update

Author: mrbullwinkle

articles/ai-foundry/openai/how-to/working-with-models.md

@@ -59,9 +59,9 @@ The corresponding property can also be accessed via [REST](../how-to/working-wit
 
 |Option| Read | Update |
 |---|---|---|
-| [REST](../how-to/working-with-models.md#model-deployment-upgrade-configuration) | Yes. If `versionUpgradeOption` is not returned, it means it is `null` |Yes |
+| [REST](../how-to/working-with-models.md#model-deployment-upgrade-configuration) | Yes. If `versionUpgradeOption` isn't returned, it means it's `null` |Yes |
 | [Azure PowerShell](/powershell/module/az.cognitiveservices/get-azcognitiveservicesaccountdeployment) | Yes.`VersionUpgradeOption` can be checked for `$null`| Yes |
-| [Azure CLI](/cli/azure/cognitiveservices/account/deployment#az-cognitiveservices-account-deployment-show) | Yes. It shows `null` if `versionUpgradeOption` is not set.| *No.* It is currently not possible to update the version upgrade option.|
+| [Azure CLI](/cli/azure/cognitiveservices/account/deployment#az-cognitiveservices-account-deployment-show) | Yes. It shows `null` if `versionUpgradeOption` isn't set.| *No.* It's currently not possible to update the version upgrade option.|
 
 There are three distinct model deployment upgrade options:
 
@@ -72,7 +72,7 @@ There are three distinct model deployment upgrade options:
 |`NoAutoUpgrade` | The model deployment never automatically upgrades. Once the retirement date is reached the model deployment stops working. You need to update your code referencing that deployment to point to a nonexpired model deployment. |
 
 > [!NOTE]
-> `null` is equivalent to `OnceCurrentVersionExpired`. If the **Version update policy** option is not present in the properties for a model that supports model upgrades this indicates the value is currently `null`. Once you explicitly modify this value, the property is visible in the studio properties page as well as via the REST API.
+> `null` is equivalent to `OnceCurrentVersionExpired`. If the **Version update policy** option isn't present in the properties for a model that supports model upgrades this indicates the value is currently `null`. Once you explicitly modify this value, the property is visible in the studio properties page as well as via the REST API.
 
 ### Examples
 
@@ -223,7 +223,7 @@ This is only a subset of the available request body parameters. For the full lis
 |Parameter|Type| Description |
 |--|--|--|
 |versionUpgradeOption | String | Deployment model version upgrade options:<br>`OnceNewDefaultVersionAvailable`<br>`OnceCurrentVersionExpired`<br>`NoAutoUpgrade`|
-|capacity|integer|This represents the amount of [quota](../how-to/quota.md) you are assigning to this deployment. A value of 1 equals 1,000 Tokens per Minute (TPM)|
+|capacity|integer|This represents the amount of [quota](../how-to/quota.md) you're assigning to this deployment. A value of 1 equals 1,000 Tokens per Minute (TPM)|
 
 #### Example request
 
@@ -302,7 +302,7 @@ Selecting a deployment name opens the **Properties** for the model deployment. F
 ![Screenshot of update deployment dialogue box with the model version field selector opened to show model version options available for selection.](media/working-with-models/provisioned-deployment-model-version-update.png)
 
 #### In-place migration: model family change
-In-place migration that target updating an existing provisioned deployment to a new model family are supported through REST API and Azure CLI. To perform an in-place migration targeting a model family change, use the example request below as a guide. In the request, you will need to update the model name and model version for the target model you are migrating to. 
+In-place migrations that target updating an existing provisioned deployment to a new model family are supported through REST API and Azure CLI. To perform an in-place migration targeting a model family change, use the example request below as a guide. In the request, you'll need to update the model name and model version for the target model you're migrating to. 
 
 ```Bash
 curl -X PUT https://management.azure.com/subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/resource-group-temp/providers/Microsoft.CognitiveServices/accounts/docs-openai-test-001/deployments/gpt-4o-ptu-deployment?api-version=2024-10-01 \
@@ -365,7 +365,7 @@ curl -X PUT https://management.azure.com/subscriptions/00000000-0000-0000-0000-0
 Multi-deployment migrations allow you to have greater control over the model migration process. With multi-deployment migrations, you can dictate how quickly you would like to migrate your existing traffic to the target model version or model family on a new provisioned deployment. The process to migrate to a new model version or model family using the multi-deployment migration approach is as follows:
 - Create a new provisioned deployment. For this new deployment, you can choose to maintain the same provisioned deployment type as your existing deployment or select a new deployment type if desired.
 - Transition traffic from the existing provisioned deployment to the newly created provisioned deployment with your target model version or model family until all traffic is offloaded from the original deployment. 
-- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric does not show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
+- Once traffic is migrated over to the new deployment, validate that there are no inference requests being processed on the previous provisioned deployment by ensuring the Azure OpenAI Requests metric doesn't show any API calls made within 5-10 minutes of the inference traffic being migrated over to the new deployment. For more information on this metric, [see the Monitor Azure OpenAI documentation](https://aka.ms/aoai/docs/monitor-azure-openai).
 - Once you confirm that no inference calls have been made, delete the original provisioned deployment.
 
 ## Next steps