Mindket

OuteTTS WebGPU

Newversion 1 · updated

Overview

Turns text you type into spoken audio inside your browser, running the OuteTTS speech model on WebGPU through Transformers.js, for developers and anyone curious about in-browser speech.

OuteTTS WebGPU is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on . Download it on this page, a zip of its files. Nothing in it runs by itself.

At a glance

You need
  • Online use: a browser with WebGPU, nothing to install
  • Local files: Python with pip, on Windows, macOS or Linux
  • Dev server: Node.js with npm and a copy of the Hugging Face transformers.js-examples repository
Runs in
  • A web browser: open the Space's page on Hugging Face and run it there
  • A browser with WebGPU support, which the model uses for speed
  • Windows, macOS or Linux, if you download the files and open index.html
  • A local dev server, if you run the React and Vite source with npm
Start with
pip install -U huggingface_hub
hf download webml-community/OuteTTS-WebGPU --repo-type space --local-dir OuteTTS-WebGPU
cd OuteTTS-WebGPU

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

This Space runs OuteTTS, an experimental speech model, right inside your browser. OuteTTS generates speech purely by language modeling, so one model does the whole job. Transformers.js and WebGPU run it on your own graphics hardware, so you enter text and hear it spoken with nothing to install.

Who it suits

Front-end and machine learning developers get the most from it, because it shows a speech model running in a web page. Anyone curious about text to speech can also try it with no setup.

IndustryWho uses itHow they use itExample
Web developmentFront-end developersRead the React and Vite code to see how a model runs in a pageAdding spoken output to a web page prototype
Machine learningML engineersStudy speech generation done as language modelingComparing the approach with other speech models they know
EducationTeachers and studentsShow how a speech model turns text into audioA classroom demo of AI that runs in the browser
AccessibilityDesigners and testersHear how written text sounds when read aloudTrying a draft message as spoken audio

If you need polished voice work for finished audio, you can skip it, since the model is experimental.

Where to use it

  • A web browser: open the Space's page on Hugging Face and run it there
  • A browser with WebGPU support, which the model uses for speed
  • Windows, macOS or Linux, if you download the files and open index.html
  • A local dev server, if you run the React and Vite source with npm
Use caseWhoWhat they get back
Try speech synthesisAnyone curiousSpoken audio for the text they enter
Prototype a voice featureWeb developersA working React and Vite example to read and change
Teach in-browser AIEducatorsA live demo that needs no installs

How to set it up

Online use needs nothing beyond a browser. A local copy needs a few more things.

  • Online use: a browser with WebGPU, nothing to install
  • Local files: Python with pip, on Windows, macOS or Linux
  • Dev server: Node.js with npm and a copy of the Hugging Face transformers.js-examples repository
  1. Install the Hugging Face hub package.
  2. Download the Space's files into a folder.
  3. Move into that folder.
  4. Open index.html in a web browser.
pip install -U huggingface_hub
hf download webml-community/OuteTTS-WebGPU --repo-type space --local-dir OuteTTS-WebGPU
cd OuteTTS-WebGPU

To work on the React and Vite source instead, clone the examples repository, enter its text-to-speech-webgpu folder and install the dependencies.

npm i

How to use it

Open the Space page, enter the text you want spoken and start the generation. You then hear the result. If you run the dev copy, this command starts the server, and you open port 5173 on your own machine.

npm run dev

Example

You type "Welcome to the demo" into the page. The page turns that line into speech. You hear it spoken, while the model runs on your own graphics hardware.

For newcomers and experts

Text to speech means a computer reads written words aloud. To try it, open the Space page, type one short sentence and run it. Nothing gets installed, because the page does the work inside your browser.

OuteTTS handles speech as a language modeling task, so a single model generates it. Transformers.js loads that model in the page and WebGPU speeds up the maths on your GPU. The trade-off is that you depend on browser WebGPU support, and the model is experimental.

  1. You enter text on the page
  2. Transformers.js loads OuteTTS in your browser
  3. WebGPU runs the model on your graphics hardware
  4. The model generates speech from the text
  5. You hear the spoken result

Good to know

  • License: apache-2, as listed on Hugging Face
  • Cost to run: none named
  • Data it reaches: it runs in your browser, and the source names no files, account or clipboard access
  • Not for: production-critical voice work, since the source calls the model experimental
  • Needs a browser that supports WebGPU for the speed-up

README and files

README

OuteTTS WebGPU

Turns text you type into spoken audio inside your browser, running the OuteTTS speech model on WebGPU through Transformers.js, for developers and anyone curious about in-browser speech.

