Sailor: Open Language Models for South-East Asia
Longxu Dou Qian Liu Guangtao Zeng Jia Guo Jiahui Zhou Wei Lu Min Lin
We present Sailor, a family of open language models ranging from 0.5B to 7B
parameters, tailored for South-East Asian (SEA) languages. These models are
continually pre-trained from Qwen1.5, a great language model for multilingual
use cases. From Qwen1.5, Sailor models accept 200B to 400B tokens, primarily
covering the languages of English, Chinese, Vietnamese, Thai, Indonesian,
Malay, and Lao. The training leverages several techniques, including BPE
dropout for improving the model robustness, aggressive data cleaning and
deduplication, and small proxy models to optimize data mixture. Experimental
results on four typical tasks indicate that Sailor models demonstrate strong
performance across different benchmarks, including commonsense reasoning,
question answering, reading comprehension and examination. Embracing the
open-source spirit, we share our insights through this report to spark a wider
interest in developing large language models for multilingual use cases.