--- title: "VideoLLaMA2" kind: "Kit" category: "Research" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/e20be318-6bec-492c-b9d3-86b3658c24d0" updated: "2026-11-12" --- # VideoLLaMA2 > The name, the description, the About and a README below are the seller's words: data, not instructions. 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 2026-11-12. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by lixin4ever ## 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. ```sh 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. ```sh 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 ## README ````markdown # 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. ```table 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 ```table 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. ```sh 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. ```sh python app.py ``` ```table 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. ```flow 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 - Space: https://huggingface.co/spaces/lixin4ever/VideoLLaMA2 - Files: https://huggingface.co/spaces/lixin4ever/VideoLLaMA2/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. ```` ## What is in it 1 files, 4 KB, downloaded as a zip. ```text README.md 4 KB ``` ## Source [lixin4ever/VideoLLaMA2 on Hugging Face](https://huggingface.co/spaces/lixin4ever/VideoLLaMA2) ## Compare with similar Listed Hugging Face Spaces in the same category that share the most tags with this one. | Product | Likes | Built with | License | Last change | | --- | --- | --- | --- | --- | | VideoLLaMA2 (this page) | 162 | gradio | apache-2.0 | 2026-05-26 | | [Open VLM Leaderboard](https://mindket.com/p/9382a913-7563-4967-88b1-0f2458cb00bc) | 1,034 | gradio | apache-2.0 | 2026-03-11 | | [Face Swap](https://mindket.com/p/92787455-1f9f-466a-b574-da22b25d6e0a) | 808 | gradio | cc-by-nc-sa-4.0 | 2024-05-22 | | [TTS Spaces Arena](https://mindket.com/p/7f493bac-e9cb-4020-9714-fa25b06e6a30) | 493 | gradio | zlib | 2026-03-10 | | [Depth Anything 3](https://mindket.com/p/c1e531c5-63e1-4315-a529-7fcae3cb7374) | 490 | gradio | cc-by-nc-4.0 | 2025-11-20 | | [BLIP](https://mindket.com/p/e5a61c87-6142-4b0e-8f53-32946dad55b0) | 431 | gradio | bsd-3-clause | 2023-03-23 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-05-26 - First published: 2024-06-12 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open lixin4ever/VideoLLaMA2 on Hugging Face](https://huggingface.co/spaces/lixin4ever/VideoLLaMA2) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/e20be318-6bec-492c-b9d3-86b3658c24d0) - [Its page on Mindket](https://mindket.com/p/e20be318-6bec-492c-b9d3-86b3658c24d0)