diff --git a/src/python/txtai/embeddings/base.py b/src/python/txtai/embeddings/base.py
index d8a3087d0..b54aadf8c 100644
--- a/src/python/txtai/embeddings/base.py
+++ b/src/python/txtai/embeddings/base.py
@@ -741,7 +741,7 @@ def configure(self, config):
         self.scoring = self.createscoring() if scoring and (not isinstance(scoring, dict) or not scoring.get("terms")) else None
 
         # Dense vectors - transforms data to embeddings vectors
-        self.model = self.loadvectors() if self.config else None
+        self.model = self.loadvectors() if self.config and self.config.get("path") else None
 
         # Query model
         self.query = self.loadquery() if self.config else None
diff --git a/src/python/txtai/vectors/factory.py b/src/python/txtai/vectors/factory.py
index 627333434..92fc737f3 100644
--- a/src/python/txtai/vectors/factory.py
+++ b/src/python/txtai/vectors/factory.py
@@ -42,7 +42,7 @@ def create(config, scoring=None, models=None):
             return WordVectors(config, scoring, models)
 
         # Default to TransformersVectors when configuration available
-        return TransformersVectors(config, scoring, models) if config and "path" in config else None
+        return TransformersVectors(config, scoring, models) if config.get("path") else None
 
     @staticmethod
     def method(config):