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 runs OuteTTS, an experimental speech model, right inside your browser. OuteTTS generates speech purely by language modeling, so one model does the whole job. Transformers.js and WebGPU run it on your own graphics hardware, so you enter text and hear it spoken with nothing to install.

Who it suits: Front-end and machine learning developers get the most from it, because it shows a speech model running in a web page. Anyone curious about text to speech can also try it with no setup.

Industry | Who uses it | How they use it | Example
Web development | Front-end developers | Read the React and Vite code to see how a model runs in a page | Adding spoken output to a web page prototype
Machine learning | ML engineers | Study speech generation done as language modeling | Comparing the approach with other speech models they know
Education | Teachers and students | Show how a speech model turns text into audio | A classroom demo of AI that runs in the browser
Accessibility | Designers and testers | Hear how written text sounds when read aloud | Trying a draft message as spoken audio

If you need polished voice work for finished audio, you can skip it, since the model is experimental.

Where to use it:

  • A web browser: open the Space's page on Hugging Face and run it there
  • A browser with WebGPU support, which the model uses for speed
  • Windows, macOS or Linux, if you download the files and open index.html
  • A local dev server, if you run the React and Vite source with npm
Use case | Who | What they get back
Try speech synthesis | Anyone curious | Spoken audio for the text they enter
Prototype a voice feature | Web developers | A working React and Vite example to read and change
Teach in-browser AI | Educators | A live demo that needs no installs

How to set it up: Online use needs nothing beyond a browser. A local copy needs a few more things.

  • Online use: a browser with WebGPU, nothing to install
  • Local files: Python with pip, on Windows, macOS or Linux
  • Dev server: Node.js with npm and a copy of the Hugging Face transformers.js-examples repository
  1. Install the Hugging Face hub package.
  2. Download the Space's files into a folder.
  3. Move into that folder.
  4. Open index.html in a web browser.
pip install -U huggingface_hub
hf download webml-community/OuteTTS-WebGPU --repo-type space --local-dir OuteTTS-WebGPU
cd OuteTTS-WebGPU

To work on the React and Vite source instead, clone the examples repository, enter its text-to-speech-webgpu folder and install the dependencies.

npm i

How to use it: Open the Space page, enter the text you want spoken and start the generation. You then hear the result. If you run the dev copy, this command starts the server, and you open port 5173 on your own machine.

npm run dev

Example: You type "Welcome to the demo" into the page. The page turns that line into speech. You hear it spoken, while the model runs on your own graphics hardware.

For newcomers and experts: Text to speech means a computer reads written words aloud. To try it, open the Space page, type one short sentence and run it. Nothing gets installed, because the page does the work inside your browser.

OuteTTS handles speech as a language modeling task, so a single model generates it. Transformers.js loads that model in the page and WebGPU speeds up the maths on your GPU. The trade-off is that you depend on browser WebGPU support, and the model is experimental.

You enter text on the page
Transformers.js loads OuteTTS in your browser
WebGPU runs the model on your graphics hardware
The model generates speech from the text
You hear the spoken result

Good to know:

  • License: apache-2, as listed on Hugging Face
  • Cost to run: none named
  • Data it reaches: it runs in your browser, and the source names no files, account or clipboard access
  • Not for: production-critical voice work, since the source calls the model experimental
  • Needs a browser that supports WebGPU for the speed-up

On Hugging Face, 13 November 2026

  • Likes: 46
  • Built with: static
  • License: apache-2.0

Links

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.

Files
README.md  5 KB

1 file, 5 KB, downloaded as a zip.

What’s new

  • Version 1 · 2026-11-12

Compare with similar

Listed Hugging Face Spaces in the same category that share the most tags with this one.

ProductLikesBuilt withLicenseLast change
OuteTTS WebGPU This page46staticapache-2.0
InferenceSupportShares static764staticafl-3.0
HuggyShares static463staticcc-by-nc-sa-4.0
Z-Image Lookalike LoRA IndexShares static189staticapache-2.0
Granite Docling 258M WebGPUShares static163staticapache-2.0
DINOv3 WebShares static162staticapache-2.0
Numbers as Mindket last read them, on 2026-11-12.

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