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wd-v1-4-moat-tagger-v2
XUly/wd-v1-4-moat-tagger-v2
wd-v1-4-moat-tagger-v2 is a machine learning model from XUly. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for tf-keras. The card lists the license as apache-2.0.
Supports ratings, characters and general tags.
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At a glance
- Library
- tf-keras
- License
- apache-2.0
- Access
- Public
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026
- SHA
- e1cc3156
Model card
From the Hugging Face model README
WD 1.4 MOAT Tagger V2
Supports ratings, characters and general tags.
Trained using https://github.com/SmilingWolf/SW-CV-ModelZoo.
TPUs used for training kindly provided by the TRC program.
Dataset
Last image id: 5944504
Trained on Danbooru images with IDs modulo 0000-0899.
Validated on images with IDs modulo 0950-0999.
Images with less than 10 general tags were filtered out.
Tags with less than 600 images were filtered out.
Validation results
P=R: threshold = 0.3771, F1 = 0.6911
Paper
MOAT: Alternating Mobile Convolution and Attention Brings Strong Vision Models
Final words
Subject to change and updates.
Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.
- Library
- tf-keras
- License
- apache-2.0
- Created
- Mar 28, 2026
- Updated
- Mar 28, 2026