Instructions to use keras/stable_diffusion_3.5_large_turbo with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- KerasHub
How to use keras/stable_diffusion_3.5_large_turbo with KerasHub:
import keras_hub # Load TextToImage model (optional: use half precision for inference) text_to_image = keras_hub.models.TextToImage.from_preset("hf://keras/stable_diffusion_3.5_large_turbo", dtype="bfloat16") # Generate images with a TextToImage model. text_to_image.generate("Astronaut in a jungle")import keras_hub # Create a ImageToImage model task = keras_hub.models.ImageToImage.from_preset("hf://keras/stable_diffusion_3.5_large_turbo")import keras_hub # Create a Inpaint model task = keras_hub.models.Inpaint.from_preset("hf://keras/stable_diffusion_3.5_large_turbo")import keras_hub # Create a Backbone model unspecialized for any task backbone = keras_hub.models.Backbone.from_preset("hf://keras/stable_diffusion_3.5_large_turbo") - Keras
How to use keras/stable_diffusion_3.5_large_turbo with Keras:
# !pip install -U keras tensorflow huggingface_hub # Keras needs TensorFlow installed to read "hf://" paths, so the tensorflow backend is selected here; # "jax" and "torch" also work for computation once TensorFlow is installed. import os os.environ["KERAS_BACKEND"] = "tensorflow" import keras model = keras.saving.load_model("hf://keras/stable_diffusion_3.5_large_turbo") - Notebooks
- Google Colab
- Kaggle
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