app.py

import os
os.system("pip install diffusers torch transformers accelerate gradio")

import gradio as gr
from diffusers import StableDiffusionPipeline

# Load the Stable Diffusion model
model = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")

def generate_image(prompt):
    # Generate an image based on the prompt
    image = model(prompt).images[0]
    return image

# Create a Gradio interface
interface = gr.Interface(
    fn=generate_image,
    inputs="text",
    outputs="image",
    title="AI Image Generator",
    description="Enter a prompt to generate an image using Stable Diffusion."
)

# Launch the interface
if __name__ == "__main__":
    interface.launch()
model = StableDiffusionPipeline.from_pretrained("SG161222/Realistic_Vision_V4.0")

import torch
from diffusers import StableDiffusionPipeline

model = StableDiffusionPipeline.from_pretrained("SG161222/Realistic_Vision_V4.0").to("cuda")
model.unet = torch.compile(model.unet)  # Speeds up inference

def generate_image(prompt):
    image = model(prompt).images[0]
    return image