diff --git a/api/onnx_web/diffusers/load.py b/api/onnx_web/diffusers/load.py
index 340be21d..6c95364f 100644
--- a/api/onnx_web/diffusers/load.py
+++ b/api/onnx_web/diffusers/load.py
@@ -229,20 +229,20 @@ def load_pipeline(
         ]]
 
         logger.info("blending text encoder with LoRA models: %s", lora_models)
-        blended_text_encoder = merge_lora("text_encoder", lora_models, None, "text_encoder")
+        blended_text_encoder = merge_lora(path.join(server.model_path, "stable-diffusion-onnx-v1-5/text_encoder/model.onnx"), lora_models, None, "text_encoder")
         (text_encoder_model, text_encoder_data) = buffer_external_data_tensors(blended_text_encoder)
         text_encoder_names, text_encoder_values = zip(*text_encoder_data)
         text_encoder_opts = SessionOptions()
         text_encoder_opts.add_external_initializers(list(text_encoder_names), list(text_encoder_values))
-        components["text_encoder"] = OnnxRuntimeModel.from_pretrained(text_encoder_model, sess_options=text_encoder_opts)
+        components["text_encoder"] = OnnxRuntimeModel(OnnxRuntimeModel.load_model(text_encoder_model.SerializeToString(), provider=device.ort_provider(), sess_options=text_encoder_opts))
 
         logger.info("blending unet with LoRA models: %s", lora_models)
-        blended_unet = merge_lora("unet", lora_models, None, "unet")
+        blended_unet = merge_lora(path.join(server.model_path, "stable-diffusion-onnx-v1-5/unet/model.onnx"), lora_models, None, "unet")
         (unet_model, unet_data) = buffer_external_data_tensors(blended_unet)
         unet_names, unet_values = zip(*unet_data)
         unet_opts = SessionOptions()
         unet_opts.add_external_initializers(list(unet_names), list(unet_values))
-        components["unet"] = OnnxRuntimeModel.from_pretrained(unet_model, sess_options=unet_opts)
+        components["unet"] = OnnxRuntimeModel(OnnxRuntimeModel.load_model(unet_model.SerializeToString(), provider=device.ort_provider(), sess_options=unet_opts))
 
         pipe = pipeline.from_pretrained(
             model,