance.
-- You've identified shortcomings using a base model, such as inconsistent performance on edge cases, inability to fit enough few shot prompts in the context window to steer the model, high latency, etc.
+- Identified shortcomings using a base model, such as inconsistent performance on edge cases, inability to fit enough few shot prompts in the context window to steer the model, high latency, etc.
 
-**Common signs you might not be ready for fine-tuning yet:**
+**Common signs you might not be ready for fine-tuning include:**
 
 - Insufficient knowledge from the model or data source.
 - Inability to find the right data to serve the model.
@@ -86,9 +86,9 @@ Another important point is even with high quality data if your data isn't in the
 
 **If you are ready for fine-tuning you:**
 
-- Have identified a dataset for fine-tuning.
-- The dataset is in the appropriate format for training.
-- Some level of curation has been employed to ensure dataset quality.
+- Identified a dataset for fine-tuning.
+- Formatted the dataset appropriately for training.
+- Curated the dataset to ensure quality.
 
 **Common signs you might not be ready for fine-tuning yet:**
 
@@ -103,4 +103,4 @@ There isn’t a single right answer to this question, but you should have clearl
 
 - Watch the [Azure AI Show episode: "To fine-tune or not to fine-tune, that is the question"](https://www.youtube.com/watch?v=0Jo-z-MFxJs)
 - Learn more about [Azure OpenAI fine-tuning](../how-to/fine-tuning.md)
-- Explore our [fine-tuning tutorial](../tutorials/fine-tune.md)
+- Explore our [fine-tuning tutorial](../tutorials/fine-tune.md)

articles/ai-services/openai/how-to/evaluations.md

@@ -22,6 +22,7 @@ Azure OpenAI evaluation enables developers to create evaluation runs to test aga
 
 ### Regional availability
 
+- East US2
 - North Central US
 - Sweden Central
 - Switzerland West

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

@@ -26,9 +26,6 @@ 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.
 
-> [!NOTE]
-> Azure OpenAI currently only supports text-to-text fine-tuning for all supported models including GPT-4o mini.
-
 ::: zone pivot="programming-language-studio"
 
 [!INCLUDE [Azure OpenAI Studio fine-tuning](../includes/fine-tuning-unified.md)]

articles/ai-services/openai/how-to/realtime-audio.md

@@ -161,4 +161,5 @@ An example `session.update` that configures several aspects of the session, incl
 ## Related content
 
 * Try the [real-time audio quickstart](../realtime-audio-quickstart.md)
+* See the [Realtime API reference](../realtime-audio-reference.md)
 * Learn more about Azure OpenAI [quotas and limits](../quotas-limits.md)

articles/ai-services/openai/includes/fine-tuning-unified.md

@@ -11,7 +11,12 @@ author: mrbullwinkle
 ms.author: mbullwin
 ---
 
-There are two unique fine-tuning experiences in Azure AI Foundry portal. Both allow you to fine-tune Azure OpenAI models, but only the Hub/Project view supports fine-tuning non Azure OpenAI models. If you are only using the Azure OpenAI fine-tuning experience which is available anytime you select a resource in a region where fine-tuning is supported.
+There are two unique fine-tuning experiences in the Azure AI Foundry portal:
+
+* [Hub/Project view](https://ai.azure.com) - supports fine-tuning models from multiple providers including Azure OpenAI, Meta Llama, Microsoft Phi, etc.
+* [Azure OpenAI centric view](https://oai.azure.com) - only supports fine-tuning Azure OpenAI models, but has support for additional features like the [Weights & Biases (W&B) preview integration](../how-to/weights-and-biases-integration.md). 
+
+If you are only fine-tuning Azure OpenAI models, we recommend the Azure OpenAI centric fine-tuning experience which is available by navigating to [https://oai.azure.com](https://oai.azure.com). 
 
 # [Azure OpenAI](#tab/azure-openai)
 

articles/ai-services/openai/realtime-audio-quickstart.md

@@ -128,4 +128,5 @@ You can run the sample code locally on your machine by following these steps. Re
 ## Related content
 
 * Learn more about [How to use the Realtime API](./how-to/realtime-audio.md)
+* See the [Realtime API reference](./realtime-audio-reference.md)
 * Learn more about Azure OpenAI [quotas and limits](quotas-limits.md)