DBv4-Tagger ConvNext-v2-Huge

DBv4-Tagger ConvNext-v2-Huge

Tags anime images with the animetimm convnextv2_huge model, in a Gradio page. For people who organize or study anime artwork.

Made by DraconicDragon 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 is a Gradio image tagger for anime pictures. It uses the animetimm convnextv2_huge model, and it also names a PixAI tagger in ONNX form. A helper file in the repository, fetch_url_util.py, suggests it can fetch an image from a link. It runs on the basic CPU tier at Hugging Face.

Who it suits: People who sort or study anime artwork and want tags for a picture, and developers who want a small example of an image tagger in Gradio.

Industry | Who uses it | How they use it | Example
Digital art | Collectors and archivists | Get tags for pictures to help sort a collection | Tag a picture before filing it
Research | Dataset builders | Try a tagging model on sample images | Compare tags on several pictures
Software | Developers | Read app.py and the fetch helper to see how images are loaded | Reuse the layout for another tagger

Skip it if your images are not anime art, since the model is built for that style.

Where to use it:

• A web browser, on the Space's page at Hugging Face
• Your own computer, as a local copy, once Python 3.13 is installed

Use case | Who | What they get back
Tag an anime picture | Archivists and fans | A list of tags for the image
Study the setup | Developers | A short Gradio app with a tagging model

How to set it up:

• Nothing at all if you only use the online Space
• Python 3.13 and pip, for a local copy
• The Python packages listed in requirements.txt

1. Open the Space's page at Hugging Face to use it online.
2. For a local copy, install the Hugging Face hub package and download the Space.
3. Move into the new folder and install Gradio at the pinned version.
4. Install the packages from requirements.txt.
5. Start the app with Python.

pip install -U huggingface_hub
pip install gradio==6.29.1
pip install -r requirements.txt
python app.py

Put your own value in its key setting first.

The repository is small, with an app file, a link helper and a requirements file. The page does not say what a local run needs beyond the packages.

How to use it: Online, open the Space and give it an image through the form on its page. On your own machine, run the app file and open the page Gradio serves in your browser. The page lists no other commands.

Tool | What it does
python app.py | Starts the Gradio app on your computer

Example: You upload an anime illustration and run the tagger. The app returns tags for what it recognizes in the picture, and you use them to label or sort the file in your collection.

For newcomers and experts: If you are new, open the Space online and try one picture. Treat the tags as suggestions and glance over them before you rely on them.

If you know the field, the page names a ConvNeXt V2 Huge model from animetimm and a PixAI tagger in ONNX form. It gives no score thresholds, tag lists or accuracy figures, so check the model pages for those.

Open the Space in a browser
Add an image
The tagging model scans the picture
A list of tags is shown

Good to know:

• License: mit
• Cost to run: none named, and the Space sits on the basic CPU tier at Hugging Face
• Data it reaches: the images you give it, and the model files from Hugging Face
• Not for: photos or other non-anime images, since the model is built for anime art

On Hugging Face, 13 November 2026

• Likes: 6
• Built with: gradio
• License: mit

Links

• Space: https://huggingface.co/spaces/DraconicDragon/DBv4-Tagger_ConvNext-v2-Huge
• Files: https://huggingface.co/spaces/DraconicDragon/DBv4-Tagger_ConvNext-v2-Huge/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.