Use positional bidirectional mask helper call

Call transformers.masking_utils.create_bidirectional_mask positionally so the custom model does not depend on either the deprecated input_embeds keyword or the newer inputs_embeds spelling.

llama_bidirectional_model.py

@@ -118,9 +118,9 @@ class LlamaBidirectionalModel(LlamaModel):
 
         if _HAS_NATIVE_BIDIRECTIONAL_MASK:
             return create_bidirectional_mask(
-                config=self.config,
-                inputs_embeds=input_embeds,
-                attention_mask=attention_mask,
+                self.config,
+                input_embeds,
+                attention_mask,
             )
 
         # Fallback for transformers < 5.0 without create_bidirectional_mask