Fix issue with zeroshot topic modeling missing outlier (#1957)

bertopic/_bertopic.py

@@ -3679,15 +3679,20 @@ def _combine_zeroshot_topics(self,
 
         cluster_indices = list(documents.Old_ID.values)
         cluster_names = list(merged_model.topic_labels_.values())[len(set(y)):]
-        cluster_topics = [cluster_names[topic + self._outliers] for topic in documents.Topic.values]
+        if self._outliers:
+            cluster_topics = [cluster_names[topic] if topic != -1 else "Outliers" for topic in documents.Topic.values]
+        else:
+            cluster_topics = [cluster_names[topic] for topic in documents.Topic.values]
 
         df = pd.DataFrame({
             "Indices": zeroshot_indices + cluster_indices,
             "Label": zeroshot_topics + cluster_topics}
         ).sort_values("Indices")
         reverse_topic_labels = dict((v, k) for k, v in merged_model.topic_labels_.items())
+        if self._outliers:
+            reverse_topic_labels["Outliers"] = -1
         df.Label = df.Label.map(reverse_topic_labels)
-        merged_model.topics_ = df.Label.values
+        merged_model.topics_ = df.Label.astype(int).tolist()
 
         # Update the class internally
         has_outliers = bool(self._outliers)