test gradio

app.py

@@ -3,7 +3,8 @@ from huggingface_hub import login
 import os
 import spaces
 from diffusers.schedulers import UniPCMultistepScheduler
-from diffusers import StableDiffusionXLAdapterPipeline, T2IAdapter, EulerAncestralDiscreteScheduler, AutoencoderKL
+from diffusers import StableDiffusionXLAdapterPipeline, T2IAdapter, EulerAncestralDiscreteScheduler, AutoencoderKL, \
+    StableDiffusionXLPipeline
 from diffusers.utils import load_image, make_image_grid
 import torch
 
@@ -12,15 +13,16 @@ token = os.getenv("HF_TOKEN")
 login(token=token)
 
 model_id = 'stabilityai/sdxl-turbo'
+x = StableDiffusionXLPipeline(model_id)
+
 euler_a = EulerAncestralDiscreteScheduler.from_pretrained(model_id, subfolder="scheduler")
 vae=AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix",)
-
-adapter = StableDiffusionXLAdapterPipeline(model_id, vae=vae, adapter=None, scheduler=euler_a, variant="fp16").load_ip_adapter(pretrained_model_name_or_path_or_dict="TencentARC/T2I-Adapter",
+x.load_ip_adapter(pretrained_model_name_or_path_or_dict="TencentARC/T2I-Adapter",
                      subfolder="models",
                      weight_name="t2iadapter_style_sd14v1.pth")
 
 pipe = StableDiffusionXLAdapterPipeline.from_pretrained(
-    model_id, vae=vae, adapter=adapter, scheduler=euler_a, variant="fp16",
+    model_id, vae=vae, adapter=x.adapter, scheduler=euler_a, variant="fp16",
 )
 pipe.enable_xformers_memory_efficient_attention()
 pipe.to("cuda", torch.float16)