  In this technical report, we present VinaLLaMA, an open-weight,
state-of-the-art (SOTA) Large Language Model for the Vietnamese language, built
upon LLaMA-2 with an additional 800 billion trained tokens. VinaLLaMA not only
demonstrates fluency in Vietnamese but also exhibits a profound understanding
of Vietnamese culture, making it a truly indigenous model. VinaLLaMA-7B-chat,
trained on 1 million high-quality synthetic samples, achieves SOTA results on
key benchmarks, including VLSP, VMLU, and Vicuna Benchmark Vietnamese, marking
a significant advancement in the Vietnamese AI landscape and offering a
versatile resource for various applications.

Computation and Language