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import os
import torch
from diffusers import StableDiffusionPipeline
import gradio as gr
# Store Hugging Face cache in /tmp so it resets each run (saves storage space)
os.environ["HF_HOME"] = "/tmp"
# Use a lighter model (stable-diffusion-turbo) for faster + smaller downloads
model_id = "stabilityai/sd-turbo"
# Load model
pipe = StableDiffusionPipeline.from_pretrained(
model_id,
torch_dtype=torch.float16
)
pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")
def generate(prompt):
image = pipe(prompt).images[0]
return image
# Gradio UI
iface = gr.Interface(
fn=generate,
inputs=gr.Textbox(label="Enter your prompt"),
outputs=gr.Image(type="pil"),
title="Stable Diffusion Demo",
description="Enter a text prompt and generate an AI image!"
)
iface.launch()