diff --git a/python/cudf/cudf/core/df_protocol.py b/python/cudf/cudf/core/df_protocol.py
index cc9f39d70ef..5f2dfe98a3e 100644
--- a/python/cudf/cudf/core/df_protocol.py
+++ b/python/cudf/cudf/core/df_protocol.py
@@ -105,7 +105,7 @@ def __dlpack__(self):
         # DLPack not implemented in NumPy yet, so leave it out here.
         try:
             cuda_array = as_cuda_array(self._buf).view(self._dtype)
-            return cp.asarray(cuda_array).toDlpack()
+            return cp.asarray(cuda_array).__dlpack__()
         except ValueError:
             raise TypeError(f"dtype {self._dtype} unsupported by `dlpack`")
 
diff --git a/python/cudf/cudf/core/subword_tokenizer.py b/python/cudf/cudf/core/subword_tokenizer.py
index 50d1a11c39b..24e6aa40de0 100644
--- a/python/cudf/cudf/core/subword_tokenizer.py
+++ b/python/cudf/cudf/core/subword_tokenizer.py
@@ -19,7 +19,7 @@ def _cast_to_appropriate_type(ar, cast_type):
     elif cast_type == "tf":
         from tensorflow.experimental.dlpack import from_dlpack
 
-    return from_dlpack(ar.astype("int32").toDlpack())
+    return from_dlpack(ar.astype("int32").__dlpack__())
 
 
 class SubwordTokenizer:
diff --git a/python/cudf/cudf/tests/test_dlpack.py b/python/cudf/cudf/tests/test_dlpack.py
index 20c24bd7564..187a5524e8e 100644
--- a/python/cudf/cudf/tests/test_dlpack.py
+++ b/python/cudf/cudf/tests/test_dlpack.py
@@ -1,4 +1,4 @@
-# Copyright (c) 2019-2024, NVIDIA CORPORATION.
+# Copyright (c) 2019-2025, NVIDIA CORPORATION.
 
 import itertools
 from contextlib import ExitStack as does_not_raise
@@ -140,7 +140,7 @@ def test_to_dlpack_cupy_2d(data_2d):
 def test_from_dlpack_cupy_1d(data_1d):
     cupy_array = cupy.array(data_1d)
     cupy_host_array = cupy_array.get()
-    dlt = cupy_array.toDlpack()
+    dlt = cupy_array.__dlpack__()
 
     gs = cudf.from_dlpack(dlt)
     cudf_host_array = gs.to_numpy(na_value=np.nan)
@@ -151,7 +151,7 @@ def test_from_dlpack_cupy_1d(data_1d):
 def test_from_dlpack_cupy_2d(data_2d):
     cupy_array = cupy.array(data_2d, order="F")
     cupy_host_array = cupy_array.get().flatten()
-    dlt = cupy_array.toDlpack()
+    dlt = cupy_array.__dlpack__()
 
     gdf = cudf.from_dlpack(dlt)
     cudf_host_array = np.array(gdf.to_pandas()).flatten()