diff --git a/ldm/modules/embedding_manager.py b/ldm/modules/embedding_manager.py
index af9383bbd6..8b37ec602a 100644
--- a/ldm/modules/embedding_manager.py
+++ b/ldm/modules/embedding_manager.py
@@ -366,12 +366,12 @@ class EmbeddingManager(nn.Module):
         '''
         embedding_info = {}
         if isinstance(list(embedding_ckpt['string_to_token'].values())[0],torch.Tensor):
-            print('>> Detected .pt file variant 1') # example at https://github.com/invoke-ai/InvokeAI/issues/1829
-            for token in list(embedding_ckpt['string_to_token'].keys()):
-                embedding_info['name'] = token if token != '*' else os.path.basename(os.path.splitext(embedding_file)[0])
-                embedding_info['embedding'] = embedding_ckpt['string_to_param'].state_dict()[token]
-                embedding_info['num_vectors_per_token'] = embedding_info['embedding'].shape[0]
-                embedding_info['token_dim'] = embedding_info['embedding'].size()[0]
+            print(f'>> Variant Embedding Detected. Parsing: {embedding_file}') # example at https://github.com/invoke-ai/InvokeAI/issues/1829
+            token = list(embedding_ckpt['string_to_token'].keys())[0]
+            embedding_info['name'] = os.path.basename(os.path.splitext(embedding_file)[0])
+            embedding_info['embedding'] = embedding_ckpt['string_to_param'].state_dict()[token]
+            embedding_info['num_vectors_per_token'] = embedding_info['embedding'].shape[0]
+            embedding_info['token_dim'] = embedding_info['embedding'].size()[0]
         else:
             print('>> Invalid embedding format')
             embedding_info = None