Instructions to use kfahn/dreambooth_diffusion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kfahn/dreambooth_diffusion_model with Keras:
# Available backend options are: "jax", "torch", "tensorflow". import os os.environ["KERAS_BACKEND"] = "jax" import keras model = keras.saving.load_model("hf://kfahn/dreambooth_diffusion_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 04291d0da3dcc98bb54e92c5c88e8f049486278ad121aa1509042b3794b31d4d
- Size of remote file:
- 20.8 MB
- SHA256:
- 6b995624a9a30ae7b9ae966451d69ca99370a570cc877b1aff7b6f72d1ab9bf2
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