Create initial app

app.py

@@ -0,0 +1,29 @@
+from huggingface_hub import from_pretrained_keras
+from keras_cv import models
+import gradio as gr
+
+sd_dreambooth_model = models.StableDiffusion(
+    img_width=512, img_height=512
+)
+db_diffusion_model = from_pretrained_keras("bharat-raghunathan/dreambooth_dosa")
+sd_dreambooth_model._diffusion_model = db_diffusion_model
+gr.HTML("<h2 style=\"font-size: 2em; font-weight: bold\" align=\"center\">Keras Dreambooth - The Humble Dosa</h2>")
+gr.HTML("<p style=\"font-size: 14; font-weight: normal\" align=\"left\">This model has been fine-tuned to learn the concept of a dosa.")
+# generate images
+def infer(prompt):
+    generated_images = sd_dreambooth_model.text_to_image(
+        prompt
+    )
+    return generated_images 
+    
+
+output = gr.Gallery(label="Outputs").style(grid=(2,2))
+
+gr.Examples(["realistic picture of a man eating a dosa",
+             "realistic picture of a dosa on a plate",
+             "realistic picture of a dosa in a restaurant"
+            ],
+            prompt, gallery, generate_images, cache_examples=True)
+gr.Markdown('Demo created by [Bharat Raghunathan](https://huggingface.co/bharat-raghunathan/)')
+# pass function, input type for prompt, the output for multiple images
+gr.Interface(infer, inputs=["text"], outputs=[output]).launch()