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import gradio as gr
from diffusers import StableDiffusion3Pipeline
import torch
import os
import psutil
pipe = StableDiffusion3Pipeline.from_pretrained(
"stabilityai/stable-diffusion-3.5-medium",
torch_dtype=torch.float16,
)
seed = None
if seed is None:
seed = int.from_bytes(os.urandom(2), "big")
print(f"Using seed: {seed}")
generator = torch.Generator(device=device).manual_seed(seed)
def generate_image(prompt):
with torch.device(device):
print(f"Current device: {torch.device(device)}")
image = pipe(
prompt=prompt,
height=(height := 512),
width=(width := 512),
num_inference_steps=28,
guidance_scale=7.0,
num_images_per_prompt=1,
generator=generator,
output_type="pil",
return_dict=True,
callback_on_step_end_tensor_inputs=["latents"],
).images[0]
return image
iface = gr.Interface(
fn=generate_image,
inputs="text",
outputs="image",
title="Stable Diffusion 3.5",
description="Enter a prompt to generate an image using Stable Diffusion 3.5."
)
iface.launch() |