Update app.py

app.py

@@ -42,8 +42,8 @@ use_va = True
 models_dict = {
 #    "Juggernaut": "RunDiffusion/Juggernaut-XL-v8",
    "RealVision": "SG161222/RealVisXL_V4.0" ,
-#    "SDXL":"stabilityai/stable-diffusion-xl-base-1.0" ,
-   "Unstable": "stablediffusionapi/sdxl-unstable-diffusers-y"
+   "SDXL":"stabilityai/stable-diffusion-xl-base-1.0" ,
+#   "Unstable": "stablediffusionapi/sdxl-unstable-diffusers-y"
 }
 photomaker_path =  hf_hub_download(repo_id="TencentARC/PhotoMaker", filename="photomaker-v1.bin", repo_type="model")
 MAX_SEED = np.iinfo(np.int32).max
@@ -436,7 +436,7 @@ use_safetensors= False
 # pipe1.scheduler.set_timesteps(50)
 ### 
 pipe2 = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
-    models_dict["Unstable"], torch_dtype=torch.float16, use_safetensors=use_safetensors)
+    models_dict["RealVision"], torch_dtype=torch.float16, use_safetensors=use_safetensors)
 pipe2 = pipe2.to("cpu")
 pipe2.load_photomaker_adapter(
     os.path.dirname(photomaker_path),
@@ -449,7 +449,7 @@ pipe2.enable_freeu(s1=0.6, s2=0.4, b1=1.1, b2=1.2)
 pipe2.fuse_lora()
 
 pipe4 = PhotoMakerStableDiffusionXLPipeline.from_pretrained(
-    models_dict["RealVision"], torch_dtype=torch.float16, use_safetensors=True)
+    models_dict["SDXL"], torch_dtype=torch.float16, use_safetensors=True)
 pipe4 = pipe4.to("cpu")
 pipe4.load_photomaker_adapter(
     os.path.dirname(photomaker_path),