Update README.md

README.md

@@ -77,7 +77,7 @@ Evaluated with [JMTEB](https://github.com/sbintuitions/JMTEB).
 ||||||||||
 |[Ruri-Small](https://huggingface.co/cl-nagoya/ruri-small)|68M|69.41|82.79|76.22|93.00|51.19|62.11|71.53|
 |[Ruri-Base](https://huggingface.co/cl-nagoya/ruri-base)|111M|69.82|82.87|75.58|92.91|54.16|62.38|71.91|
-|[Ruri-Large](https://huggingface.co/cl-nagoya/ruri-large)|337M|73.02|83.13|77.43|92.99|51.82|62.29|73.31|
+|[**Ruri-Large**](https://huggingface.co/cl-nagoya/ruri-large) (this model)|337M|73.02|83.13|77.43|92.99|51.82|62.29|73.31|
 
 
 
@@ -93,16 +93,10 @@ Evaluated with [JMTEB](https://github.com/sbintuitions/JMTEB).
 - **License:** Apache 2.0
 <!-- - **Training Dataset:** Unknown -->
 
-### Model Sources
-
-- **Documentation:** [Sentence Transformers Documentation](https://sbert.net)
-- **Repository:** [Sentence Transformers on GitHub](https://github.com/UKPLab/sentence-transformers)
-- **Hugging Face:** [Sentence Transformers on Hugging Face](https://huggingface.co/models?library=sentence-transformers)
-
 ### Full Model Architecture
 
 ```
-MySentenceTransformer(
+SentenceTransformer(
   (0): Transformer({'max_seq_length': 512, 'do_lower_case': False}) with Transformer model: BertModel 
   (1): Pooling({'word_embedding_dimension': 1024, '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})
 )