Merge pull request #1497 from mrbullwinkle/mrb_11_11_2024_index

[Azure OpenAI] Studio consolidation

Author: JamesJBarnett

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: 10/03/2024
+ms.date: 11/11/2024
 author: mrbullwinkle
 ms.author: mbullwin
-zone_pivot_groups: openai-fine-tuning-new
+zone_pivot_groups: openai-fine-tuning-newest
 ---
 
 # Customize a model with fine-tuning
@@ -31,13 +31,7 @@ We use LoRA, or low rank approximation, to fine-tune models in a way that reduce
 
 ::: zone pivot="programming-language-studio"
 
-[!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)]
+[!INCLUDE [Azure OpenAI Studio fine-tuning](../includes/fine-tuning-unified.md)]
 
 ::: zone-end
 

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

@@ -1,7 +1,7 @@
 ---
-title: 'Customize a model with Azure OpenAI Service and Azure OpenAI Studio'
+title: 'Customize a model with Azure OpenAI Service and Azure AI Studio'
 titleSuffix: Azure OpenAI
-description: Learn how to create your own custom model with Azure OpenAI Service by using the Azure OpenAI Studio.
+description: Learn how to create your own custom model with Azure OpenAI Service by using the Azure AI Studio.
 #services: cognitive-services
 manager: nitinme
 ms.service: azure-ai-openai
@@ -17,8 +17,7 @@ ms.author: mbullwin
 - An Azure subscription. <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
 - An Azure OpenAI resource that's located in a region that supports fine-tuning of the Azure OpenAI model. Check the [Model summary table and region availability](../concepts/models.md#fine-tuning-models) for the list of available models by region and supported functionality. For more information, see [Create a resource and deploy a model with Azure OpenAI](../how-to/create-resource.md).
 - Fine-tuning access requires **Cognitive Services OpenAI Contributor**.
-- If you do not already have access to view quota, and deploy models in Azure OpenAI Studio you will require [additional permissions](../how-to/role-based-access-control.md).  
-
+- If you do not already have access to view quota, and deploy models in Azure AI Studio you will require [additional permissions](../how-to/role-based-access-control.md).  
 
 ## Models
 
@@ -41,12 +40,12 @@ Or you can fine tune a previously fine-tuned model, formatted as base-model.ft-{
 Consult the [models page](../concepts/models.md#fine-tuning-models) to check which regions currently support fine-tuning.
 
 
-## Review the workflow for Azure OpenAI Studio
+## Review the workflow for Azure AI Studio
 
-Take a moment to review the fine-tuning workflow for using Azure OpenAI Studio:
+Take a moment to review the fine-tuning workflow for using Azure AI Studio:
 
