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("CompVis/stable-diffusion-v1-4", use_auth_token=YOUR_TOKEN) pipe.to(device) gallery = gr.Gallery(label="Generated images", show_label=False, elem_id="gallery").style(grid=[2], height="auto") def infer(prompt): #image = pipe(prompt, init_image=init_image)["sample"][0] images_list = pipe([prompt] * 4) images = [] safe_image = Image.open(r"unsafe.png") for i, image in enumerate(images_list["sample"]): 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="Stable Diffusion CPU" description="Stable Diffusion example using CPU and HF token.
Warning: Slow process... ~5/10 min inference time. NSFW filter enabled." gr.Interface(fn=infer, inputs="text", outputs=gallery,title=title,description=description).launch(enable_queue=True)