diff --git a/bertopic/_bertopic.py b/bertopic/_bertopic.py
index 90ec3fbe..f67c99fb 100644
--- a/bertopic/_bertopic.py
+++ b/bertopic/_bertopic.py
@@ -3783,19 +3783,34 @@ def _reduce_dimensionality(
         if partial_fit:
             if hasattr(self.umap_model, "partial_fit"):
                 self.umap_model = self.umap_model.partial_fit(embeddings)
+                umap_embeddings = self.umap_model.transform(embeddings)
             elif self.topic_representations_ is None:
                 self.umap_model.fit(embeddings)
+                umap_embeddings = self.umap_model.transform(embeddings)
+            else:
+                if hasattr(self.umap_model, "fit_transform"):
+                    umap_embeddings = self.umap_model.fit_transform(embeddings)
+                else:
+                    self.umap_model.fit(embeddings)
+                    umap_embeddings = self.umap_model.transform(embeddings)
 
         # Regular fit
         else:
             try:
                 # cuml umap needs y to be an numpy array
                 y = np.array(y) if y is not None else None
-                self.umap_model.fit(embeddings, y=y)
+                if hasattr(self.umap_model, "fit_transform"):
+                    umap_embeddings = self.umap_model.fit_transform(embeddings, y=y)
+                else:
+                    self.umap_model.fit(embeddings)
+                    umap_embeddings = self.umap_model.transform(embeddings, y=y)
             except TypeError:
-                self.umap_model.fit(embeddings)
+                if hasattr(self.umap_model, "fit_transform"):
+                    umap_embeddings = self.umap_model.fit_transform(embeddings)
+                else:
+                    self.umap_model.fit(embeddings)
+                    umap_embeddings = self.umap_model.transform(embeddings)
 
-        umap_embeddings = self.umap_model.transform(embeddings)
         logger.info("Dimensionality - Completed \u2713")
         return np.nan_to_num(umap_embeddings)