 1. Prepare your training and validation data.
-1. Use the **Create custom model** wizard in Azure OpenAI Studio to train your custom model.
+1. Use the **Create custom model** wizard in Azure AI Studio to train your custom model.
     1. [Select a base model](#select-the-base-model).
     1. [Choose your training data](#choose-your-training-data).
     1. Optionally, [choose your validation data](#choose-your-validation-data).
@@ -77,7 +76,7 @@ If you would like a step-by-step walk-through of fine-tuning a `gpt-4o-mini` (20
 {"messages": [{"role": "system", "content": "You are an Xbox customer support agent whose primary goal is to help users with issues they are experiencing with their Xbox devices. You are friendly and concise. You only provide factual answers to queries, and do not provide answers that are not related to Xbox."}, {"role": "user", "content": "I'm having trouble connecting my Xbox to the Wi-Fi."}, {"role": "assistant", "content": "No worries, let's go through the network settings on your Xbox. Can you please tell me what happens when you try to connect it to the Wi-Fi?"}]}
 ```
 
-## Multi-turn chat file format
+## Multi-turn chat file format Azure OpenAI 
 
 Multiple turns of a conversation in a single line of your jsonl training file is also supported. To skip fine-tuning on specific assistant messages add the optional `weight` key value pair. Currently `weight` can be set to 0 or 1.  
 
@@ -145,13 +144,13 @@ After it guides you through the process of implementing suggested changes, the t
 
 ## Use the Create custom model wizard
 
-Azure OpenAI Studio provides the **Create custom model** wizard, so you can interactively create and train a fine-tuned model for your Azure resource.
+Azure AI Studio provides the **Create custom model** wizard, so you can interactively create and train a fine-tuned model for your Azure resource.
 
-1. Open Azure OpenAI Studio at <a href="https://oai.azure.com/" target="_blank">https://oai.azure.com/</a> and sign in with credentials that have access to your Azure OpenAI resource. During the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
+1. Open Azure AI Studio at <a href="https://oai.azure.com/" target="_blank">https://oai.azure.com/</a> and sign in with credentials that have access to your Azure OpenAI resource. During the sign-in workflow, select the appropriate directory, Azure subscription, and Azure OpenAI resource.
 
-1. In Azure OpenAI Studio, browse to the **Tools > Fine-tuning** pane, and select **Fine-tune model**.
+1. In Azure AI Studio, browse to the **Tools > Fine-tuning** pane, and select **Fine-tune model**.
 
-   :::image type="content" source="../media/fine-tuning/studio-create-custom-model.png" alt-text="Screenshot that shows how to access the Create custom model wizard in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-create-custom-model.png":::
+   :::image type="content" source="../media/fine-tuning/studio-create-custom-model.png" alt-text="Screenshot that shows how to access the Create custom model wizard in Azure AI Studio." lightbox="../media/fine-tuning/studio-create-custom-model.png":::
 
 The **Create custom model** wizard opens.
 
@@ -180,7 +179,7 @@ For more information about our base models that can be fine-tuned, see [Models](
 
 The next step is to either choose existing prepared training data or upload new prepared training data to use when customizing your model. The **Training data** pane displays any existing, previously uploaded datasets and also provides options to upload new training data.
 
-:::image type="content" source="../media/fine-tuning/studio-training-data.png" alt-text="Screenshot of the Training data pane for the Create custom model wizard in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-training-data.png":::
+:::image type="content" source="../media/fine-tuning/studio-training-data.png" alt-text="Screenshot of the Training data pane for the Create custom model wizard in Azure AI Studio." lightbox="../media/fine-tuning/studio-training-data.png":::
 
 - If your training data is already uploaded to the service, select **Files from Azure OpenAI Connection**.
 
@@ -229,7 +228,7 @@ The next step provides options to configure the model to use validation data in
 
 The **Validation data** pane displays any existing, previously uploaded training and validation datasets and provides options by which you can upload new validation data. 
 
-:::image type="content" source="../media/fine-tuning/studio-validation-data.png" alt-text="Screenshot of the Validation data pane for the Create custom model wizard in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-validation-data.png":::
+:::image type="content" source="../media/fine-tuning/studio-validation-data.png" alt-text="Screenshot of the Validation data pane for the Create custom model wizard in Azure AI Studio." lightbox="../media/fine-tuning/studio-validation-data.png":::
 
 - If your validation data is already uploaded to the service, select **Choose dataset**.
 
@@ -294,15 +293,15 @@ After you configure the advanced options, select **Next** to [review your choice
 
 The **Review** pane of the wizard displays information about your configuration choices.
 
-:::image type="content" source="../media/fine-tuning/studio-review.png" alt-text="Screenshot of the Review pane for the Create custom model wizard in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-review.png":::
