Instructions to use SmilingWolf/wd-v1-4-moat-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-moat-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-moat-tagger-v2") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- c4473547c0f8f6df0826929a09a4a8b795afc5cc1341640b82588ac342d6f99c
- Size of remote file:
- 326 MB
- SHA256:
- b8cef913be4c9e8d93f9f903e74271416502ce0b4b04df0ff1e2f00df488aa03
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.