Instructions to use SmilingWolf/wd-v1-4-convnext-tagger-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use SmilingWolf/wd-v1-4-convnext-tagger-v2 with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("SmilingWolf/wd-v1-4-convnext-tagger-v2") - Notebooks
- Google Colab
- Kaggle
WD 1.4 ConvNext 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 = 0.3685, F1 = 0.6810
Final words
Subject to change and updates.
Downstream users are encouraged to use tagged releases rather than relying on the head of the repo.
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