Mindket

SoulX FlashHead

Newversion 1 · updated

Overview

Streams a demo of the SoulX FlashHead 1.3B model, which by its name and helper models looks like head video driven by speech. Suits people who want to try it or read its code.

SoulX FlashHead is a kit in the Productivity 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
  • Python with pip on Windows, macOS or Linux
  • The Hugging Face hub client, which the first step installs
  • The packages listed in requirements.txt
Runs in
  • A browser: open the Space's page on Hugging Face, with nothing to install
  • A copy on Windows, macOS or Linux, using Python
Start with
pip install -U huggingface_hub
hf download Soul-AILab/SoulX-FlashHead --repo-type space --local-dir SoulX-FlashHead
cd SoulX-FlashHead

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

This Space is a streaming demo of SoulX FlashHead, a 1.3B model from Soul-AILab. The page says only that it is a streaming demo. The models it names include a speech model, wav2vec2, and a PixArt image model, which suggests video of a head driven by speech. That reading is a guess from the names.

Who it suits

It suits people who want to try an experimental video model in the browser, and developers who want to read how a streaming Gradio demo is built.

IndustryWho uses itHow they use itExample
MediaVideo creatorsTry the model on short clips before deciding if it fitsOpen the Space and run an example
Machine learningResearchersLook at how a speech model and a video model are combinedRead generate_video.py and the flash_head folder
SoftwareDevelopersStudy a streaming Gradio app around a video modelOpen gradio_app_streaming.py and follow it

Skip it if you need documented inputs or a finished product, since the source describes neither.

Where to use it

  • A browser: open the Space's page on Hugging Face, with nothing to install
  • A copy on Windows, macOS or Linux, using Python
Use caseWhoWhat they get back
Trying the demoAnyone curiousA streamed result from the model for the example inputs
Reading the codeDevelopersA repository with a streaming app and a video generation script
Checking the partsResearchersA list of the models the demo names

How to set it up

The online copy needs nothing. For a copy on your own computer, you need the following.

  • Python with pip on Windows, macOS or Linux
  • The Hugging Face hub client, which the first step installs
  • The packages listed in requirements.txt
  1. Install the Hugging Face hub client.
  2. Download the Space's files into a local folder.
  3. Move into that folder.
  4. Install the Gradio version the Space pins.
  5. Install the remaining packages from requirements.txt.
  6. Start app.py.
pip install -U huggingface_hub
hf download Soul-AILab/SoulX-FlashHead --repo-type space --local-dir SoulX-FlashHead
cd SoulX-FlashHead
pip install gradio==5.50.0
pip install -r requirements.txt
python app.py

How to use it

Online, open the Space's page and try an example from the page. On your own computer, start the app with the command below. The source does not describe the controls, so follow the labels on the page.

python app.py

Example

You open the Space and pick one of the built-in examples. The page streams the model's result back as it is made. The source gives no sample input, output or timing.

For newcomers and experts

If you are new, start with a built-in example before you use your own material. Only use faces and voices you have the right to use.

If you know the field, the repository carries a streaming Gradio app, a separate video generation script and a download helper for the model files. The Space runs on zero-a10g hardware at Hugging Face. How the three named models connect is not stated.

  1. You open the Space or run app.py
  2. You pick an example or give an input
  3. The named models process it
  4. The result streams back to you

Good to know

The source is short, so features, inputs and limits are not described. Use only faces and voices you have the right to use.

  • License: apache-2, as listed on Hugging Face
  • Cost to run: no API key or paid service is named, and the online copy runs on zero-a10g hardware at Hugging Face
  • Data it reaches: what you give it, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files and model files
  • Not for: the source lists no exclusions, but do not use anyone's face or voice without permission

README and files

README

SoulX FlashHead

Streams a demo of the SoulX FlashHead 1.3B model, which by its name and helper models looks like head video driven by speech. Suits people who want to try it or read its code.

Made by Soul-AILab 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 streaming demo of SoulX FlashHead, a 1.3B model from Soul-AILab. The page says only that it is a streaming demo. The models it names include a speech model, wav2vec2, and a PixArt image model, which suggests video of a head driven by speech. That reading is a guess from the names.

Who it suits: It suits people who want to try an experimental video model in the browser, and developers who want to read how a streaming Gradio demo is built.

Industry | Who uses it | How they use it | Example
Media | Video creators | Try the model on short clips before deciding if it fits | Open the Space and run an example
Machine learning | Researchers | Look at how a speech model and a video model are combined | Read generate_video.py and the flash_head folder
Software | Developers | Study a streaming Gradio app around a video model | Open gradio_app_streaming.py and follow it

Skip it if you need documented inputs or a finished product, since the source describes neither.

Where to use it:

  • A browser: open the Space's page on Hugging Face, with nothing to install
  • A copy on Windows, macOS or Linux, using Python
Use case | Who | What they get back
Trying the demo | Anyone curious | A streamed result from the model for the example inputs
Reading the code | Developers | A repository with a streaming app and a video generation script
Checking the parts | Researchers | A list of the models the demo names

How to set it up: The online copy needs nothing. For a copy on your own computer, you need the following.

  • Python with pip on Windows, macOS or Linux
  • The Hugging Face hub client, which the first step installs
  • The packages listed in requirements.txt
  1. Install the Hugging Face hub client.
  2. Download the Space's files into a local folder.
  3. Move into that folder.
  4. Install the Gradio version the Space pins.
  5. Install the remaining packages from requirements.txt.
  6. Start app.py.
pip install -U huggingface_hub
hf download Soul-AILab/SoulX-FlashHead --repo-type space --local-dir SoulX-FlashHead
cd SoulX-FlashHead
pip install gradio==5.50.0
pip install -r requirements.txt
python app.py

How to use it: Online, open the Space's page and try an example from the page. On your own computer, start the app with the command below. The source does not describe the controls, so follow the labels on the page.

python app.py

Example: You open the Space and pick one of the built-in examples. The page streams the model's result back as it is made. The source gives no sample input, output or timing.

For newcomers and experts: If you are new, start with a built-in example before you use your own material. Only use faces and voices you have the right to use.

If you know the field, the repository carries a streaming Gradio app, a separate video generation script and a download helper for the model files. The Space runs on zero-a10g hardware at Hugging Face. How the three named models connect is not stated.

You open the Space or run app.py
You pick an example or give an input
The named models process it
The result streams back to you

Good to know: The source is short, so features, inputs and limits are not described. Use only faces and voices you have the right to use.

  • License: apache-2, as listed on Hugging Face
  • Cost to run: no API key or paid service is named, and the online copy runs on zero-a10g hardware at Hugging Face
  • Data it reaches: what you give it, which the online Space handles on Hugging Face's servers, and a local copy downloads the Space's files and model files
  • Not for: the source lists no exclusions, but do not use anyone's face or voice without permission

On Hugging Face, 13 November 2026

  • Likes: 16
  • Built with: gradio
  • 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  4 KB

1 file, 4 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
SoulX FlashHead This page16gradioapache-2.0
MusicGenShares gradio5,116gradiocc-by-nc-4.0
Kokoro TTSShares gradio3,556gradioapache-2.0
Background RemovalShares gradio2,988gradiomit
Omni Image EditorShares gradio2,922gradiomit
Diffusers Image OutpaintShares gradio2,565gradioapache-2.0
Numbers as Mindket last read them, on 2026-11-12.

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