diff --git a/src/glum/_glm.py b/src/glum/_glm.py
index 8c9e73e9..66398940 100644
--- a/src/glum/_glm.py
+++ b/src/glum/_glm.py
@@ -1972,7 +1972,9 @@ def _set_up_and_check_fit_args(
 
                 # Backwards compatibility
                 if isinstance(X, pd.DataFrame):
-                    self.feature_dtypes_ = X.dtypes.to_dict()
+                    with warnings.catch_warnings():
+                        warnings.filterwarnings("ignore")
+                        self.feature_dtypes_ = X.dtypes.to_dict()
 
                 X = cast(nw.DataFrame, nw.from_native(X))  # avoid inferring `Never`
 
diff --git a/tests/glm/test_glm_regressor.py b/tests/glm/test_glm_regressor.py
index 351d1077..30f7bcfd 100644
--- a/tests/glm/test_glm_regressor.py
+++ b/tests/glm/test_glm_regressor.py
@@ -1212,10 +1212,11 @@ def test_predict_list_categorical():
     df["x"] = df["x"].astype("category")
     df["y"] = df["x"].map({v: k + 1 for k, v in enumerate(letters)})
 
-    regressor = GeneralizedLinearRegressor(alpha=[0, 2], alpha_search=True)
-    regressor = regressor.fit(df[["x"]], df["y"])
-
-    candidate = regressor.predict(df[["x"]], alpha=0)
+    candidate = (
+        GeneralizedLinearRegressor(alpha=[0, 2], alpha_search=True, fit_intercept=False)
+        .fit(df[["x"]], df["y"])
+        .predict(df[["x"]], alpha=0)
+    )
 
     np.testing.assert_allclose(candidate, df["y"])