# Register a Model

{% hint style="info" %}
*<mark style="color:green;">Please Note:</mark>* *The currently supported model types are: **Sklearn (ML & CV)**, **Keras (ML & CV)**, and **PyTorch (ML)**.*
{% endhint %}

{% hint style="info" %}
*Check out the walk-through to Register a DSL model to the* [*Data Pipeline*](https://docs.bdb.ai/7.6/data-pipeline/components/ai-ml/dsl-model-and-script-runner) *(from the Model tab).*
{% endhint %}

<figure><img src="https://859511478-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGDmsjfjJBNqow7Fo97cO%2Fuploads%2FJNRXY2PczEwkRNhiqtj8%2FRegister%20model.gif?alt=media&#x26;token=383ec7c4-7864-4c1f-8cb4-42637496975e" alt=""><figcaption><p>Registering a Model from the Model tab</p></figcaption></figure>

The user can deploy a saved DSL model to the Data Pipeline plugin by using the ***Model*** tab.

* Navigate to the ***Model*** tab.
* Select a model (unregistered model) from the list.
* Click the ***Register*** icon for the model.

<figure><img src="https://859511478-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGDmsjfjJBNqow7Fo97cO%2Fuploads%2FQpj6yRrXVutNhXXVnqWl%2Fimage.png?alt=media&#x26;token=bd05785b-a4fa-4657-ba5c-88a78326acbe" alt=""><figcaption><p>Registering a model from the Model tab</p></figcaption></figure>

* The ***Deploy to Pipeline*** dialog box appears to confirm the action.
* Click the ***Yes*** option.

![](https://859511478-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGDmsjfjJBNqow7Fo97cO%2Fuploads%2FmlF8rvW7sR20Qsdf1OVa%2Fimage.png?alt=media\&token=75c894ea-f4d7-4286-b169-38a6a0737c43)​

* The selected model gets published and deployed to the Data Pipeline (It disappears from the ***Unpublished*** model list).
* A notification message appears to inform the same.

<figure><img src="https://859511478-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGDmsjfjJBNqow7Fo97cO%2Fuploads%2FGfawkZsGqSvfrnx5wmUX%2Fimage.png?alt=media&#x26;token=5cf808d6-a268-40a0-9895-bcec76653d03" alt=""><figcaption><p>A confirmation message after the Model gets registered.</p></figcaption></figure>

* The model gets listed under the ***Registered*** model list.

<figure><img src="https://859511478-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FGDmsjfjJBNqow7Fo97cO%2Fuploads%2F7tME8TlEq78pVRLL6jaw%2Fimage.png?alt=media&#x26;token=9979f0d7-eefd-4e01-94b8-8dc0111bb075" alt=""><figcaption><p>The Model list displaying the Registered Models</p></figcaption></figure>

{% hint style="info" %}
*<mark style="color:green;">Please Note:</mark>*&#x20;

* The ***Register*** option provided under the ***Notebook tab*** and ***Model tab*** perform the same task.​
* *Refer the **Data Science Lab Quick Start Flow** page to get an overview of the **Data Science Lab** module in nutshell.* [***Click here***](https://docs.bdb.ai/data-science-lab/data-science-lab-quick-start-flow) *to get redirected to the quick start flow page.*
  {% endhint %}


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.bdb.ai/data-science-lab/project/tabs-for-a-data-science-lab-project/tabs-for-tensorflow-and-pytorch-environment/model/register-a-model.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
