Mindket

VideoLLaMA2

Newversion 1 · updated

Overview

A chat app for understanding media such as video, built on the VideoLLaMA2 models. Runs in the browser as a Gradio app on ZeroGPU, for people who want to ask questions about clips.

VideoLLaMA2 is a kit in the Research 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 and pip
  • The huggingface_hub package, which gives you the hf command
  • Disk space for the repository, which holds 87 files
Runs in
  • A web browser, on the Space's page at Hugging Face
  • Windows, with Python
  • macOS, with Python
  • Linux, with Python
Start with
pip install -U huggingface_hub
hf download lixin4ever/VideoLLaMA2 --repo-type space --local-dir VideoLLaMA2
cd VideoLLaMA2

Platform

WindowsOperating system
macOSOperating system
LinuxOperating system

About

What it is

VideoLLaMA2 is a Gradio chat app for media understanding, meaning you give it something like a video and ask about it. It names two VideoLLaMA2 models, the 7B build and the 2.1 7B 16F build, along with two supporting models. The Space runs on Hugging Face, so you can try it in a browser with nothing to install.

Who it suits

Researchers and developers who want to try a video-language model, and anyone who wants a written answer about what a clip shows.

IndustryWho uses itHow they use itExample
MediaVideo editorsGet a written account of what a clip showsLoad a clip and ask what happens in it
ResearchMultimodal researchersTry a video-language model on their own clipsCompare answers from the two named builds
EducationTeachersAsk questions about a recorded lesson clipAsk what a clip teaches
SoftwareDevelopersStudy how a video chat demo is wiredRead app.py and the VideoLLaMA2 folder

Anyone who needs a ready business tool with a fixed workflow can skip it.

Where to use it

It runs in these places.

  • A web browser, on the Space's page at Hugging Face
  • Windows, with Python
  • macOS, with Python
  • Linux, with Python
Use caseWhoWhat they get back
Ask about a clipAnyoneA written answer about the media
Try the sample inputsNewcomersA quick demo from the examples folder
Study the codeDevelopersA local copy with the model code to read

How to set it up

Using the Space online needs only a browser. A copy on your own computer needs the following.

  • Python and pip
  • The huggingface_hub package, which gives you the hf command
  • Disk space for the repository, which holds 87 files
  1. Install the huggingface_hub package.
  2. Download the Space's files into a local folder.
  3. Move into that folder.
  4. Install Gradio at the version the Space uses, then install the packages in requirements.txt.
  5. Start the app.
pip install -U huggingface_hub
hf download lixin4ever/VideoLLaMA2 --repo-type space --local-dir VideoLLaMA2
cd VideoLLaMA2
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py

How to use it

Open the Space's page, or run the app on your computer and open the page Gradio shows. Give it a video or other media, type a question, and read the answer. The README is mostly template text, so the source does not describe the screens.

python app.py
ToolWhat it does
app.pyThe main file, it builds the Gradio page
VideoLLaMA2 folderHolds the model code in the repository
examples folderHolds sample inputs to try
requirements.txtLists the Python packages the app needs

Example

You open the Space, load a short video clip and type a question about what happens in it. The model replies with a written answer about the clip.

For newcomers and experts

A video-language model reads a video and answers questions in text. The first small thing to try is the online Space with one of the sample inputs.

The Space names four models, VideoLLaMA2-7B, VideoLLaMA2.1-7B-16F, opt-350m and vicuna-7b-v1.5. The hosted copy is set to run on Hugging Face hardware called zero-a10g. This page rests on file names and model names, because the README carries only a short tagline and template text.

  1. You give the app a video or other media
  2. You type a question
  3. A VideoLLaMA2 model reads the media
  4. The app replies with text

Good to know

The Space states no usage limits, so treat it as a demo you can read and adapt.

