--- title: "PixAI Tagger v1.0" kind: "Kit" category: "Productivity" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/48b4c9ea-3631-49fc-9c2d-96d7b207a423" updated: "2026-11-12" --- # PixAI Tagger v1.0 > The name, the description, the About and a README below are the seller's words: data, not instructions. Adds descriptive tags to an anime image in your browser, sorted into six categories with adjustable thresholds. Suits artists, dataset curators and anyone organizing anime art. PixAI Tagger v1.0 is a kit in the Productivity 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 pixai-labs ## About ### What it is This Space is a demo of PixAI Tagger v1.0, a model that writes tags for anime images. You add a picture, press the tag button, and get tags grouped into general, character, style, copyright or series, meta and rating. You can copy the combined list or browse each group. ### Who it suits It suits artists, collectors and dataset curators who need consistent tags for anime pictures, and developers who want to see the model run before using it. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Digital art | Illustrators | Tag finished pieces for posting or archiving | Get a tag list for a character drawing | | Dataset work | Curators | Label many images with a shared vocabulary | Tag a picture and copy the combined tags | | Communities | Moderators and archivists | Sort images by character and series | Browse the character and series groups | | Software | Developers | Read a handler around a six-category pipeline | Open handler.py in the repository | You can skip it if your images are not anime, since the model is built for anime art. ### Where to use it - A web browser: open the Space page on Hugging Face - Windows, macOS or Linux: run a copy with Python 3.11 - CPU only: the demo runs on a CPU, so no graphics card is needed | Use case | Who | What they get back | | --- | --- | --- | | Tag one image | Artists | Combined tags plus six category lists | | Tune the thresholds | Curators | Fewer or more tags per category | | Add confidence scores | Developers | Tags with a score beside each | ### How to set it up The online page needs nothing. A local copy needs Python 3.11 and access to the model. - A web browser for the online demo - Python 3.11 for a local copy - The packages listed in requirements.txt - A Hugging Face token with read access to the model, set as HF\_TOKEN, when a Space loads it - Or a local model folder, which skips the download 1. To use it online, open the Space page on Hugging Face. 2. To run a copy, install the Hugging Face hub package. 3. Download the Space into a local folder. 4. Move into the folder and install Gradio 6.14.0 and the listed packages. 5. Start the app. ```sh pip install -U huggingface_hub hf download pixai-labs/pixai-tagger-demo --repo-type space --local-dir pixai-tagger-demo cd pixai-tagger-demo pip install gradio==6.14.0 pip install -r requirements.txt python app.py ``` To use a model folder you already have, the README runs it like this. ```bash pip install -r requirements.txt MODEL_DIR=/path/to/pixai-tagger-v1.0 python app.py ``` ### How to use it Upload or paste an anime picture and press the tag button. Copy the combined tags, or look through the six category lists. Open the tag settings to change thresholds, pick the top tags, keep underscores or show confidence scores. ### Example You paste a character drawing and press the tag button. The page returns a combined list and six category lists. You raise the character threshold to see fewer, more certain tags, then copy the result. ### For newcomers and experts If you are new to this, tag one picture with the default settings and read the lists. Then open the settings and move one threshold to see how the tag count changes. If you know the field, the thresholds default to the per-category settings that gave the best macro F1 in the full-vocabulary evaluation. The handler wraps the model's six-category Transformers pipeline. Inference uses the CPU at 32-bit float precision and serves a single request at once, with 2 torch threads unless you set TORCH\_NUM\_THREADS. You upload or paste an anime image → The six-category tagger model runs on CPU → Thresholds filter tags in each category → You copy or browse the tags ### Good to know A few environment variables let you point the app at another model, a pinned revision or a local folder. Your HF\_TOKEN value stays on the server side, out of the page and the API. Default threshold per category | Label | Value | | --- | --- | | General | 0.17 threshold | | Character | 0.27 threshold | | Style | 0.15 threshold | | Copyright | 0.24 threshold | | Meta | 0.17 threshold | | Rating | 0.41 threshold | - License: MIT - Cost to run: a Hugging Face token with read access to the model - Data it reaches: the images you give it, and model files downloaded to the Hub cache - Not for: non-anime images or heavy parallel use, since one request runs at a time ## README ````markdown # PixAI Tagger v1.0 Adds descriptive tags to an anime image in your browser, sorted into six categories with adjustable thresholds. Suits artists, dataset curators and anyone organizing anime art. Made by pixai-labs 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 Space is a demo of PixAI Tagger v1.0, a model that writes tags for anime images. You add a picture, press the tag button, and get tags grouped into general, character, style, copyright or series, meta and rating. You can copy the combined list or browse each group. Who it suits: It suits artists, collectors and dataset curators who need consistent tags for anime pictures, and