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README.md
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@@ -62,7 +62,7 @@ Join our <a href="docs/wechat.md" target="_blank"> 💬 WeChat</a>
- [MiniCPM-V 2.6](#minicpm-v-26)
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [MiniCPM-V 2.0](#minicpm-v-20)
- [Chat with Our Demo on Gradio](#chat-with-our-demo-on-gradio)
- [Chat with Our Demo on Gradio 🤗](#chat-with-our-demo-on-gradio-)
- [Install](#install)
- [Inference](#inference)
- [Model Zoo](#model-zoo)
@@ -1226,9 +1226,9 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
| OmniLMM-12B | [Document](./omnilmm_en.md) |
## Chat with Our Demo on Gradio
## Chat with Our Demo on Gradio 🤗
We provide online and local demos powered by HuggingFace [Gradio](https://github.com/gradio-app/gradio), the most popular model deployment framework nowadays. It supports streaming outputs, progress bars, queuing, alerts, and other useful features.
We provide online and local demos powered by Hugging Face **Gradio** <a href='https://github.com/gradio-app/gradio'><img src='https://img.shields.io/github/stars/gradio-app/gradio'></a>, the most popular model deployment framework nowadays. It supports streaming outputs, progress bars, queuing, alerts, and other useful features.
### Online Demo <!-- omit in toc -->

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README_en.md
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@@ -62,7 +62,7 @@ Join our <a href="docs/wechat.md" target="_blank"> 💬 WeChat</a>
- [MiniCPM-V 2.6](#minicpm-v-26)
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [MiniCPM-V 2.0](#minicpm-v-20)
- [Chat with Our Demo on Gradio](#chat-with-our-demo-on-gradio)
- [Chat with Our Demo on Gradio 🤗](#chat-with-our-demo-on-gradio-)
- [Install](#install)
- [Inference](#inference)
- [Model Zoo](#model-zoo)
@@ -93,7 +93,7 @@ Join our <a href="docs/wechat.md" target="_blank"> 💬 WeChat</a>
- 💪 **Strong OCR Capability and Others.**
MiniCPM-V 2.6 can process images with any aspect ratio and up to 1.8 million pixels (e.g., 1344x1344). It achieves **state-of-the-art performance on OCRBench, surpassing proprietary models such as GPT-4o, GPT-4V, and Gemini 1.5 Pro**.
Based on the the latest [RLAIF-V](https://github.com/RLHF-V/RLAIF-V/) and [VisCPM](https://github.com/OpenBMB/VisCPM) techniques, it features **trustworthy behaviors**, with significantly lower hallucination rates than GPT-4o and GPT-4V on Object HalBench, and supports **multilingual capabilities** on English, Chiense, German, French, Italian, Korean, etc.
Based on the the latest [RLAIF-V](https://github.com/RLHF-V/RLAIF-V/) and [VisCPM](https://github.com/OpenBMB/VisCPM) techniques, it features **trustworthy behaviors**, with significantly lower hallucination rates than GPT-4o and GPT-4V on Object HalBench, and supports **multilingual capabilities** on English, Chinese, German, French, Italian, Korean, etc.
- 🚀 **Superior Efficiency.**
@@ -380,7 +380,7 @@ MiniCPM-V 2.6 can be easily used in various ways: (1) [llama.cpp](https://github
</table>
</div>
* We evaluate this benchmark using chain-of-thought prompting.
* We evaluate this benchmark using chain-of-thought prompting. Specifically, for MME, we used this technique only for the Cognition set.
<sup>+</sup> Token Density: number of pixels encoded into each visual token at maximum resolution, i.e., # pixels at maximum resolution / # visual tokens.
@@ -1226,9 +1226,9 @@ We deploy MiniCPM-V 2.0 on end devices. The demo video is the raw screen recordi
| OmniLMM-12B | [Document](./omnilmm_en.md) |
## Chat with Our Demo on Gradio
## Chat with Our Demo on Gradio 🤗
We provide online and local demos powered by HuggingFace [Gradio](https://github.com/gradio-app/gradio), the most popular model deployment framework nowadays. It supports streaming outputs, progress bars, queuing, alerts, and other useful features.
We provide online and local demos powered by Hugging Face **Gradio** <a href='https://github.com/gradio-app/gradio'><img src='https://img.shields.io/github/stars/gradio-app/gradio'></a>, the most popular model deployment framework nowadays. It supports streaming outputs, progress bars, queuing, alerts, and other useful features.
### Online Demo <!-- omit in toc -->

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README_zh.md
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@@ -67,7 +67,7 @@
- [MiniCPM-V 2.6](#minicpm-v-26)
- [MiniCPM-Llama3-V 2.5](#minicpm-llama3-v-25)
- [MiniCPM-V 2.0](#minicpm-v-20)
- [Demo](#demo)
- [Gradio Demo 🤗](#gradio-demo-)
- [安装](#安装)
- [推理](#推理)
- [模型库](#模型库)
@@ -1232,9 +1232,9 @@
| OmniLMM-12B | [文档](./omnilmm.md) |
## Demo
## Gradio Demo 🤗
我们提供由 Hugging Face [Gradio](https://github.com/gradio-app/gradio) 支持的在线和本地 Demo。Gradio 是目前最流行的模型部署框架，支持流式输出、进度条、process bars 和其他常用功能。
我们提供由 Hugging Face **Gradio** <a href='https://github.com/gradio-app/gradio'><img src='https://img.shields.io/github/stars/gradio-app/gradio'></a> 支持的在线和本地 Demo。Gradio 是目前最流行的模型部署框架，支持流式输出、进度条、process bars 和其他常用功能。
### Online Demo <!-- omit in toc -->