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openshift-docs/modules/microshift-rhoai-install.adoc
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// Module included in the following assemblies:
//
// * microshift_ai/microshift-rhoai.adoc
:_mod-docs-content-type: PROCEDURE
[id="microshift-rhoai-install_{context}"]
= Installing the {rhoai-full} RPM
[role="_abstract"]
To use AI models in {microshift-short} deployments, install the {rhoai-full} ({rhoai}) RPM with a new {microshift-short} installation. You can also install the RPM on an existing {microshift-short} instance if you restart the system.
[NOTE]
====
The `microshift-ai-model-serving` RPM contains manifests that deploy `kserve`, with the raw deployment mode enabled, and `ServingRuntimes` objects in the `redhat-ods-applications` namespace.
====
:FeatureName: {rhoai-full}
include::snippets/technology-preview.adoc[leveloffset=+1]
.Prerequisites
* The system requirements for installing {microshift-short} have been met.
* You have root user access to your machine.
* The {oc-first} is installed.
* You configured your LVM VG with the capacity needed for the PVs of your workload.
* You have the RAM and disk space required for your AI model.
* You configured the required accelerators, hardware, operating system, and {microshift-short} to provide the resources your model needs.
* Your AI model is ready to use.
.Procedure
. Install the {microshift-short} AI-model-serving RPM package by running the following command:
+
[source,terminal]
----
$ sudo dnf install microshift-ai-model-serving
----
. As a root user, restart the {microshift-short} service by entering the following command:
+
[source,terminal]
----
$ sudo systemctl restart microshift
----
. Optional: Install the release information package by running the following command:
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[source,terminal]
----
$ sudo dnf install microshift-ai-model-serving-release-info
----
+
[NOTE]
====
The `microshift-ai-model-serving-release-info` RPM contains a JSON file with image references useful for offline procedures or deploying a copy of a `ServingRuntime` Custom Resource to your namespace during a bootc image build.
====
.Verification
* Verify that the `kserve` pod is running in the `redhat-ods-applications` namespace by entering the following command:
+
[source,terminal]
----
$ oc get pods -n redhat-ods-applications
----
+
.Example output
+
[source,text]
----
NAME READY STATUS RESTARTS AGE
kserve-controller-manager-7fc9fc688-kttmm 1/1 Running 0 1h
----
.Next steps
* Create a namespace for your AI model.
* Package your model into an OCI image.
* Configure a model-serving runtime.
* Verify that your model is ready for inferencing.
* Make requests against the model server.