Merge pull request #4687 from voutilad/ptum-global-ga

Drop preview tags for Global and PTU-M FT.

Author: prmerger-automator[bot]

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

@@ -366,7 +366,9 @@ Azure OpenAI fine-tuning supports the following deployment types.
 |GPT-35-Turbo-1106-finetune|East US2, North Central US, Sweden Central, Switzerland West|
 |GPT-35-Turbo-0125-finetune|East US2, North Central US, Sweden Central, Switzerland West|
 
-### Global Standard (preview)
+### Global Standard
+
+[Global standard](./deployment-types.md#global-standard) fine-tuned deployments offer [cost savings](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/), but custom model weights may temporarily be stored outside the geography of your Azure OpenAI resource.
 
 | Models | Region |
 |--|--|
@@ -375,72 +377,16 @@ Azure OpenAI fine-tuning supports the following deployment types.
 |GPT-4o-finetune|East US2, North Central US, and Sweden Central|
 |GPT-4o-mini-finetune|East US2, North Central US, and Sweden Central|
 
-[Global standard](./deployment-types.md#global-standard) fine-tuned deployments offer [cost savings](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/), but custom model weights may temporarily be stored outside the geography of your Azure OpenAI resource.
-
 :::image type="content" source="../media/fine-tuning/global-standard.png" alt-text="Screenshot of the global standard deployment user experience with a fine-tuned model." lightbox="../media/fine-tuning/global-standard.png":::
 
-### Provisioned Managed (preview)
+### Provisioned Managed
 
 | Models | Region |
 |--|--|
-|GPT-4o-finetune|North Central US, Switzerland West|
-|GPT-4o-mini-finetune|North Central US, Switzerland West|
-
-- `gpt-4o-mini-2024-07-18`
-- `gpt-4o-2024-08-06`
-
-[Provisioned managed](./deployment-types.md#provisioned) fine-tuned deployments offer [predictable performance](../concepts/provisioned-throughput.md) for fine-tuned deployments. As part of public preview, provisioned managed deployments may be created regionally via the data-plane [REST API](../reference.md#data-plane-inference) version `2024-10-01` or newer. See below for examples.
-
-#### Creating a Provisioned Managed deployment
-
-To create a new deployment, make an HTTP PUT call via the [Deployments - Create or Update REST API](/rest/api/aiservices/accountmanagement/deployments/create-or-update?view=rest-aiservices-accountmanagement-2024-10-01&tabs=HTTP&preserve-view=true). The approach is similar to performing [cross region deployment](#cross-region-deployment) with the following exceptions:
-
-- You must provide a `sku` name of `ProvisionedManaged`.
-- The capacity must be declared in PTUs.
-- The `api-version` must be `2024-10-01` or newer.
-- The HTTP method should be `PUT`.
-
-For example, to deploy a gpt-4o-mini model:
-
-```bash
-curl -X PUT "https://management.azure.com/subscriptions/<SUBSCRIPTION>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.CognitiveServices/accounts/<RESOURCE_NAME>/deployments/<MODEL_DEPLOYMENT_NAME>api-version=2024-10-01" \
-  -H "Authorization: Bearer <TOKEN>" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "sku": {"name": "ProvisionedManaged", "capacity": 25},
-    "properties": {
-        "model": {
-            "format": "OpenAI",
-            "name": "gpt-4omini-ft-model-name",
-            "version": "1",
-            "source": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/{SourceResourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{SourceAOAIAccountName}"
-        }
-    }
-  }'
-```
-
-#### Scaling a fine-tuned model on Provisioned Managed
+|GPT-4o-finetune|North Central US, Sweden Central|
+|GPT-4o-mini-finetune|North Central US, Sweden Central|
 
-To scale a fine-tuned provision managed deployment to increase or decrease PTU capacity, perform the same `PUT` REST API call as you did when [creating the deployment](#creating-a-provisioned-managed-deployment) and provide an updated `capacity` value for the `sku`. Keep in mind, provisioned deployments must scale in [minimum increments](../how-to/provisioned-throughput-onboarding.md#how-much-throughput-per-ptu-you-get-for-each-model).
-
-For example, to scale the model deployed in the previous section from 25 to 40 PTU, make another `PUT` call and increase the capacity:
-
-```bash
-curl -X PUT "https://management.azure.com/subscriptions/<SUBSCRIPTION>/resourceGroups/<RESOURCE_GROUP>/providers/Microsoft.CognitiveServices/accounts/<RESOURCE_NAME>/deployments/<MODEL_DEPLOYMENT_NAME>api-version=2024-10-01" \
-  -H "Authorization: Bearer <TOKEN>" \
-  -H "Content-Type: application/json" \
-  -d '{
-    "sku": {"name": "ProvisionedManaged", "capacity": 40},
-    "properties": {
-        "model": {
-            "format": "OpenAI",
-            "name": "gpt-4omini-ft-model-name",
-            "version": "1",
-            "source": "/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/{SourceResourceGroupName}/providers/Microsoft.CognitiveServices/accounts/{SourceAOAIAccountName}"
-        }
-    }
-  }'
-```
+[Provisioned managed](./deployment-types.md#provisioned) fine-tuned deployments offer [predictable performance](../concepts/provisioned-throughput.md) for latency-sensitive agents and applications. They use the same regional provisioned throughput (PTU) capacity as base models, so if you already have regional PTU quota you can deploy your fine-tuned model in support regions.
 
 ## Clean up your deployment