Update README.md

README.md

@@ -454,7 +454,7 @@ Trained with a **Matryoshka loss**, allowing embeddings to be truncated with min
 
 ```
 SentenceTransformer(
-  (0): Transformer({'max_seq_length': 256, 'do_lower_case': False}) with Transformer model: RobertaModel 
+  (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: RobertaModel 
   (1): Pooling({'word_embedding_dimension': 768, 'pooling_mode_cls_token': False, 'pooling_mode_mean_tokens': True, 'pooling_mode_max_tokens': False, 'pooling_mode_mean_sqrt_len_tokens': False, 'pooling_mode_weightedmean_tokens': False, 'pooling_mode_lasttoken': False, 'include_prompt': True})
 )
 ```
@@ -515,8 +515,8 @@ for doc, score in zip(sorted_docs, sorted_scores):
 
 | Model               | dim_768    | dim_512    | dim_256    | dim_128    | dim_64     |
 |:--------------------|:-----------|:-----------|:-----------|:-----------|:-----------|
-| vietnamese-bi-encoder   | 0.4645     | 0.4628     | 0.4494     | 0.4233     | 0.3744     |
-| sup-SimCSE-VietNamese-phobert-base   | 0.4033     | 0.3902     | 0.3835     | 0.3785     | 0.3695      |
+| bkai-foundation-models/vietnamese-bi-encoder   | 0.4645     | 0.4628     | 0.4494     | 0.4233     | 0.3744     |
+| VoVanPhuc/sup-SimCSE-VietNamese-phobert-base   | 0.4033     | 0.3902     | 0.3835     | 0.3785     | 0.3695      |
 | hiieu/halong_embedding  | 0.6242     | 0.6134      | 0.5983     | 0.5878     | 0.5762     |
 | quanghuy123/LEGAL_EMBEDDING  | 0.8112      | 0.8074     | 0.8022     | 0.7937     | 0.7718     |
 ## Citation