diff --git a/app.py b/app.py
index 46bcdd3..66405bd 100644
--- a/app.py
+++ b/app.py
@@ -38,10 +38,10 @@ def startup_event():
         logger.info("Running on CPU")
 
     # Batch text tokenization enabled by default
-    direct_tokenize = True
+    direct_tokenize = False
     transformers_direct_tokenize = os.getenv("T2V_TRANSFORMERS_DIRECT_TOKENIZE")
-    if transformers_direct_tokenize is not None and transformers_direct_tokenize == "false" or transformers_direct_tokenize == "0":
-        direct_tokenize = False
+    if transformers_direct_tokenize is not None and transformers_direct_tokenize == "true" or transformers_direct_tokenize == "1":
+        direct_tokenize = True
 
     meta_config = Meta('./models/model')
     vec = Vectorizer('./models/model', cuda_support, cuda_core, cuda_per_process_memory_fraction,
diff --git a/vectorizer.py b/vectorizer.py
index 2b993d1..994f972 100644
--- a/vectorizer.py
+++ b/vectorizer.py
@@ -67,7 +67,7 @@ def pool_embedding(self, batch_results, tokens, config):
 
     async def vectorize(self, text: str, config: VectorInputConfig):
         with torch.no_grad():
-            if not self.direct_tokenize:
+            if self.direct_tokenize:
                 # create embeddings without tokenizing text
                 tokens = self.tokenize(text)
                 if self.cuda: