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+- English
+- 中文
+- 한국어
+- 日本語
+- Deutsch
+- Français
+- Português
+- Español
+- မြန်မာဘာသာ
+- ไทย
+- Tiếng Việt
+- Türkçe
+- ܣܘܪܝܝܐ
+- العربية
+- हिन्दी
+- বাংলা
+- नेपाली
+- Türkmençe
+- Тоҷикӣ
+- Кыргызча
+- Русский
+- Українська
+- Беларуская
+- ქართული
+- Azərbaycanca
+- Հայերեն
+- Polski
+- Lietuvių
+- Eesti
+- Latviešu
+- Čeština
+- Slovenčina
+- Magyar
+- Slovenščina
+- Hrvatski
+- Bosanski
+- Crnogorski
+- Српски
+- Shqip
+- Română
+- Български
+- Македонски
+
+
+## 支持语言
+
+英语
+
+中文
+
+韩语
+
+日语
+
+德语
+
+法语
+
+葡萄牙语
+
+西班牙语
+
+缅甸语
+
+泰语
+
+越南语
+
+土耳其语
+
+叙利亚语
+
+阿拉伯语
+
+印地语
+
+孟加拉语
+
+尼泊尔语
+
+土库曼语
+
+塔吉克语
+
+吉尔吉斯语
+
+俄语
+
+乌克兰语
+
+白俄罗斯语
+
+格鲁吉亚语
+
+阿塞拜疆语
+
+亚美尼亚语
+
+波兰语
+
+立陶宛语
+
+爱沙尼亚语
+
+拉脱维亚语
+
+捷克语
+
+斯洛伐克语
+
+匈牙利语
+
+斯洛文尼亚语
+
+克罗地亚语
+
+波斯尼亚语
+
+黑山语
+
+塞尔维亚语
+
+阿尔巴尼亚语
+
+罗马尼亚语
+
+保加利亚
+
+马其顿语
+
+
+
+## Supported Languages
+
+English  
+Chinese  
+Korean  
+Japanese  
+German  
+French  
+Portuguese  
+Spanish  
+Burmese  
+Thai  
+Vietnamese  
+Turkish  
+Syriac  
+Arabic  
+Hindi  
+Bengali  
+Nepali  
+Turkmen  
+Tajik  
+Kyrgyz  
+Russian  
+Ukrainian  
+Belarusian  
+Georgian  
+Azerbaijani  
+Armenian  
+Polish  
+Lithuanian  
+Estonian  
+Latvian  
+Czech  
+Slovak  
+Hungarian  
+Slovenian  
+Croatian  
+Bosnian  
+Montenegrin  
+Serbian  
+Albanian  
+Romanian  
+Bulgarian  
+Macedonian
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diff --git a/docs/minicpm_llama3_v2dot5.md b/docs/minicpm_llama3_v2dot5.md
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+++ b/docs/minicpm_llama3_v2dot5.md
@@ -15,7 +15,7 @@
   Leveraging the latest [RLAIF-V](https://github.com/RLHF-V/RLAIF-V/) method (the newest technique in the [RLHF-V](https://github.com/RLHF-V) [CVPR'24] series), MiniCPM-Llama3-V 2.5 exhibits more trustworthy behavior. It achieves a **10.3%** hallucination rate on Object HalBench, lower than GPT-4V-1106 (13.6%), achieving the best-level performance within the open-source community. [Data released](https://huggingface.co/datasets/openbmb/RLAIF-V-Dataset).
 
 - 🌏 **Multilingual Support.**
-  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, Korean etc.** [All Supported Languages](./assets/minicpm-llama-v-2-5_languages.md).
+  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, Korean etc.** [All Supported Languages](../docs/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 end-side 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**.