app.py

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

fseed=random.random()
model="models/nan2/lcbanner"

def TextToImage(Prompt,model):
  model_id = model
  pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
  pipe = pipe.to("cpu")

  prompt = Prompt
  image = pipe(prompt).images[0]

  return image



interface = gr.Interface(fn=TextToImage, 
                        inputs=["text", "nan2/lcbanner"],
                         outputs="image", 
                        title='Text to Image')

interface.launch()

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