Update README.md

README.md

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 ## Model Summary
 
-FuxiTranyu-8B is a completely open source large language model trained from scratch, with a specific focus on the multilinguality.
-FuxiTranyu-8B was trained on 600B tokens with a much more smooth distribution across languages.
+FuxiTranyu-8B is an **open-source** **multilingual large language model** trained from scratch, with a specific focus on the multilinguality. It is trained on 600B tokens with a balanced data distribution across languages, exhibiting remarkable multilingual performance compared to previous multilingual LLMs like BLOOM-7B, PolyLM-13B. 
 
-We cover 43 natural languages: Arabic, Bengali, Bulgarian, Burmese, Catalan, Chinese, Czech, Dutch, English, Filipino, Finnish, French, German, Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Malay, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Tamil, Tajik, Thai, Turkish, Turkmen, Ukrainian, Urdu, Uzbek, and Vietnamese.
-And also cover 16 programming languages: Java, JavaScript, Python, PHP, C, C++, C#, TypeScript, Go, SQL, Rust, Ruby, Scala, Lua, Assembly, and Visual Basic.
+FuxiTranyu supports 43 natural languages (Arabic, Bengali, Bulgarian, Burmese, Catalan, Chinese, Czech, Dutch, English, Filipino, Finnish, French, German, Greek, Hebrew, Hindi, Hungarian, Indonesian, Italian, Japanese, Kazakh, Khmer, Korean, Kurdish, Kyrgyz, Lao, Malay, Persian, Polish, Portuguese, Romanian, Russian, Spanish, Swedish, Tamil, Tajik, Thai, Turkish, Turkmen, Ukrainian, Urdu, Uzbek, and Vietnamese) and cover 16 programming languages (Java, JavaScript, Python, PHP, C, C++, C#, TypeScript, Go, SQL, Rust, Ruby, Scala, Lua, Assembly, and Visual Basic).
 
 FuxiTranyu-8B-DPO is trained using DPO with the UltraFeedback dataset, based on the [FuxiTranyu-8B](https://huggingface.co/TJUNLP/FuxiTranyu-8B) model.
 
-More details can be found at our technical report.
+More details on the data collection & processing, pretraining and fine-tuning of FuxiTranyu can be found in the technical report.
 
 We also provide the instruction fine-tuned version at [here](https://huggingface.co/TJUNLP/FuxiTranyu-8B-SFT).
 ## Usage