Fix warning and formatting

Author: msakande

articles/machine-learning/concept-endpoints-online.md

@@ -140,7 +140,9 @@ To learn how to deploy online endpoints using the CLI, SDK, studio, and ARM temp
 
 [!INCLUDE [quota-allocation-online-deployment](includes/quota-allocation-online-deployment.md)]
 
-[!INCLUDE [machine-learning-shared-quota](includes/machine-learning-shared-quota.md)]
+#### Shared quota pool
+
+Also, [!INCLUDE [machine-learning-shared-quota](includes/machine-learning-shared-quota.md)]
 
 To deploy Llama-2, Phi, Nemotron, Mistral, Dolly, and Deci-DeciLM models from the model catalog via the shared quota, you must have an [Enterprise Agreement subscription](../cost-management-billing/manage/create-enterprise-subscription.md). For more information on how to use the shared quota for online endpoint deployment, see [How to deploy foundation models using the studio](how-to-use-foundation-models.md#shared-quota).
 

articles/machine-learning/how-to-deploy-online-endpoints.md

@@ -71,8 +71,7 @@ Before following the steps in this article, make sure you have the following pre
 
 * Ensure that you have enough virtual machine (VM) quota allocated for deployment. Azure Machine Learning reserves 20% of your compute resources for performing upgrades on some VM SKUs. For example, if you request 10 instances in a deployment, you must have a quota for 12 for each number of cores for the VM SKU. Failure to account for the extra compute resources results in an error. There are some VM SKUs that are exempt from the extra quota reservation. For more information on quota allocation, see [virtual machine quota allocation for deployment](how-to-manage-quotas.md#virtual-machine-quota-allocation-for-deployment).
 
-* Alternatively, you could use quota from Azure Machine Learning's shared quota pool for a limited time.
-  [!INCLUDE [machine-learning-shared-quota](includes/machine-learning-shared-quota.md)]
+* Alternatively, you could use quota from Azure Machine Learning's shared quota pool for a limited time. [!INCLUDE [machine-learning-shared-quota](includes/machine-learning-shared-quota.md)]
 
 
 ## Prepare your system

articles/machine-learning/includes/machine-learning-shared-quota.md

@@ -7,4 +7,4 @@ ms.author: mopeakande
 ---
 
 Azure Machine Learning provides a shared quota pool from which users across various regions can access quota to perform testing for a limited time, depending upon availability. 
-When you use the studio to deploy Llama-2, Phi, Nemotron, Mistral, Dolly, and Deci-DeciLM models from the model catalog to a managed online endpoint, Azure Machine Learning allows you to access its shared quota pool for a short time so that you can perform testing. For more information on the shared quota pool, see [Azure Machine Learning shared quota](how-to-manage-quotas.md#azure-machine-learning-shared-quota).
+When you use the studio to deploy Llama-2, Phi, Nemotron, Mistral, Dolly, and Deci-DeciLM models from the model catalog to a managed online endpoint, Azure Machine Learning allows you to access its shared quota pool for a short time so that you can perform testing. For more information on the shared quota pool, see [Azure Machine Learning shared quota](../how-to-manage-quotas.md#azure-machine-learning-shared-quota).

articles/machine-learning/includes/quota-allocation-online-deployment.md

@@ -10,5 +10,4 @@ ms.date: 12/07/2023
 For managed online endpoints, Azure Machine Learning reserves 20% of your compute resources for performing upgrades on some VM SKUs. If you request a given number of instances for those VM SKUs in a deployment, you must have a quota for `ceil(1.2 * number of instances requested for deployment) * number of cores for the VM SKU` available to avoid getting an error. For example, if you request 10 instances of a [Standard_DS3_v2](../../virtual-machines/dv2-dsv2-series.md) VM (that comes with four cores) in a deployment, you should have a quota for 48 cores (`12 instances * 4 cores`) available. This extra quota is reserved for system-initiated operations such as OS upgrades and VM recovery, and it won't incur cost unless such operations run.
 
 There are certain VM SKUs that are exempted from extra quota reservation. To view the full list, see [Managed online endpoints SKU list](../reference-managed-online-endpoints-vm-sku-list.md).
-
 To view your usage and request quota increases, see [View your usage and quotas in the Azure portal](../how-to-manage-quotas.md#view-your-usage-and-quotas-in-the-azure-portal). To view your cost of running a managed online endpoint, see [View costs for a managed online endpoint](../how-to-view-online-endpoints-costs.md).