Instructions to use kailashsp/dreambooth_diffusion_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Keras
How to use kailashsp/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://kailashsp/dreambooth_diffusion_model") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 8f1ea5dd9019131a234ad931bc7872acd1d017455a3302d73210a45bcaa0fa72
- Size of remote file:
- 20.8 MB
- SHA256:
- 2467f113e34ced491554e2ffb970d564d9cff4b138a62290007941ce36ba3403
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