diff --git a/api/onnx_web/diffusers/load.py b/api/onnx_web/diffusers/load.py
index 4e4c8c90..3e0c2920 100644
--- a/api/onnx_web/diffusers/load.py
+++ b/api/onnx_web/diffusers/load.py
@@ -369,6 +369,32 @@ def load_text_encoders(
             )
             text_encoder_session._model_path = path.join(model, "text_encoder")
             components["text_encoder_session"] = text_encoder_session
+
+            text_encoder_2 = path.join(model, "text_encoder_2", ONNX_MODEL)
+            text_encoder_2 = blend_loras(
+                server,
+                text_encoder_2,
+                list(zip(lora_models, lora_weights)),
+                "text_encoder",
+                2,
+                params.is_xl(),
+            )
+            (text_encoder_2, text_encoder_2_data) = buffer_external_data_tensors(
+                text_encoder_2
+            )
+            text_encoder_2_names, text_encoder_2_values = zip(*text_encoder_2_data)
+            text_encoder_2_opts = device.sess_options(cache=False)
+            text_encoder_2_opts.add_external_initializers(
+                list(text_encoder_2_names), list(text_encoder_2_values)
+            )
+
+            text_encoder_2_session = InferenceSession(
+                text_encoder_2.SerializeToString(),
+                providers=[device.ort_provider("text-encoder")],
+                sess_options=text_encoder_2_opts,
+            )
+            text_encoder_2_session._model_path = path.join(model, "text_encoder_2")
+            components["text_encoder_2_session"] = text_encoder_2_session
         else:
             components["text_encoder"] = OnnxRuntimeModel(
                 OnnxRuntimeModel.load_model(
@@ -378,33 +404,6 @@ def load_text_encoders(
                 )
             )
 
-    if params.is_xl():
-        text_encoder_2 = path.join(model, "text_encoder_2", ONNX_MODEL)
-        text_encoder_2 = blend_loras(
-            server,
-            text_encoder_2,
-            list(zip(lora_models, lora_weights)),
-            "text_encoder",
-            2,
-            params.is_xl(),
-        )
-        (text_encoder_2, text_encoder_2_data) = buffer_external_data_tensors(
-            text_encoder_2
-        )
-        text_encoder_2_names, text_encoder_2_values = zip(*text_encoder_2_data)
-        text_encoder_2_opts = device.sess_options(cache=False)
-        text_encoder_2_opts.add_external_initializers(
-            list(text_encoder_2_names), list(text_encoder_2_values)
-        )
-
-        text_encoder_2_session = InferenceSession(
-            text_encoder_2.SerializeToString(),
-            providers=[device.ort_provider("text-encoder")],
-            sess_options=text_encoder_2_opts,
-        )
-        text_encoder_2_session._model_path = path.join(model, "text_encoder_2")
-        components["text_encoder_2_session"] = text_encoder_2_session
-
     return components