app.py

import gradio as gr
#import torch
#from torch import autocast // only for GPU

from PIL import Image

import os
MY_SECRET_TOKEN=os.environ.get('HF_TOKEN_SD')

from diffusers import StableDiffusionPipeline
#from diffusers import StableDiffusionImg2ImgPipeline

print("hello sylvain")

YOUR_TOKEN=MY_SECRET_TOKEN

device="cpu"

pipe = StableDiffusionPipeline.from_pretrained("Yntec/YiffyPixar", use_auth_token=YOUR_TOKEN)
pipe.to(device)

gallery = gr.Gallery(label="Generated image", show_label=False, elem_id="gallery").style(grid=[2], height="auto")

def infer(prompt, steps=21): 
    
    #image = pipe(prompt, init_image=init_image)["sample"][0]
    images_list = pipe([prompt], num_inference_steps=steps)
    images = []
    safe_image = Image.open(r"unsafe.png")
    for i, image in enumerate(images_list["images"]):
        if(images_list["nsfw_content_detected"][i]):
            images.append(safe_image)
        else:
            images.append(image)
    
    return images

print("Great sylvain ! Everything is working fine !")

title="YiffyPixar"
description="It takes about 600 seconds to generate an image per user. If you like this model, you can like it at its original page! https://huggingface.co/Yntec/YiffyPixar" 

gr.Interface(fn=infer, inputs=["text", 
                               gr.Slider(20, 21, value = 21, step = 1, label = 'Steps', visible = False)], outputs=gallery,title=title,description=description).queue(max_size=10).launch(enable_queue=True)