> For the complete documentation index, see [llms.txt](https://guide.palletml.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://guide.palletml.com/quickstart-deploy-a-model.md).

# Quick Start - Deploy a Model

## 1. Get Pallet

**Install Pallet** from the Play Store (or **Scan** the QR Code) and **Sign Up** to create an account.

&#x20;[<img src="/files/-MVcUg6H3R1Zwnao5wnC" alt="" data-size="original">](https://play.google.com/store/apps/details?id=com.palletml.app)&#x20;

<img src="/files/-MVcT_GkU0XvALSrV4ku" alt="" data-size="original">&#x20;

## 2. Choose a Model

**Download** **MobileNet** below and **Unzip the model assets** to your computer. (Or [create your own model](/models/create-image-classifiers.md))

{% file src="/files/-MMI6JdzQRAqqHZhOYVi" %}
Download MobileNet assets
{% endfile %}

{% hint style="info" %}
These *assets* include a TensorFlow Lite image classification model & labels. [MobileNet](https://github.com/tensorflow/models/blob/master/research/slim/nets/mobilenet/README.md) is one of Google's state of the art vision models that can recognize 1,000 different objects. \
[See more pre-built models](/models/download-pre-built-models.md)
{% endhint %}

## 3. Deploy the Model

**Log In** to the [**web console**](https://app.palletml.com/) ([app.palletml.com](http://app.palletml.com/)) and **Create a New Project.**

**Browse** or **Drag & Drop** the model assets and click **Upload**.

![Drag, Drop, Deploy](/files/-MME79LWMAnC3yM4JzmO)

## 4. Start Making Predictions

**Go to** your **Profile** :bust\_in\_silhouette:in the Pallet app and **pull to refresh** to see your new Project.

**Open** the Project and **Launch** your app. *(Skip the Tune Settings dialog by tapping Launch again)*

You can **immediately** start classifying images by taking a picture with your camera, selecting a photo stored on your device, submitting link to an image, or going **real-time**.

![](/files/-MVnjtxbRNftBkXHhdiz)

:tada:**Congratulations** on deploying a model with Pallet! Your app is infinitely **scalable**, easily **upgradable**, and ready to be [**shared**](/deploy/share-your-model.md) with the world.

## Up Next

* Learn how to train and deploy your own **custom image classification model**:

{% content-ref url="/pages/-MMH2ACkMTVRaWx03O0V" %}
[Create an Image Classifier](/models/create-image-classifiers.md)
{% endcontent-ref %}

* Create more classification apps from **pre-built** models:

{% content-ref url="/pages/-MMEbmxz8mcJX6TqwDmm" %}
[Download Pre-Built Models](/models/download-pre-built-models.md)
{% endcontent-ref %}