OVStableDiffusionXLPipeline

app.py

@@ -2,7 +2,7 @@ import gradio as gr
 import modin.pandas as pd
 import torch
 import time
-
+from optimum.intel import OVStableDiffusionXLPipeline
 import numpy as np
 from PIL import Image
 from diffusers import AutoPipelineForImage2Image
@@ -13,7 +13,7 @@ from DeepCache import DeepCacheSDHelper
 adapter_id = "latent-consistency/lcm-lora-sdv1-5"
 
 device = "cuda" if torch.cuda.is_available() else "cpu"
-pipe = AutoPipelineForImage2Image.from_pretrained("Lykon/dreamshaper-xl-v2-turbo", torch_dtype=torch.float16) if torch.cuda.is_available() else AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo")
+pipe = OVStableDiffusionXLPipeline.from_pretrained("Lykon/dreamshaper-xl-v2-turbo", torch_dtype=torch.float16, export=True) if torch.cuda.is_available() else AutoPipelineForImage2Image.from_pretrained("stabilityai/sdxl-turbo")
 pipe = pipe.to(device)
 # helper = DeepCacheSDHelper(pipe=pipe)
 # helper.set_params(
@@ -21,6 +21,8 @@ pipe = pipe.to(device)
 #     cache_branch_id=0,
 # )
 # helper.enable()
+pipe.compile()
+
 def resize(value,img):
     img = Image.open(img)
     img = img.resize((value,value))