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README.md

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 We introduce **Babel**, a multilingual LLM that covers the top 25 languages by number of speakers, including English, Chinese, Hindi, Spanish, Arabic, French, Bengali, Portuguese, Russian, Urdu, Indonesian, German, Japanese, Swahili, Filipino, Tamil, Vietnamese, Turkish, Italian, Javanese, Korean, Hausa, Persian, Thai, and Burmese. These 25 languages support over 90% of the global population, and include many languages neglected by other open multilingual LLMs. Unlike traditional continued pretraining approaches, Babel expands its parameter count through a layer extension technique that elevates Babel's performance ceiling.
 
 We introduce two variants:  
-- **Babel-9B**, designed for efficient single-GPU inference and fine-tuning  
+- **Babel-9B**, designed for efficient inference and fine-tuning  
 - **Babel-83B**, which sets a new standard for open multilingual LLMs  
 
 Extensive evaluations on multilingual tasks demonstrate its superior performance compared to open LLMs of comparable size. In addition, using existing supervised fine-tuning datasets, Babel achieves remarkable performance, with **Babel-9B-Chat** leading among 10B-sized LLMs and **Babel-83B-Chat** setting a new standard for open LLMs, performing comparably to GPT-4o on certain tasks.