# Download Pre-Built Models

### **Image Classification Models**

{% hint style="info" %}
Each download is zip file containing a TensorFlow Lite Model + Labels pair. When the download completes, unzip the model assets to your computer.
{% endhint %}

:robot: **Google's MobileNetV2**

Developed by Google, this model can classify 1,000 different objects - from umbrellas to volcanoes!

![Example images MobileNet was trained to classify](/files/-MMNNZPopFkDwrKZFqA5)

{% file src="/files/-MMI6JdzQRAqqHZhOYVi" %}
Download MobileNetV2
{% endfile %}

:sunflower: **FlowerNet**

This model classifies daisies, dandelions, roses, sunflowers, and tulips.

![Example images FlowerNet was trained to classify](/files/-MMNNlik9SulHtGbp6fZ)

{% file src="/files/-MMI6JdyieiVE9TBWkvM" %}
Download FlowerNet
{% endfile %}

:dog: **Dog Breeds**

This model can distinguish between 120 different dog breeds.

![Example images this model was trained to classify](/files/-MMNO79xPXCF5lF133Pm)

{% file src="/files/-MMI6JdqDvY5KIaNXJ3E" %}
Download Dog Breeds
{% endfile %}

:punch: **Rock-Paper-Scissors**

This model can tell if you're throwing Rock, Paper, or Scissors from the classic game.

It was trained on [3D generated images](http://www.laurencemoroney.com/rock-paper-scissors-dataset/) instead of photographs, so **for best results**, take a picture of your hand in Rock, Paper, or Scissors formation over a clear plain surface.

![Example images this model was trained to classify](/files/-MMNPLor3D6rEMdrqQQr)

{% file src="/files/-MMI6JdvZIR73Zw3K\_Gp" %}
Download Rock-Paper-Scissors
{% endfile %}

### Deploy Your Model

Now that you have model assets prepared, head back over to the tutorial to turn your model into a shareable image classification app:

{% content-ref url="/pages/-MMEc-O4zIXHIjinxTB0" %}
[Your First No-Code Smart App](/0.3.0/quickstart/your-first-no-code-smart-app.md)
{% endcontent-ref %}


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# Agent Instructions: Querying This Documentation

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