diff --git a/src/topicgpt/TopicGPT.py b/src/topicgpt/TopicGPT.py
index 331017a..2e30856 100644
--- a/src/topicgpt/TopicGPT.py
+++ b/src/topicgpt/TopicGPT.py
@@ -23,12 +23,12 @@ def __init__(self,
              api_key: str = "",
              azure_endpoint: dict = {},
              n_topics: int = None,
-             openai_prompting_model: str = "gpt-3.5-turbo-16k",
+             openai_prompting_model: str = "gpt-4o-mini",
              max_number_of_tokens: int = 16384,
              corpus_instruction: str = "",
              document_embeddings: np.ndarray = None,
              vocab_embeddings: dict[str, np.ndarray] = None,
-             embedding_model: str = "text-embedding-ada-002",
+             embedding_model: str = "text-embedding-3-small",
              max_number_of_tokens_embedding: int = 8191,
              use_saved_embeddings: bool = True,
              path_saved_embeddings: str = embeddings_path,
diff --git a/src/topicgpt/TopicRepresentation.py b/src/topicgpt/TopicRepresentation.py
index 89b152a..7cad155 100644
--- a/src/topicgpt/TopicRepresentation.py
+++ b/src/topicgpt/TopicRepresentation.py
@@ -298,7 +298,7 @@ def extract_topics_no_new_vocab_computation(corpus: list[str], vocab: list[str],
     centroid_arr = np.array(list(centroid_dict.values()))
     if centroid_arr.ndim == 1:
         centroid_arr = centroid_arr.reshape(-1, 1)
-    dim_red_centroids = umap_mapper.transform(np.array(list(centroid_dict.values())))  # map the centroids to low dimensional space
+    dim_red_centroids = umap_mapper.transform(centroid_arr)  # map the centroids to low dimensional space
 
     dim_red_centroid_dict = {label: centroid for label, centroid in zip(centroid_dict.keys(), dim_red_centroids)}