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README.md
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@@ -50,7 +50,6 @@
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25) - [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [Evaluation](#evaluation)
- [MiniCPM-V 2.0](#minicpm-v-20) - [MiniCPM-V 2.0](#minicpm-v-20)
- [Online Demo](#online-demo) - [Online Demo](#online-demo)
- [Install](#install) - [Install](#install)
@@ -86,7 +85,7 @@
- 🚀 **Efficient Deployment.** - 🚀 **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 **150x acceleration in end-side MLLM image encoding** and a **3x speedup in language decoding**. 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 ### Evaluation <!-- omit in toc -->
<div align="center"> <div align="center">
<img src=assets/MiniCPM-Llama3-V-2.5-peformance.png width=66% /> <img src=assets/MiniCPM-Llama3-V-2.5-peformance.png width=66% />

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README_en.md
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- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25) - [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [Evaluation](#evaluation)
- [MiniCPM-V 2.0](#minicpm-v-20) - [MiniCPM-V 2.0](#minicpm-v-20)
- [Online Demo](#online-demo) - [Online Demo](#online-demo)
- [Install](#install) - [Install](#install)
@@ -86,7 +85,7 @@
- 🚀 **Efficient Deployment.** - 🚀 **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 **150x acceleration in end-side MLLM image encoding** and a **3x speedup in language decoding**. 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 ### Evaluation <!-- omit in toc -->
<div align="center"> <div align="center">
<img src=assets/MiniCPM-Llama3-V-2.5-peformance.png width=66% /> <img src=assets/MiniCPM-Llama3-V-2.5-peformance.png width=66% />

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README_zh.md
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## 目录 <!-- omit in toc --> ## 目录 <!-- omit in toc -->
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25) - [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [性能评估](#性能评估)
- [典型示例](#典型示例)
- [MiniCPM-V 2.0](#minicpm-v-20) - [MiniCPM-V 2.0](#minicpm-v-20)
- [Online Demo](#online-demo) - [Online Demo](#online-demo)
- [安装](#安装) - [安装](#安装)
@@ -92,7 +90,7 @@
### 性能评估 ### 性能评估 <!-- omit in toc -->
<div align="center"> <div align="center">
<img src="assets/MiniCPM-Llama3-V-2.5-peformance.png" width="66%" /> <img src="assets/MiniCPM-Llama3-V-2.5-peformance.png" width="66%" />
@@ -381,7 +379,7 @@
</div> </div>
### 典型示例 ### 典型示例 <!-- omit in toc -->
<table align="center"> <table align="center">
<p align="center"> <p align="center">
<img src="assets/minicpmv-llama3-v2.5/cases_all.png" width=95%/> <img src="assets/minicpmv-llama3-v2.5/cases_all.png" width=95%/>