Update README.md

README.md

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 ## Introduction
 
-We present a compact yet powerful reasoning model **Ring-mini-2.0**. It has 16B total parameters, with 1.4B parameters are activated per input token (non-embedding 789M). Although **Ring-mini-2.0** is quite compact, it still reaches the top-tier level of sub-10B dense LLMs and even matches or surpasses much larger MoE models
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-through pre-training on 20T tokens of high-quality data and enhanced through long-cot supervised fine-tuning and multi-stage reinforcement learning.
+We present a compact yet powerful reasoning model **Ring-mini-2.0**. It has 16B total parameters, with 1.4B parameters are activated per input token (non-embedding 789M). Although **Ring-mini-2.0** is quite compact, it still reaches the top-tier level of sub-10B dense LLMs and even matches or surpasses much larger MoE models, through pre-training on 20T tokens of high-quality data and enhanced through long-cot supervised fine-tuning and multi-stage reinforcement learning.
 
 
 ## Model Downloads