Add local_dir_use_symlinks=False in from_pretrained.

app.py

@@ -98,7 +98,7 @@ usage_to_weights_file = {
     'General-dynamic': 'BiRefNet_dynamic',
 }
 
-birefnet = transformers.AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file['General'])), trust_remote_code=True, cache_dir=hf_cache_path)
+birefnet = transformers.AutoModelForImageSegmentation.from_pretrained('/'.join(('zhengpeng7', usage_to_weights_file['General'])), trust_remote_code=True, cache_dir=hf_cache_path, local_dir_use_symlinks=False)
 birefnet.to(device)
 birefnet.eval(); birefnet.half()
 
@@ -111,7 +111,7 @@ def predict(images, resolution, weights_file):
     # Load BiRefNet with chosen weights
     _weights_file = '/'.join(('zhengpeng7', usage_to_weights_file[weights_file] if weights_file is not None else usage_to_weights_file['General']))
     print('Using weights: {}.'.format(_weights_file))
-    birefnet = transformers.AutoModelForImageSegmentation.from_pretrained(_weights_file, trust_remote_code=True, cache_dir=hf_cache_path)
+    birefnet = transformers.AutoModelForImageSegmentation.from_pretrained(_weights_file, trust_remote_code=True, cache_dir=hf_cache_path, local_dir_use_symlinks=False)
     birefnet.to(device)
     birefnet.eval(); birefnet.half()