Update README.md

README.md

@@ -1063,14 +1063,16 @@ piccolo是一个通用embedding模型, 由来自商汤科技的通用模型组
 目前，我们提供了piccolo-base-zh和piccolo-large-zh两个模型。
 
 piccolo is a general text embedding model, powered by General Model Group from SenseTime Research. 
-Based on BERT framework, piccolo is trained using a two stage pipeline. On the first stage, we collect and crawl 400 million weakly supervised Chinese text pairs from the Internet, 
+Inspired from E5 and GTE, piccolo is trained using a two stage pipeline. On the first stage, we collect and crawl 400 million weakly supervised Chinese text pairs from the Internet, 
 and train the model with the pair(text and text pos) softmax contrastive loss. 
 On the second stage, we collect 20 million human labeled chinese text pairs from the open-source dataset, and finetune the model with tiplet (text, text_pos, text_neg) contrastive loss. 
 Currently here we offer two different sizes of models, including piccolo-base-zh, piccolo-large-zh. 
 
 ## Metric
 我们将piccolo与其他的开源embedding模型在CMTEB榜单上进行了比较，请参考CMTEB榜单。我们在eval文件夹中提供了复现结果的脚本。
-We compared the performance of the piccolo with other embedding models on the C-MTEB benchmark. please refer to the C-MTEB leaderboard. wo provide scripts in "eval" folder for results reproducing.
+
+We compared the performance of the piccolo with other embedding models on the C-MTEB benchmark. please refer to the C-MTEB leaderboard. 
+we provide scripts in "eval" folder for results reproducing.
 
 
 | Model Name | Model Size (GB) | Dimension | Sequence Length | Average (35) | Classification (9) | Clustering (4) | Pair Classification (2) | Reranking (4) | Retrieval (8) | STS (8) |