  • License: apache-2
  • Cost to run: none named
  • Data it reaches: the media you load, plus the Space files and model files that Hugging Face supplies
  • Hardware: the Space is set to zero-a10g at Hugging Face, and what your own computer needs is not stated

README and files

README

VideoLLaMA2

A chat app for understanding media such as video, built on the VideoLLaMA2 models. Runs in the browser as a Gradio app on ZeroGPU, for people who want to ask questions about clips.

Made by lixin4ever 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: VideoLLaMA2 is a Gradio chat app for media understanding, meaning you give it something like a video and ask about it. It names two VideoLLaMA2 models, the 7B build and the 2.1 7B 16F build, along with two supporting models. The Space runs on Hugging Face, so you can try it in a browser with nothing to install.

Who it suits: Researchers and developers who want to try a video-language model, and anyone who wants a written answer about what a clip shows.

Industry | Who uses it | How they use it | Example
Media | Video editors | Get a written account of what a clip shows | Load a clip and ask what happens in it
Research | Multimodal researchers | Try a video-language model on their own clips | Compare answers from the two named builds
Education | Teachers | Ask questions about a recorded lesson clip | Ask what a clip teaches
Software | Developers | Study how a video chat demo is wired | Read app.py and the VideoLLaMA2 folder

Anyone who needs a ready business tool with a fixed workflow can skip it.

Where to use it: It runs in these places.

  • A web browser, on the Space's page at Hugging Face
  • Windows, with Python
  • macOS, with Python
  • Linux, with Python
Use case | Who | What they get back
Ask about a clip | Anyone | A written answer about the media
Try the sample inputs | Newcomers | A quick demo from the examples folder
Study the code | Developers | A local copy with the model code to read

How to set it up: Using the Space online needs only a browser. A copy on your own computer needs the following.

  • Python and pip
  • The huggingface_hub package, which gives you the hf command
  • Disk space for the repository, which holds 87 files
  1. Install the huggingface_hub package.
  2. Download the Space's files into a local folder.
  3. Move into that folder.
  4. Install Gradio at the version the Space uses, then install the packages in requirements.txt.
  5. Start the app.
pip install -U huggingface_hub
hf download lixin4ever/VideoLLaMA2 --repo-type space --local-dir VideoLLaMA2
cd VideoLLaMA2
pip install gradio==5.49.1
pip install -r requirements.txt
python app.py

How to use it: Open the Space's page, or run the app on your computer and open the page Gradio shows. Give it a video or other media, type a question, and read the answer. The README is mostly template text, so the source does not describe the screens.

python app.py
Tool | What it does
app.py | The main file, it builds the Gradio page
VideoLLaMA2 folder | Holds the model code in the repository
examples folder | Holds sample inputs to try
requirements.txt | Lists the Python packages the app needs

Example: You open the Space, load a short video clip and type a question about what happens in it. The model replies with a written answer about the clip.

For newcomers and experts: A video-language model reads a video and answers questions in text. The first small thing to try is the online Space with one of the sample inputs.

The Space names four models, VideoLLaMA2-7B, VideoLLaMA2.1-7B-16F, opt-350m and vicuna-7b-v1.5. The hosted copy is set to run on Hugging Face hardware called zero-a10g. This page rests on file names and model names, because the README carries only a short tagline and template text.

You give the app a video or other media
You type a question
A VideoLLaMA2 model reads the media
The app replies with text

Good to know: The Space states no usage limits, so treat it as a demo you can read and adapt.

  • License: apache-2
  • Cost to run: none named
  • Data it reaches: the media you load, plus the Space files and model files that Hugging Face supplies
  • Hardware: the Space is set to zero-a10g at Hugging Face, and what your own computer needs is not stated

On Hugging Face, 13 November 2026

  • Likes: 162
  • 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
VideoLLaMA2 This page162gradioapache-2.0
Open VLM LeaderboardShares gradio1,034gradioapache-2.0
Face SwapShares gradio808gradiocc-by-nc-sa-4.0
TTS Spaces ArenaShares gradio493gradiozlib
Depth Anything 3Shares gradio490gradiocc-by-nc-4.0
BLIPShares gradio431gradiobsd-3-clause
Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13.

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