App file

app.py

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+from huggingface_hub import from_pretrained_keras
+from keras_cv import models
+import gradio as gr
+
+from tensorflow import keras
+
+keras.mixed_precision.set_global_policy("mixed_float16")
+
+# prepare model
+resolution = 512
+sd_dreambooth_model = models.StableDiffusion(
+    img_width=resolution, img_height=resolution
+)
+db_diffusion_model = from_pretrained_keras("chimneyliu/dreambooth_diffusion_model")
+sd_dreambooth_model._diffusion_model = db_diffusion_model
+
+# generate images
+def infer(prompt):
+    generated_images = sd_dreambooth_model.text_to_image(
+        prompt, batch_size=2
+    )
+    return generated_images 
+    
+output = gr.Gallery(label="Outputs").style(grid=(1,2))
+
+# customize interface
+title = "Dreambooth Demo on Dog Images"
+description = "This is a dreambooth model fine-tuned on dog images. To try it, input the concept with {sks dog}."
+examples=[["sks dog in space"]]
+gr.Interface(infer, inputs=["text"], outputs=[output], title=title, description=description, examples=examples).launch()
+

requirements.txt

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+keras-cv
+tensorflow
+huggingface-hub