Attention Visualization

Attention Visualization

Shows how a Vision Transformer pays attention to parts of an image, as a static web page that runs in the browser. It is one of the transformers.js example projects.

Made by webml-community on Hugging Face. These notes are Mindket's, written from its Space page and README; the app's own files and license are on Hugging Face.

About

What it is: This Space is a visualization of attention in a Vision Transformer, the kind of image model that splits a picture into patches. It is a static web page, so a browser is all you need and nothing gets installed. The project belongs to the transformers.js examples.

Who it suits: Students and developers who want to see where a vision model looks when it reads an image. Teachers can use the page to make the idea of attention easier to show.

Industry | Who uses it | How they use it | Example
Education | Teachers and students | Show how attention works inside an image model | Opening the page in a class on vision models
Machine learning | Engineers | Check what a Vision Transformer focuses on | Using the page to build an intuition for a model
Web development | Front end developers | Read a small browser project that runs a model | Opening index.html to see how the page is put together

If you do not work with image models, you can skip it.

Where to use it:

• A web browser, on the Space's page at Hugging Face
• Windows, macOS or Linux, by opening a downloaded index.html in any browser
• A local development server, using npm

Use case | Who | What they get back
See model attention | Students and engineers | A visualization of how a Vision Transformer attends to an image
Study a browser demo | Developers | A small project made of one page and its assets

How to set it up: Online use needs nothing. To keep a copy of the static page, you need little.

• Python and pip, only to download the files with the Hugging Face tool
• A web browser to open the page
• Node and npm, only if you follow the development server route

1. Install the Hugging Face hub package.
2. Download the Space's files into a local folder.
3. Move into that folder.
4. Open index.html in a web browser.

pip install -U huggingface_hub
hf download webml-community/attention-visualization --repo-type space --local-dir attention-visualization
cd attention-visualization

The project's own notes describe another route: clone the transformers.js examples repository from GitHub, move into its attention-visualization folder, install dependencies and start the development server.

cd transformers.js-examples/attention-visualization
npm i
npm run dev

How to use it: Online, open the Space's page and use the visualization there. With the development server running, open its page in your browser on port 5173.

npm run dev

Example: You open the page and look at how the Vision Transformer attends to an image. The page shows its attention as a visualization over the picture.

For newcomers and experts: If you are new to this, open the Space's page and look at the first image it shows. Nothing needs installing, and you see what attention means for an image model.

If you know the field, this is a Vision Transformer attention view in a single static page, with its assets in one folder. The repository is only 8 files, so it is easy to read through. The source does not describe how the attention is computed.

Open the page in a browser
The page loads a Vision Transformer
It shows attention over an image
You look at where the model attends

Good to know: The source gives few details, so check what the page shows for yourself.

• License: Apache 2.0, as the Space's license line says
• Cost to run: none named
• Data it reaches: the source names no accounts or services. The development route needs the transformers.js examples repository from GitHub

On Hugging Face, 13 November 2026

• Likes: 200
• Built with: static
• License: apache-2.0

Links

• Space: https://huggingface.co/spaces/webml-community/attention-visualization
• Files: https://huggingface.co/spaces/webml-community/attention-visualization/tree/main

Try it

Open the Space in your browser, or copy it to your own Hugging Face account from its page. Nothing in this kit runs by itself.