Instructions to use usbmd/taesdxl with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use usbmd/taesdxl 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("usbmd/taesdxl") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 691ba352203e7ff7fe1ee660b41ff1c224ded638f7819cdcf1c19cdd46d943fa
- Size of remote file:
- 5.11 MB
- SHA256:
- ed311b5dff821be8ac415d781bfaf25ed7a179585d921e3e1dfa3743acfe6a18
·
Xet efficiently stores Large Files inside Git, intelligently splitting files into unique chunks and accelerating uploads and downloads. More info.