diff.py

import gradio as gr

from diffusers import StableDiffusionPipeline
import torch

model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda")

def notation_2_note(input_text):
    image = pipe(input_text).images[0]  
    return image

demo = gr.Interface(notation_2_note, "text", gr.Image())
demo.launch()

# No. Too much memory required