app.py

import torch
from diffusers import StableDiffusionInstructPix2PixPipeline
import gradio as gr 
import PIL

cartoonization_id = "instruction-tuning-sd/cartoonizer"
image_proc_id = "instruction-tuning-sd/low-level-img-proc"

def load_pipeline(id: str):
    pipeline = StableDiffusionInstructPix2PixPipeline.from_pretrained(id, torch_dtype=torch.float16).to("cuda")
    return pipeline 


def infer(prompt: str, image: PIL.Image.Image, num_inference_steps:int, img_guidance_scale: float):
    pass