Update README.md

README.md

@@ -9,26 +9,19 @@ inference: false
 
 ## 更新信息
 
-**[2024/03/25]** 发布XVERSE-65B-Chat-GPTQ-Int4量化模型，支持vLLM推理xverse-65b量化模型。
-
-**[2023/12/08]** 发布 **XVERSE-65B-2** 底座模型，该模型在前一版本的基础上进行了 **Continual Pre-Training**，训练总 token 量达到 **3.2** 万亿；模型各方面的能力均得到提升，尤其是数学和代码能力，在 GSM8K 上提升 **20**%，HumanEval 上提升 **41**%。 
-**[2023/11/29]** 更新模型架构及更多底座数据的相关信息。  
-
-**[2023/11/24]** 更新预训练数据的相关信息。  
-
-**[2023/11/06]** 发布 65B 尺寸的 XVERSE-65B 底座模型。  
+- **[2024/03/25]** 发布XVERSE-65B-Chat-GPTQ-Int4量化模型，支持vLLM推理xverse-65b量化模型。
+- **[2023/12/08]** 发布 **XVERSE-65B-2** 底座模型，该模型在前一版本的基础上进行了 **Continual Pre-Training**，训练总 token 量达到 **3.2** 万亿；模型各方面的能力均得到提升，尤其是数学和代码能力，在 GSM8K 上提升 **20**%，HumanEval 上提升 **41**%。
+- **[2023/11/29]** 更新模型架构及更多底座数据的相关信息。
+- **[2023/11/24]** 更新预训练数据的相关信息。
+- **[2023/11/06]** 发布 65B 尺寸的 XVERSE-65B 底座模型。  
 
 ## Update Information
 
-**[2024/03/25] ** Release the XVERSE-65B-Chat-GPTQ-Int4 quantification model, supporting vLLM inference for the xverse-65b quantification model.
-
-**[2023/12/08]** Released the **XVERSE-65B-2** base model. This model builds upon its predecessor through **Continual Pre-Training**, reaching a total training volume of **3.2** trillion tokens. It exhibits enhancements in all capabilities, particularly in mathematics and coding skills, with a **20%** improvement on the GSM8K benchmark and a **41%** increase on HumanEval. 
-
-**[2023/11/29]** Update model architecture and additional pre-training data information.  
-
-**[2023/11/24]** Update the related information of the pre-training data.  
-
-**[2023/11/06]** Released the XVERSE-65B base model.  
+- **[2024/03/25] ** Release the XVERSE-65B-Chat-GPTQ-Int4 quantification model, supporting vLLM inference for the xverse-65b quantification model.
+- **[2023/12/08]** Released the **XVERSE-65B-2** base model. This model builds upon its predecessor through **Continual Pre-Training**, reaching a total training volume of **3.2** trillion tokens. It exhibits enhancements in all capabilities, particularly in mathematics and coding skills, with a **20%** improvement on the GSM8K benchmark and a **41%** increase on HumanEval.
+- **[2023/11/29]** Update model architecture and additional pre-training data information.
+- **[2023/11/24]** Update the related information of the pre-training data.
+- **[2023/11/06]** Released the XVERSE-65B base model.  
 
 ## 模型介绍
 
@@ -98,7 +91,7 @@ for output in outputs:
 
 ## Usage
 
-We demonstrated how to use 'vllm' to run the XVERSE-65B-Chat GPTQ Int4 quantization model:
+We demonstrated how to use 'vllm' to run the XVERSE-65B-Chat-GPTQ-Int4 quantization model:
 
 ```python
 from vllm import LLM, SamplingParams