app.py

import torch
import gradio as gr
from diffusers import StableDiffusionPipeline


class CFG:
    device = "cpu"
    seed = 42
    generator = torch.Generator(device).manual_seed(seed)
    image_gen_steps = 35
    image_gen_model_id = "stabilityai/stable-diffusion-2"
    image_gen_size = (400, 400)
    image_gen_guidance_scale = 9

image_gen_model = StableDiffusionPipeline.from_pretrained(
    CFG.image_gen_model_id, torch_dtype=torch.float32,
    revision="fp16", use_auth_token='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', guidance_scale=9
)
apply = image_gen_model.to(CFG.device)

def generate_image(prompt):
    image = apply(
        prompt, num_inference_steps=CFG.image_gen_steps,
        generator=CFG.generator,
        guidance_scale=CFG.image_gen_guidance_scale
    ).images[0]
    image = image.resize(CFG.image_gen_size)
    return image


title = "Stable Diffusion Image Generator"
description = "Enter a prompt to generate an image using the Stable Diffusion model."

iface = gr.Interface(fn=generate_image, inputs="text", outputs="image", title=title, description=description)
iface.launch()