Update app.py

app.py

@@ -28,12 +28,12 @@ login(HF_TOKEN)
 # model_id = 'RunDiffusion/Juggernaut-XL-v9'
 # model_id = 'SG161222/RealVisXL_V5.0'
 # model_id = 'Lykon/dreamshaper-xl-lightning'
-# model_id = 'SG161222/RealVisXL_V5.0_Lightning'
-model_file = "https://huggingface.co/RunDiffusion/Juggernaut-XI-v11/blob/main/Juggernaut-XI-byRunDiffusion.safetensors"
-model_id = 'RunDiffusion/Juggernaut-XI-v11'
-#base_model_path = Path(model_id)
-#os.makedirs(base_model_path, exist_ok=True)
-#snapshot_download(repo_id=model_id, local_dir=base_model_path)
+model_id = 'SG161222/RealVisXL_V5.0_Lightning'
+# model_file = "https://huggingface.co/RunDiffusion/Juggernaut-XI-v11/blob/main/Juggernaut-XI-byRunDiffusion.safetensors"
+# model_id = 'RunDiffusion/Juggernaut-XI-v11'
+base_model_path = Path(model_id)
+os.makedirs(base_model_path, exist_ok=True)
+snapshot_download(repo_id=model_id, local_dir=base_model_path)
 #model_file = hf_hub_download(repo_id=model_id, filename="Juggernaut-XI-byRunDiffusion.safetensors", repo_type="model")
 
 face_detector = FaceAnalysis2(providers=['CPUExecutionProvider', 'CUDAExecutionProvider'], allowed_modules=['detection', 'recognition'])
@@ -71,21 +71,21 @@ adapter = T2IAdapter.from_pretrained(
     "TencentARC/t2i-adapter-sketch-sdxl-1.0", torch_dtype=torch_dtype, variant="fp16"
 ).to(device)
 
-pipe = PhotoMakerStableDiffusionXLAdapterPipeline.from_single_file(
-    model_file, 
-    adapter=adapter, 
-    torch_dtype=torch.float16,
-    use_safetensors=True
-).to(device)
-
-# pipe = PhotoMakerStableDiffusionXLAdapterPipeline.from_pretrained(
-#     base_model_path, 
+# pipe = PhotoMakerStableDiffusionXLAdapterPipeline.from_single_file(
+#     model_file, 
 #     adapter=adapter, 
-#     torch_dtype=torch_dtype,
-#     use_safetensors=True, 
-#     variant="fp16",
+#     torch_dtype=torch.float16,
+#     use_safetensors=True
 # ).to(device)
 
+pipe = PhotoMakerStableDiffusionXLAdapterPipeline.from_pretrained(
+    base_model_path, 
+    adapter=adapter, 
+    torch_dtype=torch_dtype,
+    use_safetensors=True, 
+    variant="fp16",
+).to(device)
+
 pipe.unet = pipe.unet.to(device=device, dtype=torch_dtype)
 pipe.unet.to(memory_format=torch.channels_last)
 pipe.unet.eval()