Update app.py

app.py

@@ -3,7 +3,7 @@ import subprocess
 import torch
 from PIL import Image
 from transformers import AutoProcessor, AutoConfig
-import importlib, sys
+import importlib.util, sys, os
 
 subprocess.run(
     "pip install --upgrade transformers>=4.50.0",
@@ -17,17 +17,23 @@ device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 
 config = AutoConfig.from_pretrained(model_id, trust_remote_code=True)
 
-module_base       = config.__module__.rsplit(".", 1)[0]
-modeling_mod_path = module_base + ".modeling_florence2"
-modeling_mod      = importlib.import_module(modeling_mod_path)
+mconfig_mod_name = config.__class__.__module__ 
+config_mod      = sys.modules[config_mod_name]
+code_dir        = os.path.dirname(config_mod.__file__)
 
-FlorenceLM = getattr(
-    modeling_mod,
-    "Florence2LanguageForConditionalGeneration"
-)
+modeling_path = os.path.join(code_dir, "modeling_florence2.py")
+if not os.path.exists(modeling_path):
+    raise FileNotFoundError(f"Couldn’t find {modeling_path}")
+
+spec = importlib.util.spec_from_file_location("florence2_modeling", modeling_path)
+flor_mod = importlib.util.module_from_spec(spec)
+sys.modules["florence2_modeling"] = flor_mod
+spec.loader.exec_module(flor_mod)
+
+FlorenceLM = flor_mod.Florence2LanguageForConditionalGeneration
 florence_model = FlorenceLM.from_pretrained(
     model_id,
-    trust_remote_code=True,
+    trust_remote_code=True
 ).to(device).eval()
 florence_processor = AutoProcessor.from_pretrained(model, trust_remote_code=True)