app.py

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

models=[
gr.Interface.load("Marvel","models/ItsJayQz/Marvel_WhatIf_Diffusion", "whatif style"), 
gr.Interface.load("Cyberpunk Anime Diffusion", "models/DGSpitzer/Cyberpunk-Anime-Diffusion", "dgs illustration style"),
gr.Interface.load("Portrait plus", "models/wavymulder/portraitplus", "portrait+ style"),
gr.Interface.load("classic Disney", "models/nitrosocke/classic-anim-diffusion", "classic disney style"),
gr.Interface.load("vintedois", "models/22h/vintedois-diffusion-v0-1", "vintedois style"),
gr.Interface.load("dreamlike", "models/dreamlike-art/dreamlike-diffusion-1.0","dreamlike style"),
gr.Interface.load("SD21","models/stabilityai/stable-diffusion-2-1", "sd21 default style")
]

def TextToImage(Prompt,model):
  model_id = model
  pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.get_default_dtype())
  pipe = pipe.to("cpu")
  prompt = Prompt
  image = pipe(prompt).images[0]
  return image

sandbox = gr.Interface(fn=TextToImage, 
                        inputs=["text", gr.Dropdown(models)],
                        outputs="image", 
                        title='AlStable Text to Image')

sandbox.launch()