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import gradio as gr
import torch
from diffusers import DiffusionPipeline
# Define the image generation function
def image_generation(prompt):
# Check if GPU is available
device = "cuda" if torch.cuda.is_available() else "cpu"
# Load the Stable Diffusion 2.1 pipeline (as you're using DiffusionPipeline now)
pipeline = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo",
torch_dtype=torch.float16 if device == "cuda" else torch.float32,
text_encoder_3=None,
tokenizer_3=None)
# Generate an image based on the prompt
image = pipeline(
prompt=prompt,
negative_prompt="blurred, ugly, watermark, low resolution, blurry",
num_inference_steps=1,
height=1024,
width=1024,
guidance_scale=9.0
).images[0]
return image
# Define the Gradio interface
interface = gr.Interface(
fn=image_generation,
inputs=gr.Textbox(lines=2, placeholder="Enter your Prompt..."),
outputs=gr.Image(type="pil"),
title="Image Creation using Stable Diffusion Model",
description="This application generates awesome images using the Stable Diffusion 3 model."
)
# Launch the Gradio app
interface.launch()
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