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SmilingWolf/wd-v1-4-swinv2-tagger-v2
wd-v1-4-swinv2-tagger-v2 is a machine learning model from SmilingWolf. 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.
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.onnx455 MB · 27%
From the Hugging Face model README
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.
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.
v2.0: P=R: threshold = 0.3771, F1 = 0.6854
Model v2.1/Dataset v2:
Re-exported to work around an ONNXRuntime v1.17.1 bug.
Bumped the minimum ONNXRuntime version to >= 1.17.0.
Now timm compatible! Load it up and give it a spin using the canonical one-liner!
Exported to msgpack for compatibility with the JAX-CV codebase.
The batch dimension of the ONNX model is not fixed to 1 anymore. Now you can go crazy with batch inference.
No change to the trained weights themselves. There might be small prediction discrepancies across frameworks due to implementation details.
Model v2.0/Dataset v2:
Initial release.
ONNX model requires onnxruntime >= 1.17.0
Subject to change and updates.
Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.