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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 | |
sd_dreambooth_model = models.StableDiffusion( | |
img_width=512, img_height=512 | |
) | |
db_diffusion_model = from_pretrained_keras("Jayabalambika/my_repo") | |
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 mobile phone Images" | |
description = "This is a dreambooth model fine-tuned on mobile phone images. To try it, input the concept with {mobile phones}." | |
examples=[["a photo of mobile phone in outer space"]] | |
gr.Interface(infer, inputs=["text"], outputs=[output], title=title, description=description, examples=examples).queue().launch() |