diff --git a/python/cuml/cuml/feature_extraction/_vectorizers.py b/python/cuml/cuml/feature_extraction/_vectorizers.py
index e8086f5ec6..162f895e7f 100644
--- a/python/cuml/cuml/feature_extraction/_vectorizers.py
+++ b/python/cuml/cuml/feature_extraction/_vectorizers.py
@@ -28,9 +28,20 @@
 
 cp = gpu_only_import("cupy")
 cudf = gpu_only_import("cudf")
+np = cpu_only_import("numpy")
 pd = cpu_only_import("pandas")
 
 
+def min_signed_type(n):
+    for int_dtype in (np.int8, np.int16, np.int32, np.int64):
+        dtype = np.dtype(int_dtype)
+        if (dtype.itemsize * 8) >= 8:
+            if np.iinfo(int_dtype).min <= n <= np.iinfo(int_dtype).max:
+                return dtype
+    # resort to using `int64` and let numpy raise appropriate exception:
+    return np.int64(n).dtype
+
+
 def _preprocess(
     doc,
     lower=False,
@@ -255,7 +266,7 @@ def _compute_empty_doc_ids(self, count_df, n_doc):
         of documents.
         """
         remaining_docs = count_df["doc_id"].unique()
-        dtype = cudf.utils.dtypes.min_signed_type(n_doc)
+        dtype = min_signed_type(n_doc)
         doc_ids = cudf.DataFrame(
             data={"all_ids": cp.arange(0, n_doc, dtype=dtype)}, dtype=dtype
         )
diff --git a/python/cuml/cuml/internals/array.py b/python/cuml/cuml/internals/array.py
index d1f1269290..f120600bb7 100644
--- a/python/cuml/cuml/internals/array.py
+++ b/python/cuml/cuml/internals/array.py
@@ -44,7 +44,6 @@
 cached_property = safe_import_from(
     "functools", "cached_property", alt=null_decorator
 )
-CudfBuffer = gpu_only_import_from("cudf.core.buffer", "Buffer")
 CudfDataFrame = gpu_only_import_from("cudf", "DataFrame")
 CudfIndex = gpu_only_import_from("cudf", "Index")
 CudfSeries = gpu_only_import_from("cudf", "Series")