diff --git a/src/spikeinterface/sorters/internal/spyking_circus2.py b/src/spikeinterface/sorters/internal/spyking_circus2.py
index 0c3b9f95d1..2c297662f4 100644
--- a/src/spikeinterface/sorters/internal/spyking_circus2.py
+++ b/src/spikeinterface/sorters/internal/spyking_circus2.py
@@ -114,7 +114,9 @@ def _run_from_folder(cls, sorter_output_folder, params, verbose):
 
         ## We get the labels for our peaks
         mask = peak_labels > -1
-        sorting = NumpySorting.from_times_labels(selected_peaks["sample_index"][mask], peak_labels[mask], sampling_rate)
+        sorting = NumpySorting.from_times_labels(
+            selected_peaks["sample_index"][mask], peak_labels[mask].astype(int), sampling_rate
+        )
         clustering_folder = sorter_output_folder / "clustering"
         if clustering_folder.exists():
             shutil.rmtree(clustering_folder)
diff --git a/src/spikeinterface/sortingcomponents/benchmark/benchmark_clustering.py b/src/spikeinterface/sortingcomponents/benchmark/benchmark_clustering.py
index d68b8e5449..bd413417bf 100644
--- a/src/spikeinterface/sortingcomponents/benchmark/benchmark_clustering.py
+++ b/src/spikeinterface/sortingcomponents/benchmark/benchmark_clustering.py
@@ -524,7 +524,7 @@ def plot_statistics(self, metric="cosine", annotations=True, detect_threshold=5)
             template_real = template_real.reshape(template_real.size, 1).T
 
             if metric == "cosine":
-                dist = sklearn.metrics.pairwise.cosine_similarity(template, template_real, metric).flatten().tolist()
+                dist = sklearn.metrics.pairwise.cosine_similarity(template, template_real).flatten().tolist()
             else:
                 dist = sklearn.metrics.pairwise_distances(template, template_real, metric).flatten().tolist()
             res += dist