app.py

import gradio as gr
from diffusers import StableDiffusionPipeline,DDIMScheduler
import torch

# Load the model
model_id = "s3nh/artwork-arcane-stable-diffusion"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
if pipe.scheduler is not None:
    pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config)
else:
    pipe.scheduler = DDIMScheduler(beta_start=0.00085, beta_end=0.012, beta_schedule="scaled_linear", clip_sample=False, set_alpha_to_one=True)
# Define the image generation function
def generate_image(prompt):
    

    image = pipe(prompt, num_inference_steps=30).images[0]
    return image

# Create the Gradio interface
interface = gr.Interface(
    fn=generate_image,
    inputs=gr.Textbox(label="Enter your prompt"),
    outputs=gr.Image(label="Generated Image"),
    title="Image Generator",
    description="Enter a prompt to generate an image using Stable Diffusion."
)

# Launch the interface
interface.launch()