Create app.py

app.py

@@ -0,0 +1,15 @@
+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