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import gradio as gr
import torch
from diffusers import StableDiffusionPipeline
import os
# Retrieve the Hugging Face token stored in Hugging Face Spaces secrets
HUGGINGFACE_TOKEN = os.getenv("keyss")
if not HUGGINGFACE_TOKEN:
raise ValueError("Hugging Face token not found! Make sure it's added in Hugging Face Secrets.")
def image_generation(prompt):
# Check if GPU is available
device = "cuda" if torch.cuda.is_available() else "cpu"
# Load the Stable Diffusion 3 pipeline
pipeline = StableDiffusionPipeline.from_pretrained(
"stabilityai/stable-diffusion-3-medium-diffusers",
torch_dtype=torch.float16 if device == "cuda" else torch.float32,
use_auth_token=HUGGINGFACE_TOKEN, # Use the Hugging Face token for authentication
text_encoder_3=None,
tokenizer_3=None
)
# Enable efficient model execution
pipeline.enable_model_cpu_offload()
# Generate an image based on the prompt
image = pipeline(
prompt=prompt,
negative_prompt="blurred, ugly, watermark, low resolution, blurry",
num_inference_steps=40,
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 3 Model",
description="This application generates awesome images using the Stable Diffusion 3 model."
)
# Launch the Gradio app
interface.launch()
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