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Orion-14B: Open-source Multilingual Large Language Models

Authors :
Chen, Du
Huang, Yi
Li, Xiaopu
Li, Yongqiang
Liu, Yongqiang
Pan, Haihui
Xu, Leichao
Zhang, Dacheng
Zhang, Zhipeng
Han, Kun
Publication Year :
2024

Abstract

In this study, we introduce Orion-14B, a collection of multilingual large language models with 14 billion parameters. We utilize a data scheduling approach to train a foundational model on a diverse corpus of 2.5 trillion tokens, sourced from texts in English, Chinese, Japanese, Korean, and other languages. Additionally, we fine-tuned a series of models tailored for conversational applications and other specific use cases. Our evaluation results demonstrate that Orion-14B achieves state-of-the-art performance across a broad spectrum of tasks. We make the Orion-14B model family and its associated code publicly accessible https://github.com/OrionStarAI/Orion, aiming to inspire future research and practical applications in the field.<br />Comment: Authors are alphabetically listed by last names, except the corresponding author who is listed last

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2401.12246
Document Type :
Working Paper