# 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="https://2699314397-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MME5PNg63VnuK-9c9y9%2F-MVcUUCx7VgtkGLj5sA7%2F-MVcUg6H3R1Zwnao5wnC%2Fbadge%20160.svg?alt=media&#x26;token=8641b49e-b2cf-488d-8f57-d580e58caf41" alt="" data-size="original">](https://play.google.com/store/apps/details?id=com.palletml.app)&#x20;

<img src="https://2699314397-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MME5PNg63VnuK-9c9y9%2F-MVcPwOY8s404namB7Dq%2F-MVcT_GkU0XvALSrV4ku%2Fqr%20code%20192.svg?alt=media&#x26;token=d4466a79-efa0-4a0f-b17c-e9ef2277c169" 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](https://guide.palletml.com/models/create-image-classifiers))

{% file src="<https://2699314397-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MME5PNg63VnuK-9c9y9%2F-MMI3DD6T31JfthRQcIt%2F-MMI6JdzQRAqqHZhOYVi%2FMobileNet.zip?alt=media&token=8b91fd30-08c0-41c0-bf39-84ecb311734b>" %}
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](https://guide.palletml.com/models/download-pre-built-models)
{% 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](https://2699314397-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2Fpalletml-guides%2F-MME6l3gHaIKJFF84Dbb%2F-MME79LWMAnC3yM4JzmO%2Fezgif-4-b29a79c113f1.gif?generation=1605497827229144\&alt=media)

## 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**.

![](https://2699314397-files.gitbook.io/~/files/v0/b/gitbook-legacy-files/o/assets%2F-MME5PNg63VnuK-9c9y9%2F-MVniAnR-lDETiDnA9OF%2F-MVnjtxbRNftBkXHhdiz%2Fstart%20making%20predictions%20shadow%20wide%20optim.gif?alt=media\&token=0faedfda-233b-45cb-b214-8c0b8d41a779)

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

## Up Next

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

{% content-ref url="models/create-image-classifiers" %}
[create-image-classifiers](https://guide.palletml.com/models/create-image-classifiers)
{% endcontent-ref %}

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

{% content-ref url="models/download-pre-built-models" %}
[download-pre-built-models](https://guide.palletml.com/models/download-pre-built-models)
{% endcontent-ref %}