Upload README.md

README.md

@@ -1059,15 +1059,18 @@ model-index:
 
 **[2024-04-22]** 
 
-piccolo-large-zh-v2 目前在C-MTEB榜单取得第一名，领先上一名BERT模型约1.9个点。   
+piccolo-large-zh-v2 目前在C-MTEB榜单取得第一名，领先上一名BERT模型约1.9个点。  
+   
 piccolo-large-zh-v2 currently ranks first on the C-MTEB list, leading the previous BERT model by about 1.9 points.
 
 ## piccolo-large-zh-v2
 
-piccolo-large-zh-v2 是一个通用embedding模型(中文), 由来自商汤科技的通用模型组完成训练，此次piccolo升级旨在更多地关注通用的下游finetune方式。  
+piccolo-large-zh-v2 是一个通用embedding模型(中文), 由来自商汤科技的通用模型组完成训练，此次piccolo升级旨在更多地关注通用的下游finetune方式。我们将在近期更新我们的技术报告，同时详细技术细节也将在商汤4.23技术交流日披露。
+
+piccolo-large-zh-v2 is an embedding model (Chinese), trained by the general model group from SenseTime Reserach. This piccolo upgrade aims to pay more attention to the general downstream finetune method.We will update our technical report in the near future, and detailed technical details will also be disclosed on SenseTime 4.23 Tech Day.
+
+
+## Usage
 目前该模型暂时需要通过API来进行访问: https://platform.sensenova.cn/doc?path=/chat/Embeddings/Embeddings.md  
-我们将在近期更新我们的技术报告，同时详细技术细节也将在商汤4.23技术交流日披露。
 
-piccolo-large-zh-v2 is an embedding model (Chinese), trained by the general model group from SenseTime Reserach. This piccolo upgrade aims to pay more attention to the general downstream finetune method.  
 Currently, the model needs to be accessed through API: https://platform.sensenova.cn/doc?path=/chat/Embeddings/Embeddings.md  
-We will update our technical report in the near future, and detailed technical details will also be disclosed on SenseTime 4.23 Tech Day.