> For the complete documentation index, see [llms.txt](https://docs.seldon.ai/seldon-enterprise-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.seldon.ai/seldon-enterprise-platform/demos/general/model-catalog.md).

# Model Catalog

## Prerequisites

{% hint style="info" %}
**Note**: This feature requires [PostgreSQL](/seldon-enterprise-platform/production-environment/postgresql/managed-postgresql.md) to be installed.
{% endhint %}

## Register New Model

1. Select the `Model Catalog` tab at the top of the page.
2. Click `Register a new model` to open the registration modal.
3. Enter the following parameters:

{% hint style="info" %}
**Note**: `Name`, `uri`, and `version` must be unique. If these values already exist in the model catalog and the model is in use, consider deleting the model everywhere it is currently running before continuing with this demonstration, or use your own values.
{% endhint %}

| Model Name    | `cifar10`                              |
| ------------- | -------------------------------------- |
| URI           | `gs://seldon-models/triton/tf_cifar10` |
| Artifact Type | `Tensorflow`                           |
| Version       | `v1.0`                                 |
| Task Type     | `Classification`                       |
| Project       | `seldon`                               |

4. Append tags and metric parameters with the following values. To add more parameters, use the `+` button. To delete a parameter, use the `x` button:
   * Tags:

     | Key            | Value      |
     | -------------- | ---------- |
     | `author`       | `Seldon`   |
     | `training_set` | `Resnet32` |
   * Metrics:

     | Key  | Value |
     | ---- | ----- |
     | `p1` | `0.8` |
     | `p2` | `0.6` |
5. Click `Register Model`.

![Register A Model](/files/B1KnF1mfsluJxxd1PCuG)

## Deploying Models From The Model Catalog

1. Select the `Model Catalog` tab at the top of the page.
2. Click on the vertical ellipses "⋮" icon for the model named `cifar10`.
3. In the dropdown menu that appears, select *Deploy*.
4. In the wizard which appears, enter the following details:

{% tabs %}
{% tab title="Seldon Core 2" %}

| Name         | `cifar10`            |
| ------------ | -------------------- |
| Namespace    | `seldon`             |
| Type         | `Seldon ML Pipeline` |
| Runtime      | `Tensorflow`         |
| {% endtab %} |                      |

{% tab title="Seldon Core 1" %}

| Name       | `cifar10`                                      |
| ---------- | ---------------------------------------------- |
| Namespace  | `seldon`                                       |
| Type       | `Seldon Deployment`                            |
| Runtime    | `Triton (ONNX, PyTorch, Tensorflow, TensorRT)` |
| Model Name | `cifar10`                                      |

{% hint style="warning" %}
The `Model Name` is linked to the name described in the `model-settings.json` file, located in the Google Cloud Storage location. Changing the name in the JSON file would also require changing the `Model Name`, and vice versa.
{% endhint %}

![Deployment predictor](/files/AkEyCz27EmzK2nFGTmsS)
{% endtab %}
{% endtabs %}

5. Click `Next` steps, then click `Launch`.

Select the `Overview` header tab to verify that your model has been deployed.

## Edit Model Metadata

{% hint style="info" %}
**Note**:

* Changing the prediction schema will require a new model to be registered.
* You can click on the vertical ellipses `⋮` button to clone a model and set a new prediction schema with a different `version`.
* `Name`, `Version`, `Tags`, and `Metrics` can be changed at any time.
  {% endhint %}

### From The Model Catalog

1. From the `Overview` page, select `Model Catalog` at the top of the page.
2. Select a model.
3. On the side drawer that opens, click `Edit Metadata`.
4. Add a new tag with the following values:

   | Key     | Value        |
   | ------- | ------------ |
   | `stage` | `production` |
5. Click `Save Metadata` at the top right hand side of the side drawer to save your edit.

### From A Deployment's Dashboard

1. From the Overview page, select a pipeline or deployment.
2. In the dashboard, click on the model within `Pipeline Components` (or `Deployment Components` for Core 1). This should open a drawer on the right hand side.
3. Click `Edit Metadata`.
4. Under the *Tags* section, press the `+` button to add a new tag.
5. For the new tag, enter the following parameters:

   | Key     | Value        |
   | ------- | ------------ |
   | `stage` | `production` |
6. Click `Save Metadata` on the top right of the side drawer.