Update serverless/pages/ml-nlp-auto-scale.mdx

Co-authored-by: István Zoltán Szabó <istvan.szabo@elastic.co>

serverless/pages/ml-nlp-auto-scale.mdx

@@ -70,9 +70,9 @@ Increasing the number of threads will make the search processes more performant.
 You can enable adaptive resources for your models when starting or updating the model deployment.
 Adaptive resources make it possible for Elasticsearch to scale up or down the available resources based on the load on the process.
 This can help you to manage performance and cost more easily.
-When adaptive resources are enabled, the number of vCPUs that the model deployment uses is set automatically based on the current load.
-When the load is high, the number of vCPUs that the process can use is automatically increased.
-When the load is low, the number of vCPUs that the process can use is automatically decreased.
+When adaptive resources are enabled, the number of vCUs that the model deployment uses is set automatically based on the current load.
+When the load is high, the number of vCUs that the process can use is automatically increased.
+When the load is low, the number of vCUs that the process can use is automatically decreased.
 
 You can choose from three levels of resource usage for your trained model deployment; autoscaling will occur within the selected level's range.