Merge pull request #232847 from mrbullwinkle/revert-232238-mrb_03_27_2023_fine_tuning

Revert "[Cognitive Services] [Azure OpenAI]  Fine-tuning model deployment changes"

Author: prmerger-automator[bot]

articles/cognitive-services/openai/concepts/models.md

@@ -194,8 +194,6 @@ These models can be used with Completion API requests. `gpt-35-turbo` is the onl
 <br><sup>2</sup> East US and West Europe were previously available, but due to high demand they are currently unavailable for new customers to use for fine-tuning. Please use US South Central region for fine-tuning.
 <br><sup>3</sup> Currently, only version `0301` of this model is available. This version of the model will be deprecated on 8/1/2023 in favor of newer version of the gpt-35-model. See [ChatGPT model versioning](../how-to/chatgpt.md#model-versioning) for more details.
 
-[!INCLUDE [Fine-tuning guidance](../includes/fine-tuning.md)]
-
 ### GPT-4 Models
 
 These models can only be used with the Chat Completion API.
@@ -219,8 +217,6 @@ These models can only be used with Completions API requests.
 
 <sup>1</sup> The model is available for fine-tuning by request only. Currently we aren't accepting new requests to fine-tune the model.
 
-[!INCLUDE [Fine-tuning guidance](../includes/fine-tuning.md)]
-
 ### Embeddings Models
 
 These models can only be used with Embedding API requests.

articles/cognitive-services/openai/faq.yml

@@ -98,11 +98,7 @@ sections:
           What are the SLAs for API responses in Azure OpenAI?
         answer:
           We don't have a defined API response time Service Level Agreement (SLA) at this time. The overall SLA for Azure OpenAI Service is the same as for other Azure Cognitive Services. For more information, see the Cognitive Services section of the [Service Level Agreements (SLA) for Online Services page](https://azure.microsoft.com/support/legal/sla/cognitive-services/v1_1/).  
-      - question: | 
-          My customized model (fine-tuned model) deployment was deleted, why did this happen?
-        answer:
-          Deployed customized models (fine-tuned models) that are inactive for greater than 90 days will automatically have their deployments deleted. **The underlying fine-tuned model is retained and can be redeployed at any time**. Once a fine-tuned model is deployed, it will continue to incur an hourly hosting cost regardless of whether you're actively using the model. To learn more about planning and managing costs with Azure OpenAI, refer to our [cost management guide](/azure/cognitive-services/openai/how-to/manage-costs#base-series-and-codex-series-fine-tuned-models).
-
+  
 additionalContent: |
 
   ## Next steps

articles/cognitive-services/openai/includes/fine-tuning-python.md

@@ -237,8 +237,6 @@ print(f'Found {len(result)} fine-tune jobs.')
 
 When the fine-tune job has succeeded, the value of `fine_tuned_model` in the response body of the FineTune.retrieve() method is set to the name of your customized model. Your model is now also available for discovery from the [list Models API](/rest/api/cognitiveservices/azureopenaistable/models/list). However, you can't issue completion calls to your customized model until your customized model is deployed. You must deploy your customized model to make it available for use with completion calls.
 
-[!INCLUDE [Fine-tuning guidance](../includes/fine-tuning.md)]
-
 > [!NOTE]
 > As with all applications, we require a review process prior to going live.
 

articles/cognitive-services/openai/includes/fine-tuning-rest.md

@@ -245,8 +245,6 @@ print(f'Found {len((r.json())["data"])} fine-tune jobs.')
 
 When the fine-tune job has succeeded, the value of `fine_tuned_model` in the response body of the `FineTune.retrieve()` method is set to the name of your customized model. Your model is now also available for discovery from the [list Models API](/rest/api/cognitiveservices/azureopenaistable/models/list). However, you can't issue completion calls to your customized model until your customized model is deployed. You must deploy your customized model to make it available for use with completion calls.
 
-[!INCLUDE [Fine-tuning guidance](../includes/fine-tuning.md)]
-
 > [!NOTE]
 > As with all applications, we require a review process prior to going live.
 

articles/cognitive-services/openai/includes/fine-tuning-studio.md

@@ -241,8 +241,6 @@ From the model page, you can also select **Download training file** to download
 
 When the fine-tune job has succeeded, you can deploy the customized model from the **Models** pane. You must deploy your customized model to make it available for use with completion calls.
 
-[!INCLUDE [Fine-tuning guidance](../includes/fine-tuning.md)]
-
 > [!NOTE]
 > Only one deployment is permitted for a customized model. An error message is displayed if you select an already-deployed customized model.
 

articles/cognitive-services/openai/includes/fine-tuning.md

@@ -8,7 +8,7 @@ ms.author: mbullwin
 ms.service: cognitive-services
 ms.subservice: openai
 ms.topic: overview
-ms.date: 03/27/2023
+ms.date: 03/21/2023
 recommendations: false
 keywords:  
 ---
@@ -17,12 +17,6 @@ keywords:
 
 ## March 2023
 
-### Fine-tuned model change
-
-Deployed customized models (fine-tuned models) that are inactive for greater than 90 days will now automatically have their deployments deleted. **The underlying fine-tuned model is retained and can be redeployed at any time**. Once a fine-tuned model is deployed, it will continue to incur an hourly hosting cost regardless of whether you're actively using the model. To learn more about planning and managing costs with Azure OpenAI, refer to our [cost management guide](/azure/cognitive-services/openai/how-to/manage-costs#base-series-and-codex-series-fine-tuned-models).
-
-### New Features
-
 - **GPT-4 series models are now available in preview on Azure OpenAI**. To request access, existing Azure OpenAI customers can [apply by filling out this form](https://aka.ms/oai/get-gpt4). These models are currently available in the East US and South Central US regions.
 
 - **New Chat Completion API for ChatGPT and GPT-4 models released in preview on 3/21**. To learn more checkout the [updated quickstarts](./quickstart.md) and [how-to article](./how-to/chatgpt.md).