Update app.py

app.py

@@ -52,30 +52,6 @@ device = torch.device("cuda:0" if torch.cuda.is_available() else "cpu")
 torch_dtype = torch.bfloat16
 
 
-repo_id = "ford442/SDXL-IP_ADAPTER"
-subfolder = "image_encoder"
-subfolder2 = "ip_adapter"
-
-# Download the entire repository
-local_repo_path = snapshot_download(repo_id=repo_id, repo_type="model")
-
-# Construct the paths to the subfolders
-local_folder = os.path.join(local_repo_path, subfolder)
-local_folder2 = os.path.join(local_repo_path, subfolder2) # Path to the ip_adapter dir
-
-print(f"Image encoder downloaded to: {local_folder}")
-print(f"IP Adapter files downloaded to: {local_folder2}")
-
-# Construct the path to the ip-adapter_sdxl.bin file
-#ip_ckpt = os.path.join(local_folder2, "ip-adapter_sdxl.bin") # Correct path
-ip_ckpt = os.path.join(local_folder2, "ip-adapter_sdxl_vit-h.bin") # Correct path
-
-print(f"IP Adapter checkpoint path: {ip_ckpt}")
-ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
-
-upscaler_2 = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(torch.device("cuda:0"))
-
-
 checkpoint = "microsoft/Phi-3.5-mini-instruct"
 #vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
 vae = AutoencoderKL.from_pretrained("ford442/sdxl-vae-bf16")
@@ -111,6 +87,33 @@ tokenizer.tokenizer_legacy=False
 model = AutoModelForCausalLM.from_pretrained(checkpoint, device_map='balanced')
 #model = torch.compile(model)
 
+
+
+repo_id = "ford442/SDXL-IP_ADAPTER"
+subfolder = "image_encoder"
+subfolder2 = "ip_adapter"
+
+# Download the entire repository
+local_repo_path = snapshot_download(repo_id=repo_id, repo_type="model")
+
+# Construct the paths to the subfolders
+local_folder = os.path.join(local_repo_path, subfolder)
+local_folder2 = os.path.join(local_repo_path, subfolder2) # Path to the ip_adapter dir
+
+print(f"Image encoder downloaded to: {local_folder}")
+print(f"IP Adapter files downloaded to: {local_folder2}")
+
+# Construct the path to the ip-adapter_sdxl.bin file
+#ip_ckpt = os.path.join(local_folder2, "ip-adapter_sdxl.bin") # Correct path
+ip_ckpt = os.path.join(local_folder2, "ip-adapter_sdxl_vit-h.bin") # Correct path
+
+print(f"IP Adapter checkpoint path: {ip_ckpt}")
+ip_model = IPAdapterXL(pipe, local_folder, ip_ckpt, device)
+
+upscaler_2 = UpscaleWithModel.from_pretrained("Kim2091/ClearRealityV1").to(torch.device("cuda:0"))
+
+
+
 def filter_text(text,phraseC):
   """Filters out the text up to and including 'Rewritten Prompt:'."""
   phrase = "Rewritten Prompt:"