Update README.md

README.md

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     </a>
 </div>
 
-# Introduction
 
 
+# A New Frontier in Code Retrieval via Adaptive Cross-Attention Pooling
 
-## C2LLM: Advanced Code Embeddings for Deep Semantic Understanding
-
-**C2LLMs (Code Contrastive Large Language Model)** is a powerful new model for generating code embeddings, designed to capture the deep semantics of source code. 
+**C2LLMs (Code Contrastive Large Language Models)** are powerful new models for generating code embeddings, designed to capture the deep semantics of source code. 
 
 #### Key Features
 
@@ -27,7 +25,7 @@ C2LLM is designed to be a go-to model for tasks like code search and Retrieval-A
 
 ## Usage (**HuggingFace Transformers**)
 
-```plain
+```Python
 from transformers import AutoModel, AutoTokenizer
 import torch
 
@@ -118,7 +116,7 @@ embeddings = model.encode(sentences)
 
 ## Evaluation (**MTEB**)
 
-```plain
+```python
 from sentence_transformers import SentenceTransformer
 from mteb.models import ModelMeta
 from mteb.cache import ResultCache
@@ -146,4 +144,4 @@ If you find this project helpful, please give it a star. It means a lot to us!
 
 ## Correspondence to 
 
-Jin Qin (qj431428@antgroup.com), Zihan Liao (liaozihan.lzh@antgroup.com), Ziyin Zhang (zhangziying.zzy@antgroup.com), Hang Yu (hyu.hugo@antgroup.com), Peng Di (dipeng.dp@antgroup.com)
+Jin Qin (qj431428@antgroup.com), Zihan Liao (liaozihan.lzh@antgroup.com), Ziyin Zhang (zhangziying.zzy@antgroup.com), Hang Yu (hyu.hugo@antgroup.com), Peng Di (dipeng.dp@antgroup.com)