app.py

import torch
from diffusers import DiffusionPipeline
import gradio as gr

# Load SDXL base (no refiner)
model_id = "stabilityai/stable-diffusion-xl-base-1.0"
pipe = DiffusionPipeline.from_pretrained(
    model_id,
    torch_dtype=torch.float32,  # use .float32 for CPU
    use_safetensors=True,
)
pipe.enable_model_cpu_offload()  # works on both CPU or small GPU

def generate(prompt):
    image = pipe(prompt, num_inference_steps=25, guidance_scale=7.5).images[0]
    return image

gr.Interface(
    fn=generate,
    inputs=gr.Textbox(label="Prompt", placeholder="Describe your image..."),
    outputs="image",
    title="SDXL 1.0 Base Generator",
    description="CPU/GPU friendly Stable Diffusion XL Base demo.",
).launch()