Update app.py

app.py

@@ -9,12 +9,16 @@ class LoRAInferenceWrapper:
         self.client = InferenceClient(model_id, token=token)
 
     def load_lora_weights(self):
-        # Define the path to the LoRA model
-        lora_model_path = "./lora_file.pth"  # Assuming the file is saved locally
-
-        # Check if the file exists
-        if not os.path.exists(lora_model_path):
-            raise FileNotFoundError(f"LoRA file not found at path: {lora_model_path}")
+    # Define the path to the LoRA model
+    lora_model_path = "./lora.model.pth"  # Update to the actual file name
+
+    # Check if the file exists at the given path
+    if os.path.exists(lora_model_path):
+        print(f"Found LoRA model at: {lora_model_path}")
+        with open(lora_model_path, 'rb') as f:
+            return f.read()  # Load the file content
+    else:
+        raise FileNotFoundError(f"LoRA model not found at path: {lora_model_path}")
 
         # Load the LoRA weights from the local file
         with open(lora_model_path, "rb") as f: