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.
Orion-14B: Open-source Multilingual Large Language Models
A multilingual large language model with 14 billion parameters achieves state-of-the-art performance across various tasks through data scheduling and fine-tuning.
- Year
- 2024
- Venue
- arXiv 2024
- Authors
- 10
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- Abstract onlyARXIV-DEFAULT
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- arxiv.org/abs/2401.12246ARXIV-DEFAULT
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