Update app.py

app.py

@@ -10,7 +10,7 @@ from typing import Tuple, Optional
 
 from PIL import Image
 from gradio_imageslider import ImageSlider
-from transformers import AutoModelForImageSegmentation
+from transformers import AutoModelForImageSegmentation, PretrainedConfig
 from torchvision import transforms
 
 import requests
@@ -18,6 +18,9 @@ from io import BytesIO
 import zipfile
 import random
 
+# monkey-patch: get_text_config를 덮어써서 dummy 객체를 반환 (tie_word_embeddings=False)
+PretrainedConfig.get_text_config = lambda self, decoder=True: type("DummyTextConfig", (), {"tie_word_embeddings": False})()
+
 torch.set_float32_matmul_precision('high')
 torch.jit.script = lambda f: f
 
@@ -75,12 +78,9 @@ usage_to_weights_file = {
     'General-legacy': 'BiRefNet-legacy'
 }
 
-# 모델 로딩 전에 tie_weights()를 빈 함수로 재정의(우회)
-AutoModelForImageSegmentation.tie_weights = lambda self: None
-
 # 초기 모델 로딩 (기본: General)
 birefnet = AutoModelForImageSegmentation.from_pretrained(
-    '/'.join(('zhengpeng7', usage_to_weights_file['General'])), 
+    '/'.join(('zhengpeng7', usage_to_weights_file['General'])),
     trust_remote_code=True
 )
 birefnet.to(device)