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from diffusers import StableDiffusionImg2ImgPipeline
import torch
import gradio as gr
def get_model():
pipe = StableDiffusionImg2ImgPipeline.from_pretrained("stabilityai/sdxl-turbo", variant="fp16")
pipe.to("cpu")
pipe.enable_model_cpu_offload()
return pipe
model = get_model()
def return_image(text,inf_steps,gScale):
image = model(prompt=text, num_inference_steps=inf_steps, guidance_scale=gScale).images[0]
return image
piece = gr.Interface(
return_image,
[
gr.Textbox(label = "Enter a prompt to describe the image you want to be generated!",placeholder = "A cinematic shot of a baby racoon wearing an intricate italian priest robe"),
gr.Slider(minimum = 1, maximum = 50, step = 1,label = "number of inference steps"),
gr.Slider(minimum = 0, maximum = 1, step = 0.1, label = "guidance scale"),
],
outputs = [gr.Image(label = "Image Output")],
title = "Stable Diffusion XL Turbo Model Demo"
)
piece.launch() |