SmilingWolf/wd-v1-4-swinv2-tagger-v2

🤗 Hugging Face 来源apache-2.096M 参数385 MBsafetensors✓ 7 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo SmilingWolf/wd-v1-4-swinv2-tagger-v2 ./model-folder
需要做种者 →

WD 1.4 SwinV2 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

v2.0: P=R: threshold = 0.3771, F1 = 0.6854

What's new

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.

Runtime deps

ONNX model requires onnxruntime >= 1.17.0

Final words

Subject to change and updates.
Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.