MuseTalkDemo

MuseTalkDemo

A Docker-packaged demo app from TMElyralab for its MuseTalk model, bundled with DWPose, a Stable Diffusion autoencoder and ffmpeg tooling. It suits developers who want to try or study the MuseTalk setup.

Made by TMElyralab 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: MuseTalkDemo is TMElyralab's demo app for its MuseTalk model, packaged with Docker. The Space names MuseTalk, DWPose, the stabilityai/sd-vae-ft-mse autoencoder and gpt2. The repository holds a musetalk package, configs, scripts and an ffmpeg install script.

Who it suits: Developers and researchers who want to try the MuseTalk model or study how the demo is packaged. It also suits anyone who wants to run a copy under Docker on their own machine.

Title: Who uses the MuseTalk demo
Industry | Who uses it | How they use it | Example
Software | Developers | Run the demo in Docker and read how it is built | Build the image and open the app on port 7860
Research | Machine learning researchers | Try the MuseTalk model through its demo | Open the Space and use the app it serves
Operations | Engineers | Study the packaging of a model demo | Read the Dockerfile and entrypoint script

If you need documentation of what the model does and how to tune it, you can skip it, since the Space page gives only a configuration note.

Where to use it:

• A web browser: the Space runs on Hugging Face with nothing to install
• Windows, macOS or Linux, inside a Docker container

Use case | Who | What they get back
Try the model online | Anyone | The demo app in a browser tab
Run the demo yourself | Developers | A local container serving the app on port 7860
Study the setup | Engineers | A repository with a Dockerfile, configs and scripts

How to set it up: Using the Space online needs nothing. A local copy needs Docker and Python with pip for the download. The container installs the Python packages and the system packages the repository lists.

• Docker
• Python with pip, for the download

1. Install the Hugging Face hub package and download the Space into a folder.
2. Move into that folder.
3. Build the Docker image.
4. Run the container with port 7860 open.

pip install -U huggingface_hub
hf download TMElyralab/MuseTalk --repo-type space --local-dir MuseTalk
cd MuseTalk
docker build -t musetalk .
docker run -it -p 7860:7860 musetalk

How to use it: Open the Space in your browser, or run the container and open the app on port 7860. The source lists no further steps, so use the controls the page shows.

docker run -it -p 7860:7860 musetalk

Example: You build the image, run the container and open the app on port 7860. The app is whatever app.py serves, and you work with it through its page.

For newcomers and experts: If you are new to this, open the Space in your browser first and only then try a local copy. Docker is the harder part, so check that it runs before you build.

If you know the field, the Space names TMElyralab/MuseTalk with yzd-v/DWPose, stabilityai/sd-vae-ft-mse and openai-community/gpt2. The repository installs ffmpeg and starts from an entrypoint script. Beyond these names, the source does not say how the parts work together.

You build the Docker image
The container installs its packages
The entrypoint starts app.py
You open the app on port 7860

Good to know:

• Build: Docker with Python and system packages installed from the repository's lists
• Port: the app listens on 7860
• License: creativeml-openrail-m
• Cost to run: none named

On Hugging Face, 13 November 2026

• Likes: 78
• Built with: docker
• License: creativeml-openrail-m

Links

• Space: https://huggingface.co/spaces/TMElyralab/MuseTalk
• Files: https://huggingface.co/spaces/TMElyralab/MuseTalk/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.