diff --git a/src/cogkit/api/services/image_generation.py b/src/cogkit/api/services/image_generation.py
index b332f2a..672d8f0 100644
--- a/src/cogkit/api/services/image_generation.py
+++ b/src/cogkit/api/services/image_generation.py
@@ -57,15 +57,17 @@ def generate(
         if model not in self._models:
             raise ValueError(f"Model {model} not loaded")
         width, height = list(map(int, size.split("x")))
-
         # TODO: Refactor this to switch by LoRA endpoint API
         if lora_path != self._current_lora[model]:
             if lora_path is not None:
                 adapter_name = os.path.basename(lora_path)
-                _logger.info(f"Loading LORA weights from {adapter_name}")
+                _logger.info(
+                    f"Loading LORA weights from {adapter_name} and unload previous weights {self._current_lora[model]}"
+                )
+                unload_lora_checkpoint(self._models[model])
                 load_lora_checkpoint(self._models[model], lora_path, lora_scale)
             else:
-                _logger.info("Unloading LORA weights")
+                _logger.info(f"Unloading LORA weights {self._current_lora[model]}")
                 unload_lora_checkpoint(self._models[model])
 
             self._current_lora[model] = lora_path
diff --git a/src/cogkit/utils/lora.py b/src/cogkit/utils/lora.py
index f0ccbe0..2c09d97 100644
--- a/src/cogkit/utils/lora.py
+++ b/src/cogkit/utils/lora.py
@@ -9,8 +9,8 @@ def load_lora_checkpoint(
     lora_model_id_or_path: str,
     lora_scale: float = 1.0,
 ) -> None:
-    pipeline.load_lora_weights(lora_model_id_or_path)
-    pipeline.fuse_lora(components=["transformer"], lora_scale=lora_scale)
+    pipeline.load_lora_weights(lora_model_id_or_path, lora_scale=lora_scale)
+    # pipeline.fuse_lora(components=["transformer"], lora_scale=lora_scale)
 
 
 def unload_lora_checkpoint(