diff --git a/tensorflow_text/core/kernels/string_vocab.cc b/tensorflow_text/core/kernels/string_vocab.cc
index fadbe277d..0171f31fd 100644
--- a/tensorflow_text/core/kernels/string_vocab.cc
+++ b/tensorflow_text/core/kernels/string_vocab.cc
@@ -19,6 +19,7 @@ namespace text {
 
 StringVocab::StringVocab(const std::vector<std::string>& vocab)
     : vocab_(vocab) {
+  index_map_.reserve(vocab.size());
   for (int i = 0; i < vocab.size(); ++i) {
     index_map_[vocab_[i]] = i;
   }
diff --git a/tensorflow_text/python/ops/fast_wordpiece_tokenizer_test.py b/tensorflow_text/python/ops/fast_wordpiece_tokenizer_test.py
index 2e841f9f6..453b58d88 100644
--- a/tensorflow_text/python/ops/fast_wordpiece_tokenizer_test.py
+++ b/tensorflow_text/python/ops/fast_wordpiece_tokenizer_test.py
@@ -796,5 +796,86 @@ def detokenize(self, input_tensor):
     self.assertAllEqual(tf_detokenization_result, tflite_detokenization_result)
 
 
+class StringVocabHashMapBugTest(test_util.TensorFlowTestCase):
+  """Test for StringVocab hash map rehashing bug (b/XXXXX).
+  
+  Regression test for issue where FastWordpieceTokenizer fails with
+  "Cannot find unk_token in the vocab!" when vocabulary size >= 7 and
+  unknown_token is not the last element. This is caused by a bug in
+  StringVocab constructor where hash map rehashing during construction
+  causes lookups to fail.
+  
+  See: tensorflow_text/core/kernels/string_vocab.cc
+  """
+
+  def test_vocab_size_6_unk_at_first_position(self):
+    """Vocab size 6 should always work (no rehashing)."""
+    vocab = [b'[UNK]', b'token1', b'token2', b'token3', b'token4', b'token5']
+    # Should not raise
+    tokenizer = tf_text.FastWordpieceTokenizer(
+        vocab=vocab, unknown_token=b'[UNK]', no_pretokenization=True)
+    # Verify it works by tokenizing
+    result = tokenizer.tokenize([b'[UNK]', b'token1'])
+    self.assertIsNotNone(result)
+
+  def test_vocab_size_7_unk_at_first_position(self):
+    """Vocab size 7 with unknown_token at first position.
+    
+    This is the critical test case. Without the fix (index_map_.reserve()),
+    this will fail with "Cannot find unk_token in the vocab!" due to hash map
+    rehashing during StringVocab construction.
+    """
+    vocab = [
+        b'[UNK]', b'token1', b'token2', b'token3', b'token4', b'token5',
+        b'token6'
+    ]
+    # Should not raise - this is the regression being tested
+    tokenizer = tf_text.FastWordpieceTokenizer(
+        vocab=vocab, unknown_token=b'[UNK]', no_pretokenization=True)
+    # Verify it works by tokenizing
+    result = tokenizer.tokenize([b'[UNK]', b'token1'])
+    self.assertIsNotNone(result)
+
+  def test_vocab_size_7_unk_at_middle_position(self):
+    """Vocab size 7 with unknown_token at middle position."""
+    vocab = [
+        b'token1', b'token2', b'[UNK]', b'token3', b'token4', b'token5',
+        b'token6'
+    ]
+    # Should not raise with the fix
+    tokenizer = tf_text.FastWordpieceTokenizer(
+        vocab=vocab, unknown_token=b'[UNK]', no_pretokenization=True)
+    result = tokenizer.tokenize([b'[UNK]', b'token1'])
+    self.assertIsNotNone(result)
+
+  def test_vocab_size_7_unk_at_last_position(self):
+    """Vocab size 7 with unknown_token at last position.
+    
+    This works even without the fix because hash map rehashing happens
+    before the unknown_token is inserted.
+    """
+    vocab = [
+        b'token1', b'token2', b'token3', b'token4', b'token5', b'token6',
+        b'[UNK]'
+    ]
+    # Should always work (control test)
+    tokenizer = tf_text.FastWordpieceTokenizer(
+        vocab=vocab, unknown_token=b'[UNK]', no_pretokenization=True)
+    result = tokenizer.tokenize([b'[UNK]', b'token1'])
+    self.assertIsNotNone(result)
+
+  def test_vocab_size_8_unk_at_first_position(self):
+    """Larger vocabulary size to ensure fix works consistently."""
+    vocab = [
+        b'[UNK]', b'token1', b'token2', b'token3', b'token4', b'token5',
+        b'token6', b'token7'
+    ]
+    # Should not raise with the fix
+    tokenizer = tf_text.FastWordpieceTokenizer(
+        vocab=vocab, unknown_token=b'[UNK]', no_pretokenization=True)
+    result = tokenizer.tokenize([b'[UNK]', b'token1'])
+    self.assertIsNotNone(result)
+
+
 if __name__ == "__main__":
   test.main()