Update app.py

app.py

@@ -464,7 +464,7 @@ def generate_modeling_phoenix_code():
     Hub에서 로드 시 자동으로 Retention 변환
     """
     
-    modeling_code = '''"""
+    modeling_code = """
 PHOENIX Retention Model - Custom Implementation
 Auto-loaded by HuggingFace transformers with trust_remote_code=True
 
@@ -812,23 +812,26 @@ class PhoenixModelForCausalLM(PhoenixPreTrainedModel):
         
         print(f"🔥 Loading PHOENIX model from {pretrained_model_name_or_path}")
         
-        # 1. Load base model
+        # 1. Load base model config
         config = AutoConfig.from_pretrained(pretrained_model_name_or_path, trust_remote_code=True)
         
         # Original architecture 추출
         original_arch = config.architectures[0] if hasattr(config, 'architectures') else 'AutoModelForCausalLM'
         
-        # 2. Load with original architecture
+        # 2. kwargs 복사 및 trust_remote_code 제거
+        base_kwargs = kwargs.copy()
+        base_kwargs.pop('trust_remote_code', None)  # 중복 방지
+        
+        # 3. Load with original architecture
         base_model = AutoModelForCausalLM.from_pretrained(
             pretrained_model_name_or_path,
             *model_args,
-            **kwargs,
-            trust_remote_code=False  # 원본 모델은 trust 불필요
+            **base_kwargs
         )
         
         print(f"   ✅ Base model loaded: {original_arch}")
         
-        # 3. Retention 변환
+        # 4. Retention 변환
         use_hierarchical = config.use_hierarchical if hasattr(config, 'use_hierarchical') else True
         
         print(f"🔄 Converting to PHOENIX Retention...")
@@ -836,7 +839,7 @@ class PhoenixModelForCausalLM(PhoenixPreTrainedModel):
         
         print(f"✅ Converted {converted}/{total} layers to Retention")
         
-        # 4. Create PHOENIX wrapper
+        # 5. Create PHOENIX wrapper
         phoenix_instance = cls(config)
         phoenix_instance._original_model = base_model
         phoenix_instance._initialized = True
@@ -868,7 +871,6 @@ class PhoenixModelForCausalLM(PhoenixPreTrainedModel):
 
 # Auto-registration
 AutoConfig.register("phoenix", PhoenixConfig)
-'''
     
     return modeling_code