diff --git a/README.md b/README.md
index 372c0a6..6d0bce2 100644
--- a/README.md
+++ b/README.md
@@ -1,24 +1,24 @@
 <p align="center">
 <img width="1000px" alt="DeepSeek Coder" src="pictures/logo.png">
 </p>
-<p align="center"><a href="https://www.deepseek.com/">[<img src="pictures/home.png" width="20px"> Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder] | <a href="https://huggingface.co/deepseek-ai">[🤗 Models Download]</a> | <a href="https://discord.gg/fUzxZTrd">[Discord]</a>  |  <a href="https://github.com/guoday/assert/blob/main/QR.png?raw=true">[Wechat(微信)]</a></p>
+<p align="center"><a href="https://www.deepseek.com/">[<img src="pictures/home.png" width="20px"> Homepage]</a> | <a href="https://coder.deepseek.com/">[🤖 Chat with DeepSeek Coder] | <a href="https://huggingface.co/deepseek-ai">[🤗 Models Download]</a> | <a href="https://discord.gg/Tc7c45Zzu5">[Discord]</a>  |  <a href="https://github.com/guoday/assert/blob/main/QR.png?raw=true">[Wechat(微信)]</a></p>
 <hr>
 
 
 ### 1. Introduction of DeepSeek Coder
 
-Deepseek Coder comprises a series of code language models trained on both 87% code and 13% natural language in English and Chinese, with each model pre-trained on 2T tokens. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support  project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks. 
+Deepseek Coder comprises a series of code language models trained on both 87% code and 13% natural language in English and Chinese, with each model pre-trained on 2T tokens. We provide various sizes of the code model, ranging from 1B to 33B versions. Each model is pre-trained on project-level code corpus by employing a window size of 16K and a extra fill-in-the-blank task, to support  project-level code completion and infilling. For coding capabilities, Deepseek Coder achieves state-of-the-art performance among open-source code models on multiple programming languages and various benchmarks.
 
 <p align="center">
 <img src="pictures/result.png" alt="result" width="70%">
 </p>
 
 - **Massive Training Data**: Trained on 2T tokens, including 87% code and 13% linguistic data in both English and Chinese languages.
-  
+
 - **Highly Flexible & Scalable**: Offered in model sizes of 1B, 5.7B, 6.7B and 33B, enabling users to choose the setup most suitable for their requirements.
-  
+
 - **Superior Model Performance**: State-of-the-art performance among publicly available code models on HumanEval, MultiPL-E, MBPP, DS-1000, and APPS benchmarks.
-  
+
 - **Advanced Code Completion Capabilities**: A window size of 16K and a fill-in-the-blank task, supporting project-level code completion and infilling tasks.
 
 
@@ -187,7 +187,7 @@ def load_data():
     X_test = torch.tensor(X_test, dtype=torch.float32)
     y_train = torch.tensor(y_train, dtype=torch.int64)
     y_test = torch.tensor(y_test, dtype=torch.int64)
-    
+
     return X_train, X_test, y_train, y_test
 
 def evaluate_predictions(y_test, y_pred):
@@ -213,7 +213,7 @@ class IrisClassifier(nn.Module):
     def train_model(self, X_train, y_train, epochs, lr, batch_size):
         criterion = nn.CrossEntropyLoss()
         optimizer = optim.Adam(self.parameters(), lr=lr)
-        
+
         # Create DataLoader for batches
         dataset = TensorDataset(X_train, y_train)
         dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=True)
@@ -272,4 +272,3 @@ See the [LICENSE-CODE](LICENSE-CODE) and [LICENSE-MODEL](LICENSE-MODEL) for more
 ### 6. Contact
 
 If you have any questions, please raise an issue or contact us at [agi_code@deepseek.com](mailto:agi_code@deepseek.com).
-