Schema order changed.

Signed-off-by: Andrews Arokiam <[email protected]>

Author: andyi2it

docs/modelserving/autoscaling/autoscaling.md

@@ -510,7 +510,7 @@ KServe supports `RawDeployment` mode to enable `InferenceService` deployment wit
 When using Kserve with the `RawDeployment` mode, Knative is not installed. In this mode, if you deploy an `InferenceService`, Kserve uses **Kubernetes’ Horizontal Pod Autoscaler (HPA)** for autoscaling instead of **Knative Pod Autoscaler (KPA)**. For more information about Kserve's autoscaler, you can refer [`this`](https://kserve.github.io/website/master/modelserving/v1beta1/torchserve/#knative-autoscaler)
 
 
-=== "Old Schema"
+=== "New Schema"
 
     ```yaml
     apiVersion: "serving.kserve.io/v1beta1"
@@ -524,11 +524,13 @@ When using Kserve with the `RawDeployment` mode, Knative is not installed. In th
         serving.kserve.io/targetUtilizationPercentage: "80"
     spec:
       predictor:
-        sklearn:
+        model:
+          modelFormat:
+            name: sklearn
           storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
     ```
 
-=== "New Schema"
+=== "Old Schema"
 
     ```yaml
     apiVersion: "serving.kserve.io/v1beta1"
@@ -542,17 +544,15 @@ When using Kserve with the `RawDeployment` mode, Knative is not installed. In th
         serving.kserve.io/targetUtilizationPercentage: "80"
     spec:
       predictor:
-        model:
-          modelFormat:
-            name: sklearn
+        sklearn:
           storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
     ```
 
 ### Disable HPA in Raw Deployment
 
 If you want to control the scaling of the deployment created by KServe inference service with an external tool like [`KEDA`](https://keda.sh/). You can disable KServe's creation of the **HPA** by replacing **external** value with autoscaler class annotaion that should be disable the creation of HPA
 
-=== "Old Schema"
+=== "New Schema"
 
     ```yaml
     apiVersion: "serving.kserve.io/v1beta1"
@@ -564,11 +564,13 @@ If you want to control the scaling of the deployment created by KServe inference
       name: "sklearn-iris"
     spec:
       predictor:
-        sklearn:
+        model:
+          modelFormat:
+            name: sklearn
           storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
     ```
 
-=== "New Schema"
+=== "Old Schema"
 
     ```yaml
     apiVersion: "serving.kserve.io/v1beta1"
@@ -580,8 +582,6 @@ If you want to control the scaling of the deployment created by KServe inference
       name: "sklearn-iris"
     spec:
       predictor:
-        model:
-          modelFormat:
-            name: sklearn
+        sklearn:
           storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
     ```