From cdac9359f0dded82b28a39cf1373a6b7a74e0f94 Mon Sep 17 00:00:00 2001
From: yiranyyu <2606375857@qq.com>
Date: Sat, 25 May 2024 11:44:33 +0800
Subject: [PATCH] update readme

---
 README.md    | 2 +-
 README_en.md | 2 +-
 2 files changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 6681ed1..bf996e9 100644
--- a/README.md
+++ b/README.md
@@ -77,7 +77,7 @@
   Thanks to the strong multilingual capabilities of Llama 3 and the cross-lingual generalization technique from [VisCPM](https://github.com/OpenBMB/VisCPM), MiniCPM-Llama3-V 2.5 extends its bilingual (Chinese-English) multimodal capabilities to **over 30 languages including German, French, Spanish, Italian, Russian etc.** [All Supported Languages](./assets/minicpm-llama-v-2-5_languages.md).
 
 - 🚀 **Efficient Deployment.**
-  MiniCPM-Llama3-V 2.5 systematically employs **model quantization, CPU optimizations, NPU optimizations and compilation optimizations**, achieving high-efficiency deployment on edge devices. For mobile phones with Qualcomm chips, we have integrated the NPU acceleration framework QNN into llama.cpp for the first time. After systematic optimization, MiniCPM-Llama3-V 2.5 has realized a **150-fold acceleration in multimodal large model end-side image encoding** and a **3-fold increase in language decoding speed**.
+  MiniCPM-Llama3-V 2.5 systematically employs **model quantization, CPU optimizations, NPU optimizations and compilation optimizations**, achieving high-efficiency deployment on edge devices. For mobile phones with Qualcomm chips, we have integrated the NPU acceleration framework QNN into llama.cpp for the first time. After systematic optimization, MiniCPM-Llama3-V 2.5 has realized a **150x acceleration in end-side MLLM image encoding** and a **3x speedup in language decoding**.
 
 ### Evaluation 
 
diff --git a/README_en.md b/README_en.md
index 6681ed1..bf996e9 100644
--- a/README_en.md
+++ b/README_en.md
@@ -77,7 +77,7 @@
   Thanks to the strong multilingual capabilities of Llama 3 and the cross-lingual generalization technique from [VisCPM](https://github.com/OpenBMB/VisCPM), MiniCPM-Llama3-V 2.5 extends its bilingual (Chinese-English) multimodal capabilities to **over 30 languages including German, French, Spanish, Italian, Russian etc.** [All Supported Languages](./assets/minicpm-llama-v-2-5_languages.md).
 
 - 🚀 **Efficient Deployment.**
-  MiniCPM-Llama3-V 2.5 systematically employs **model quantization, CPU optimizations, NPU optimizations and compilation optimizations**, achieving high-efficiency deployment on edge devices. For mobile phones with Qualcomm chips, we have integrated the NPU acceleration framework QNN into llama.cpp for the first time. After systematic optimization, MiniCPM-Llama3-V 2.5 has realized a **150-fold acceleration in multimodal large model end-side image encoding** and a **3-fold increase in language decoding speed**.
+  MiniCPM-Llama3-V 2.5 systematically employs **model quantization, CPU optimizations, NPU optimizations and compilation optimizations**, achieving high-efficiency deployment on edge devices. For mobile phones with Qualcomm chips, we have integrated the NPU acceleration framework QNN into llama.cpp for the first time. After systematic optimization, MiniCPM-Llama3-V 2.5 has realized a **150x acceleration in end-side MLLM image encoding** and a **3x speedup in language decoding**.
 
 ### Evaluation