diff --git a/sentence_transformers/SentenceTransformer.py b/sentence_transformers/SentenceTransformer.py
index 1a8cb2efb..4fd069f7d 100644
--- a/sentence_transformers/SentenceTransformer.py
+++ b/sentence_transformers/SentenceTransformer.py
@@ -1718,10 +1718,10 @@ def _load_sbert_model(
 
                 # Try to initialize the module with a lot of kwargs, but only if the module supports them
                 # Otherwise we fall back to the load method
-                # try:
-                module = module_class(model_name_or_path, cache_dir=cache_folder, backend=self.backend, **kwargs)
-                # except TypeError:
-                #     module = module_class.load(model_name_or_path)
+                try:
+                    module = module_class(model_name_or_path, cache_dir=cache_folder, backend=self.backend, **kwargs)
+                except TypeError:
+                    module = module_class.load(model_name_or_path)
             else:
                 # Normalize does not require any files to be loaded
                 if module_class == Normalize:
diff --git a/sentence_transformers/backend.py b/sentence_transformers/backend.py
index eef76352e..355f40d83 100644
--- a/sentence_transformers/backend.py
+++ b/sentence_transformers/backend.py
@@ -78,7 +78,9 @@ def export_optimized_onnx_model(
         or not isinstance(model[0], Transformer)
         or not isinstance(model[0].auto_model, ORTModelForFeatureExtraction)
     ):
-        raise ValueError('The model must be a SentenceTransformer model loaded with `backend="onnx"`.')
+        raise ValueError(
+            'The model must be a Transformer-based SentenceTransformer model loaded with `backend="onnx"`.'
+        )
 
     ort_model: ORTModelForFeatureExtraction = model[0].auto_model
     optimizer = ORTOptimizer.from_pretrained(ort_model)
@@ -158,7 +160,9 @@ def export_dynamic_quantized_onnx_model(
         or not isinstance(model[0], Transformer)
         or not isinstance(model[0].auto_model, ORTModelForFeatureExtraction)
     ):
-        raise ValueError('The model must be a SentenceTransformer model loaded with `backend="onnx"`.')
+        raise ValueError(
+            'The model must be a Transformer-based SentenceTransformer model loaded with `backend="onnx"`.'
+        )
 
     ort_model: ORTModelForFeatureExtraction = model[0].auto_model
     quantizer = ORTQuantizer.from_pretrained(ort_model)