diff --git a/tokengrams/tokengrams.pyi b/tokengrams/tokengrams.pyi
index 6f32ffd..3b34edc 100644
--- a/tokengrams/tokengrams.pyi
+++ b/tokengrams/tokengrams.pyi
@@ -36,10 +36,10 @@ class InMemoryIndex:
     def batch_count_next(self, queries: list[list[int]]) -> list[list[int]]:
         """Count the occurrences of each token that directly follows each sequence in `queries`."""
 
-    def smoothed_probs(self, query: list[int]) -> list[float]:
+    def get_smoothed_probs(self, query: list[int]) -> list[float]:
         """Compute interpolated Kneser-Ney smoothed token probability distribution using all previous tokens in the query."""
 
-    def batch_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
+    def batch_get_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
         """Compute interpolated Kneser-Ney smoothed token probability distributions using all previous tokens in each query."""
 
     def sample_smoothed(self, query: list[int], n: int, k: int, num_samples: int) -> list[list[int]]:
@@ -97,10 +97,10 @@ class MemmapIndex:
         on the previous (n - 1) characters (n-gram prefix) in the sequence. If there are fewer than 
         (n - 1) characters all available characters are used."""
 
-    def smoothed_probs(self, query: list[int]) -> list[float]:
+    def get_smoothed_probs(self, query: list[int]) -> list[float]:
         """Compute interpolated Kneser-Ney smoothed token probability distribution using all previous tokens in the query."""
 
-    def batch_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
+    def batch_get_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
         """Compute interpolated Kneser-Ney smoothed token probability distributions using all previous tokens in each query."""
     
     def estimate_deltas(self, n: int):
@@ -145,10 +145,10 @@ class ShardedMemmapIndex:
         on the previous (n - 1) characters (n-gram prefix) in the sequence. If there are fewer than 
         (n - 1) characters all available characters are used."""
 
-    def smoothed_probs(self, query: list[int]) -> list[float]:
+    def get_smoothed_probs(self, query: list[int]) -> list[float]:
         """Compute interpolated Kneser-Ney smoothed token probability distribution using all previous tokens in the query."""
 
-    def batch_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
+    def batch_get_smoothed_probs(self, queries: list[list[int]]) -> list[list[float]]:
         """Compute interpolated Kneser-Ney smoothed token probability distributions using all previous tokens in each query."""
     
     def estimate_deltas(self, n: int):