diff --git a/docs/install/install-script.md b/docs/install/install-script.md
index 513d5daf..c129444b 100644
--- a/docs/install/install-script.md
+++ b/docs/install/install-script.md
@@ -14,7 +14,7 @@ We provide an install script to quickly run ModelMesh Serving with a provisioned
 
 The install script has a `--quickstart` option for setting up a self-contained ModelMesh Serving instance. This will deploy and configure local etcd and MinIO servers in the same Kubernetes namespace. Note that this is only for experimentation and/or development use - in particular the connections to these datastores are not secure and the etcd cluster is a single member which is not highly available. Use of `--quickstart` also configures the `storage-config` secret to be able to pull from the [ModelMesh Serving example models bucket](../example-models.md) which contains the model data for the sample `InferenceService`s. For complete details on the manifests applied with `--quickstart` see [config/dependencies/quickstart.yaml](https://github.com/kserve/modelmesh-serving/blob/main/config/dependencies/quickstart.yaml).
 
-## Setup the etcd connection information
+## Set up the etcd connection information
 
 If the `--quickstart` install option is **not** being used, details of an existing etcd cluster must be specified prior to installation. Otherwise, please skip this step and proceed to [Installation](#installation).
 
diff --git a/docs/quickstart.md b/docs/quickstart.md
index 759b3ea5..37578516 100644
--- a/docs/quickstart.md
+++ b/docs/quickstart.md
@@ -22,7 +22,7 @@ cd modelmesh-serving
 
 ```shell
 kubectl create namespace modelmesh-serving
-./scripts/install.sh --namespace modelmesh-serving --quickstart
+./scripts/install.sh --namespace-scope-mode --namespace modelmesh-serving --quickstart
 ```
 
 This will install ModelMesh Serving in the `modelmesh-serving` namespace, along with an etcd and MinIO instances.
@@ -53,6 +53,7 @@ kubectl get servingruntimes
 NAME           DISABLED   MODELTYPE    CONTAINERS   AGE
 mlserver-0.x              sklearn      mlserver     5m
 ovms-1.x                  openvino_ir  ovms         5m
+torchserve-0.x            pytorch-mar  torchserve   5m
 triton-2.x                tensorflow   triton       5m
 ```
 
@@ -62,9 +63,10 @@ are:
 
 | ServingRuntime | Supported Frameworks                |
 | -------------- | ----------------------------------- |
-| triton-2.x     | tensorflow, pytorch, onnx, tensorrt |
 | mlserver-0.x   | sklearn, xgboost, lightgbm          |
 | ovms-1.x       | openvino_ir, onnx                   |
+| torchserve-0.x | pytorch-mar                         |
+| triton-2.x     | tensorflow, pytorch, onnx, tensorrt |
 
 ## 2. Deploy a model
 
diff --git a/scripts/install.sh b/scripts/install.sh
index 34b31556..a73ac028 100755
--- a/scripts/install.sh
+++ b/scripts/install.sh
@@ -283,7 +283,8 @@ info "Installing ModelMesh Serving RBACs (namespace_scope_mode=$namespace_scope_
 if [[ $namespace_scope_mode == "true" ]]; then
   kustomize build rbac/namespace-scope | kubectl apply -f -
   # We don't install the ClusterServingRuntime CRD when in namespace scope mode, so comment it out first in the CRD manifest file
-  sed -i 's/- bases\/serving.kserve.io_clusterservingruntimes.yaml/#- bases\/serving.kserve.io_clusterservingruntimes.yaml/g' crd/kustomization.yaml
+  sed -i.bak 's/- bases\/serving.kserve.io_clusterservingruntimes.yaml/#- bases\/serving.kserve.io_clusterservingruntimes.yaml/g' crd/kustomization.yaml
+  rm crd/kustomization.yaml.bak
 else
   kustomize build rbac/cluster-scope | kubectl apply -f -
 fi
@@ -299,8 +300,9 @@ fi
 if [[ $namespace_scope_mode == "true" ]]; then
   info "Enabling namespace scope mode"
   kubectl set env deploy/modelmesh-controller NAMESPACE_SCOPE=true
-  # Reset crd/kustomization.yaml back to CSR crd since we used the same file for namespace scope mode installation 
-  sed -i 's/#- bases\/serving.kserve.io_clusterservingruntimes.yaml/- bases\/serving.kserve.io_clusterservingruntimes.yaml/g' crd/kustomization.yaml
+  # Reset crd/kustomization.yaml back to CSR crd since we used the same file for namespace scope mode installation
+  sed -i.bak 's/#- bases\/serving.kserve.io_clusterservingruntimes.yaml/- bases\/serving.kserve.io_clusterservingruntimes.yaml/g' crd/kustomization.yaml
+  rm crd/kustomization.yaml.bak
 fi
 
 info "Waiting for ModelMesh Serving controller pod to be up..."