diff --git a/vectorizers/_vectorizers.py b/vectorizers/_vectorizers.py
index 0c700d4..ab588a7 100644
--- a/vectorizers/_vectorizers.py
+++ b/vectorizers/_vectorizers.py
@@ -967,6 +967,11 @@ def token_cooccurrence_matrix(
         symmetric: counts tokens occurring before and after as the same tokens
         directional: counts tokens before and after as different and returns both counts.
 
+    chunk_size: int (optional, default=1048576)
+        When processing token sequences, break the list of sequences into
+        chunks of this size to stream the data through, rather than storing all
+        the results at once. This saves on peak memory usage.
+
     Returns
     -------
     cooccurrence_matrix: scipyr.sparse.csr_matrix
@@ -1004,6 +1009,7 @@ def token_cooccurrence_matrix(
             shape=(n_unique_tokens, n_unique_tokens),
             dtype=np.float32,
         )
+        cooccurrence_matrix.sum_duplicates()
 
     if window_orientation == "before":
         cooccurrence_matrix = cooccurrence_matrix.transpose()
@@ -1205,6 +1211,11 @@ class TokenCooccurrenceVectorizer(BaseEstimator, TransformerMixin):
         symmetric: counts tokens occurring before and after as the same tokens
         directional: counts tokens before and after as different and returns both counts.
 
+    chunk_size: int (optional, default=1048576)
+        When processing token sequences, break the list of sequences into
+        chunks of this size to stream the data through, rather than storing all
+        the results at once. This saves on peak memory usage.
+
     validate_data: bool (optional, default=True)
         Check whether the data is valid (e.g. of homogeneous token type).
     """
@@ -1226,6 +1237,7 @@ def __init__(
         kernel_function="flat",
         window_radius=5,
         window_orientation="directional",
+        chunk_size=1<<20,
         validate_data=True,
     ):
         self.token_dictionary = token_dictionary
@@ -1245,6 +1257,7 @@ def __init__(
         self.window_radius = window_radius
 
         self.window_orientation = window_orientation
+        self.chunk_size = chunk_size
         self.validate_data = validate_data
 
     def fit_transform(self, X, y=None, **fit_params):
@@ -1309,6 +1322,7 @@ def fit_transform(self, X, y=None, **fit_params):
             window_args=(self._window_size, self._token_frequencies_),
             kernel_args=(self.window_radius,),
             window_orientation=self.window_orientation,
+            chunk_size=self.chunk_size,
         )
         self.cooccurrences_.eliminate_zeros()