Update README.md

README.md

@@ -16,7 +16,7 @@ tags:
 </div>
 
 <p align="center">
-<a href="XXXX" target="_blank">MiniCPM 技术报告 Technical Report</a> |
+<a href="https://shengdinghu.notion.site/MiniCPM-c805a17c5c8046398914e47f0542095a?pvs=4" target="_blank">MiniCPM 技术报告</a><a href="https://shengdinghu.notion.site/MiniCPM-Unveiling-the-Potential-of-End-side-Large-Language-Models-d4d3a8c426424654a4e80e42a711cb20?pvs=4" target="_blank"> Technical Report</a> |
 <a href="https://github.com/OpenBMB/OmniLMM/" target="_blank">OmniLMM 多模态模型 Multi-modal Model</a> |
 <a href="https://luca.cn/" target="_blank">CPM-C 千亿模型试用 ~100B Model Trial </a> 
 </p>
@@ -51,9 +51,18 @@ We release all model parameters for research and limited commercial use. We also
 - The INT4 quantized version **MiniCPM-2B-SFT/DPO-Int4** based on MiniCPM-2B-SFT/DPO
 - Mobile phone application based on MLC-LLM and LLMFarm. Both language model and multimodel model can conduct inference on smartphones.
 
+### 评测结果 Evaluation Results
 
+  详细的评测结果位于[github仓库](https://github.com/OpenBMB/MiniCPM?tab=readme-ov-file#%E8%AF%84%E6%B5%8B%E7%BB%93%E6%9E%9C)
 
-### 局限性 Limitations：
+  Detailed evaluation results are in [github repo](https://github.com/OpenBMB/MiniCPM/blob/main/README-en.md#evaluation-results)
+
+  注意：我们发现使用Huggingface生成质量略差于vLLM，因此推荐使用vLLM进行测试。我们正在排查原因。
+
+  Notice: We discovered that the quality of Huggingface generation is slightly lower than vLLM, thus benchmarking using vLLM is recommended. 
+  We are investigating the cause now.
+
+### 局限性 Limitations
 
 - 受限于模型规模，模型可能出现幻觉性问题。其中由于DPO模型生成的回复内容更长，更容易出现幻觉。我们也将持续进行MiniCPM模型的迭代改进；
 - 为了保证在学术研究用途上模型的通用性，我们未对模型进行任何身份认同训练。同时由于我们用ShareGPT开源语料作为部分训练数据，模型可能会输出类似GPT系列模型的身份认同信息；
@@ -130,8 +139,8 @@ print(responds)
 
 ## 工作引用 Citation
 
-* 如果觉得MiniCPM有助于您的工作，请考虑引用下列[技术报告](todo)
-* Please cite our [techinical report]() if you find our work valuable.
+* 如果觉得MiniCPM有助于您的工作，请考虑引用下列[技术报告](https://shengdinghu.notion.site/MiniCPM-c805a17c5c8046398914e47f0542095a?pvs=4)
+* Please cite our [techinical report](https://shengdinghu.notion.site/MiniCPM-Unveiling-the-Potential-of-End-side-Large-Language-Models-d4d3a8c426424654a4e80e42a711cb20?pvs=4) if you find our work valuable.
 
 ```
 @inproceedings{minicpm2024,
@@ -140,5 +149,3 @@ print(responds)
  year={2024}
 }
 ```
-
-