Bonsai-27B-GGUF
lmstudio-community · Kit
A GGUF conversion of the 27B Bonsai model for LM Studio, with a 3.80 GB Q1_0 language file and a 0.93 GB BF16 vision projector. Tested for text, vision and par…
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.
pip install -U huggingface_hub hf download lixin4ever/VideoLLaMA2 --repo-type space --local-dir VideoLLaMA2 cd VideoLLaMA2
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.
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.
It runs in these places.
| 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 |
Using the Space online needs only a browser. A copy on your own computer needs the following.
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
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 |
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.
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.
The Space states no usage limits, so treat it as a demo you can read and adapt.
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.
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.
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.
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.
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.
README.md 4 KB
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 | |
| Open VLM LeaderboardShares gradio | 1,034 | gradio | apache-2.0 | |
| Face SwapShares gradio | 808 | gradio | cc-by-nc-sa-4.0 | |
| TTS Spaces ArenaShares gradio | 493 | gradio | zlib | |
| Depth Anything 3Shares gradio | 490 | gradio | cc-by-nc-4.0 | |
| BLIPShares gradio | 431 | gradio | bsd-3-clause |
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