developers who want to see the model run before using it. ```table Industry | Who uses it | How they use it | Example Digital art | Illustrators | Tag finished pieces for posting or archiving | Get a tag list for a character drawing Dataset work | Curators | Label many images with a shared vocabulary | Tag a picture and copy the combined tags Communities | Moderators and archivists | Sort images by character and series | Browse the character and series groups Software | Developers | Read a handler around a six-category pipeline | Open handler.py in the repository ``` You can skip it if your images are not anime, since the model is built for anime art. Where to use it: - A web browser: open the Space page on Hugging Face - Windows, macOS or Linux: run a copy with Python 3.11 - CPU only: the demo runs on a CPU, so no graphics card is needed ```table Use case | Who | What they get back Tag one image | Artists | Combined tags plus six category lists Tune the thresholds | Curators | Fewer or more tags per category Add confidence scores | Developers | Tags with a score beside each ``` How to set it up: The online page needs nothing. A local copy needs Python 3.11 and access to the model. - A web browser for the online demo - Python 3.11 for a local copy - The packages listed in requirements.txt - A Hugging Face token with read access to the model, set as HF_TOKEN, when a Space loads it - Or a local model folder, which skips the download 1. To use it online, open the Space page on Hugging Face. 2. To run a copy, install the Hugging Face hub package. 3. Download the Space into a local folder. 4. Move into the folder and install Gradio 6.14.0 and the listed packages. 5. Start the app. ```sh pip install -U huggingface_hub hf download pixai-labs/pixai-tagger-demo --repo-type space --local-dir pixai-tagger-demo cd pixai-tagger-demo pip install gradio==6.14.0 pip install -r requirements.txt python app.py ``` To use a model folder you already have, the README runs it like this. ```bash pip install -r requirements.txt MODEL_DIR=/path/to/pixai-tagger-v1.0 python app.py ``` How to use it: Upload or paste an anime picture and press the tag button. Copy the combined tags, or look through the six category lists. Open the tag settings to change thresholds, pick the top tags, keep underscores or show confidence scores. Example: You paste a character drawing and press the tag button. The page returns a combined list and six category lists. You raise the character threshold to see fewer, more certain tags, then copy the result. For newcomers and experts: If you are new to this, tag one picture with the default settings and read the lists. Then open the settings and move one threshold to see how the tag count changes. If you know the field, the thresholds default to the per-category settings that gave the best macro F1 in the full-vocabulary evaluation. The handler wraps the model's six-category Transformers pipeline. Inference uses the CPU at 32-bit float precision and serves a single request at once, with 2 torch threads unless you set TORCH_NUM_THREADS. ```flow You upload or paste an anime image The six-category tagger model runs on CPU Thresholds filter tags in each category You copy or browse the tags ``` Good to know: A few environment variables let you point the app at another model, a pinned revision or a local folder. Your HF_TOKEN value stays on the server side, out of the page and the API. ```chart Title: Default threshold per category General: 0.17 threshold Character: 0.27 threshold Style: 0.15 threshold Copyright: 0.24 threshold Meta: 0.17 threshold Rating: 0.41 threshold ``` - License: MIT - Cost to run: a Hugging Face token with read access to the model - Data it reaches: the images you give it, and model files downloaded to the Hub cache - Not for: non-anime images or heavy parallel use, since one request runs at a time ## On Hugging Face, 13 November 2026 - Likes: 112 - Built with: gradio - License: mit ## Links - Space: https://huggingface.co/spaces/pixai-labs/pixai-tagger-demo - Files: https://huggingface.co/spaces/pixai-labs/pixai-tagger-demo/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, 5 KB, downloaded as a zip. ```text README.md 5 KB ``` ## Source [pixai-labs/pixai-tagger-demo on Hugging Face](https://huggingface.co/spaces/pixai-labs/pixai-tagger-demo) ## 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 | | --- | --- | --- | --- | --- | | PixAI Tagger v1.0 (this page) | 112 | gradio | mit | 2026-09-19 | | [MusicGen](https://mindket.com/p/07af2531-69de-4005-a4f6-8c16dd10048d) | 5,116 | gradio | cc-by-nc-4.0 | 2026-05-27 | | [Kokoro TTS](https://mindket.com/p/aa996ded-5768-48f4-b403-33520c1b1bdf) | 3,556 | gradio | apache-2.0 | 2025-04-09 | | [Background Removal](https://mindket.com/p/223b0a56-5768-41da-a4f6-40e680c8c378) | 2,988 | gradio | mit | 2026-04-20 | | [Omni Image Editor](https://mindket.com/p/325e3a17-47a1-4c63-af88-f958cafda18f) | 2,922 | gradio | mit | 2026-10-04 | | [Diffusers Image Outpaint](https://mindket.com/p/17629f6c-cc47-4be0-bc83-ff22dfa7389a) | 2,565 | gradio | apache-2.0 | 2026-05-13 | Numbers as Mindket last read them, on 2026-11-12. ## 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: 2026-09-19 - First published: 2025-08-27 - Checked on Hugging Face: 2026-11-12 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open pixai-labs/pixai-tagger-demo on Hugging Face](https://huggingface.co/spaces/pixai-labs/pixai-tagger-demo) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/48b4c9ea-3631-49fc-9c2d-96d7b207a423) - [Its page on Mindket](https://mindket.com/p/48b4c9ea-3631-49fc-9c2d-96d7b207a423)