diff --git a/src/python/txtai/vectors/factory.py b/src/python/txtai/vectors/factory.py
index de07575b7..7abdd8755 100644
--- a/src/python/txtai/vectors/factory.py
+++ b/src/python/txtai/vectors/factory.py
@@ -8,7 +8,7 @@
 from .huggingface import HFVectors
 from .litellm import LiteLLM
 from .llama import LlamaCpp
-from .words import WordVectors, WORDS
+from .words import WordVectors
 
 
 class VectorsFactory:
@@ -47,13 +47,6 @@ def create(config, scoring=None, models=None):
 
         # Word vectors
         if method == "words":
-            if not WORDS:
-                # Raise error if trying to create Word Vectors without vectors extra
-                raise ImportError(
-                    'Word vector models are not available - install "vectors" extra to enable. Otherwise, specify '
-                    + 'method="transformers" to use transformer backed models'
-                )
-
             return WordVectors(config, scoring, models)
 
         # Transformers vectors
diff --git a/src/python/txtai/vectors/litellm.py b/src/python/txtai/vectors/litellm.py
index d7d414d21..e1ecbe390 100644
--- a/src/python/txtai/vectors/litellm.py
+++ b/src/python/txtai/vectors/litellm.py
@@ -48,11 +48,12 @@ def ismodel(path):
         return False
 
     def __init__(self, config, scoring, models):
-        super().__init__(config, scoring, models)
-
+        # Check before parent constructor since it calls loadmodel
         if not LITELLM:
             raise ImportError('LiteLLM is not available - install "vectors" extra to enable')
 
+        super().__init__(config, scoring, models)
+
     def loadmodel(self, path):
         return None
 
diff --git a/src/python/txtai/vectors/words.py b/src/python/txtai/vectors/words.py
index d97514900..46f5d9ed7 100644
--- a/src/python/txtai/vectors/words.py
+++ b/src/python/txtai/vectors/words.py
@@ -66,6 +66,17 @@ class WordVectors(Vectors):
     Builds vectors using weighted word embeddings.
     """
 
+    def __init__(self, config, scoring, models):
+        # Check before parent constructor since it calls loadmodel
+        if not WORDS:
+            # Raise error if trying to create Word Vectors without vectors extra
+            raise ImportError(
+                'Word vector models are not available - install "vectors" extra to enable. Otherwise, specify '
+                + 'method="transformers" to use transformer backed models'
+            )
+
+        super().__init__(config, scoring, models)
+
     def loadmodel(self, path):
         # Ensure that vector path exists
         if not path or not os.path.isfile(path):