app.py

import gradio as gr
import torch
from torch import autocast
from diffusers import StableDiffusionPipeline

#model_id = "hakurei/waifu-diffusion"
pipe = StableDiffusionPipeline.from_pretrained("hakurei/waifu-diffusion", torch_type=torch.float16, revision="fp16")
pipe = pipe.to("cuda")
#torch.backends.cudnn.benchmark = True
num_samples = 2

def infer(prompt):
    images = pipe([prompt] * num_samples, guidance_scale=7.5)["sample"]
    return images

block = gr.Blocks()

gr.Interface.load("models/nan2/lcbanner").launch()