diff --git a/models/convert-h5-to-ggml.py b/models/convert-h5-to-ggml.py
index b882c4d..b06ad23 100644
--- a/models/convert-h5-to-ggml.py
+++ b/models/convert-h5-to-ggml.py
@@ -56,7 +56,7 @@ def bytes_to_unicode():
     The reversible bpe codes work on unicode strings.
     This means you need a large # of unicode characters in your vocab if you want to avoid UNKs.
     When you're at something like a 10B token dataset you end up needing around 5K for decent coverage.
-    This is a signficant percentage of your normal, say, 32K bpe vocab.
+    This is a significant percentage of your normal, say, 32K bpe vocab.
     To avoid that, we want lookup tables between utf-8 bytes and unicode strings.
     And avoids mapping to whitespace/control characters the bpe code barfs on.
     """