+:::image type="content" source="../media/fine-tuning/studio-review.png" alt-text="Screenshot of the Review pane for the Create custom model wizard in Azure AI Studio." lightbox="../media/fine-tuning/studio-review.png":::
 
 If you're ready to train your model, select **Start Training job** to start the fine-tuning job and return to the **Models** pane.
 
 ## Check the status of your custom model
 
 The **Models** pane displays information about your custom model in the **Customized models** tab. The tab includes information about the status and job ID of the fine-tune job for your custom model. When the job completes, the tab displays the file ID of the result file. You might need to select **Refresh** in order to see an updated status for the model training job.
 
-:::image type="content" source="../media/fine-tuning/studio-models-job-running.png" alt-text="Screenshot of the Models pane from Azure OpenAI Studio, with a custom model displayed." lightbox="../media/fine-tuning/studio-models-job-running.png":::
+:::image type="content" source="../media/fine-tuning/studio-models-job-running.png" alt-text="Screenshot of the Models pane from Azure AI Studio, with a custom model displayed." lightbox="../media/fine-tuning/studio-models-job-running.png":::
 
 After you start a fine-tuning job, it can take some time to complete. Your job might be queued behind other jobs on the system. Training your model can take minutes or hours depending on the model and dataset size.
 
@@ -318,7 +317,7 @@ Here are some of the tasks you can do on the **Models** pane:
 
 - Select **Refresh** to update the information on the page.
 
-:::image type="content" source="../media/fine-tuning/studio-model-details.png" alt-text="Screenshot of the Models pane in Azure OpenAI Studio, with a custom model displayed." lightbox="../media/fine-tuning/studio-models-job-running.png":::
+:::image type="content" source="../media/fine-tuning/studio-model-details.png" alt-text="Screenshot of the Models pane in Azure AI Studio, with a custom model displayed." lightbox="../media/fine-tuning/studio-models-job-running.png":::
 
 ## Checkpoints
 
@@ -340,13 +339,13 @@ When the fine-tuning job succeeds, you can deploy the custom model from the **Mo
 
 To deploy your custom model, select the custom model to deploy, and then select **Deploy model**.
 
-:::image type="content" source="../media/fine-tuning/studio-models-deploy-model.png" alt-text="Screenshot that shows how to deploy a custom model in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-models-deploy-model.png":::
+:::image type="content" source="../media/fine-tuning/studio-models-deploy-model.png" alt-text="Screenshot that shows how to deploy a custom model in Azure AI Studio." lightbox="../media/fine-tuning/studio-models-deploy-model.png":::
 
 The **Deploy model** dialog box opens. In the dialog box, enter your **Deployment name** and then select **Create** to start the deployment of your custom model. 
 
-:::image type="content" source="../media/fine-tuning/studio-models-deploy.png" alt-text="Screenshot of the Deploy Model dialog in Azure OpenAI Studio." lightbox="../media/fine-tuning/studio-models-deploy.png":::
+:::image type="content" source="../media/fine-tuning/studio-models-deploy.png" alt-text="Screenshot of the Deploy Model dialog in Azure AI Studio." lightbox="../media/fine-tuning/studio-models-deploy.png":::
 
-You can monitor the progress of your deployment on the **Deployments** pane in Azure OpenAI Studio.
+You can monitor the progress of your deployment on the **Deployments** pane in Azure AI Studio.
 
 ### Cross region deployment
 
@@ -358,13 +357,13 @@ Cross subscription/region deployment can be accomplished via [Python](/azure/ai-
 
 ## Use a deployed custom model
 
-After your custom model deploys, you can use it like any other deployed model. You can use the **Playgrounds** in [Azure OpenAI Studio](https://oai.azure.com) to experiment with your new deployment. You can continue to use the same parameters with your custom model, such as `temperature` and `max_tokens`, as you can with other deployed models. For fine-tuned `babbage-002` and `davinci-002` models you will use the Completions playground and the Completions API. For fine-tuned `gpt-35-turbo-0613` models you will use the Chat playground and the Chat completion API.
+After your custom model deploys, you can use it like any other deployed model. You can use the **Playgrounds** in [Azure AI Studio](https://oai.azure.com) to experiment with your new deployment. You can continue to use the same parameters with your custom model, such as `temperature` and `max_tokens`, as you can with other deployed models. For fine-tuned `babbage-002` and `davinci-002` models you will use the Completions playground and the Completions API. For fine-tuned `gpt-35-turbo-0613` models you will use the Chat playground and the Chat completion API.
 
-:::image type="content" source="../media/quickstarts/playground-load-new.png" alt-text="Screenshot of the Playground pane in Azure OpenAI Studio, with sections highlighted." lightbox="../media/quickstarts/playground-load-new.png":::
+:::image type="content" source="../media/quickstarts/playground-load-new.png" alt-text="Screenshot of the Playground pane in Azure AI Studio, with sections highlighted." lightbox="../media/quickstarts/playground-load-new.png":::
 
 ## Analyze your custom model
 
-Azure OpenAI attaches a result file named _results.csv_ to each fine-tuning job after it completes. You can use the result file to analyze the training and validation performance of your custom model. The file ID for the result file is listed for each custom model in the **Result file Id** column on the **Models** pane for Azure OpenAI Studio. You can use the file ID to identify and download the result file from the **Data files** pane of Azure OpenAI Studio.
+Azure OpenAI attaches a result file named _results.csv_ to each fine-tuning job after it completes. You can use the result file to analyze the training and validation performance of your custom model. The file ID for the result file is listed for each custom model in the **Result file Id** column on the **Models** pane for Azure AI Studio. You can use the file ID to identify and download the result file from the **Data files** pane of Azure AI Studio.
 
 The result file is a CSV file that contains a header row and a row for each training step performed by the fine-tuning job. The result file contains the following columns:
 
@@ -378,7 +377,7 @@ The result file is a CSV file that contains a header row and a row for each trai
 | `full_valid_loss` | The validation loss calculated at the end of each epoch. When training goes well, loss should decrease. |
 |`full_valid_mean_token_accuracy` | The valid mean token accuracy calculated at the end of each epoch. When training is going well, token accuracy should increase. |
 
-You can also view the data in your results.csv file as plots in Azure OpenAI Studio. Select the link for your trained model, and you will see three charts: loss, mean token accuracy, and token accuracy. If you provided validation data, both datasets will appear on the same plot.
+You can also view the data in your results.csv file as plots in Azure AI Studio. Select the link for your trained model, and you will see three charts: loss, mean token accuracy, and token accuracy. If you provided validation data, both datasets will appear on the same plot.
 
 Look for your loss to decrease over time, and your accuracy to increase. If you see a divergence between your training and validation data, that may indicate that you are overfitting. Try training with fewer epochs, or a smaller learning rate multiplier.
 
@@ -390,18 +389,18 @@ When you're done with your custom model, you can delete the deployment and model
 
 [!INCLUDE [Fine-tuning deletion](fine-tune.md)]
 
-You can delete the deployment for your custom model on the **Deployments** pane in Azure OpenAI Studio. Select the deployment to delete, and then select **Delete** to delete the deployment.
+You can delete the deployment for your custom model on the **Deployments** pane in Azure AI Studio. Select the deployment to delete, and then select **Delete** to delete the deployment.
 
 ### Delete your custom model
 
-You can delete a custom model on the **Models** pane in Azure OpenAI Studio. Select the custom model to delete from the **Customized models** tab, and then select **Delete** to delete the custom model.
+You can delete a custom model on the **Models** pane in Azure AI Studio. Select the custom model to delete from the **Customized models** tab, and then select **Delete** to delete the custom model.
 
 > [!NOTE]
 > You can't delete a custom model if it has an existing deployment. You must first [delete your model deployment](#delete-your-model-deployment) before you can delete your custom model.
 
 ### Delete your training files
 
-You can optionally delete training and validation files that you uploaded for training, and result files generated during training, on the **Management** > **Data files** pane in Azure OpenAI Studio. Select the file to delete, and then select **Delete** to delete the file.
+You can optionally delete training and validation files that you uploaded for training, and result files generated during training, on the **Management** > **Data files** pane in Azure AI Studio. Select the file to delete, and then select **Delete** to delete the file.
 
 ## Continuous fine-tuning
 

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

@@ -0,0 +1,24 @@
+---
+title: 'Customize a model with Azure OpenAI Service and Azure AI Studio'
+titleSuffix: Azure OpenAI
+description: Learn how to create your own custom model with Azure OpenAI Service by using the Azure AI Studio.
+#services: cognitive-services
+manager: nitinme
+ms.service: azure-ai-openai
+ms.topic: include
+ms.date: 11/11/2024
+author: mrbullwinkle    
+ms.author: mbullwin
+---
+
+There are two unique fine-tuning experiences in Azure AI Studio. 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.
+
+# [Azure OpenAI](#tab/azure-openai)
+
+[!INCLUDE [Azure AI Studio resource view fine-tuning](../includes/fine-tuning-studio.md)]
+
+# [Hub/Project](#tab/hub)
+
+[!INCLUDE [Azure AI Studio Hub/Project fine-tuning](../includes/fine-tuning-openai-in-ai-studio.md)]
+
+---

articles/ai-services/openai/media/fine-tuning/error.png

@@ -808,6 +808,17 @@ groups:
   - id: rest-api
     title: REST
 # Owner: mbullwin
+- id: openai-fine-tuning-newest
+  title: Programming languages
+  prompt: Choose your preferred fine-tuning method
+  pivots:
+  - id: programming-language-studio
+    title: AI Studio
+  - id: programming-language-python
+    title: Python
+  - id: rest-api
+    title: REST
+# Owner: mbullwin
 - id: URL-test-interface
   title: URL Test tool
   prompt: Choose one of the following