TigerBot：一种开放的多语言多任务LLM

摘要

我们发布并介绍了TigerBot系列大型语言模型（LLMs），包括基础模型和聊天模型，参数规模分别为70亿和180亿。我们从Llama-2和BLOOM开始开发我们的模型，并在数据、训练算法、基础设施和应用工具方面不断突破界限。我们的模型在性能上显著超越了SOTA开源模型，例如Llama-2，在英语上提升了6％，在中文上提升了20％。TigerBot模型系列在主要学术和工业基准测试以及排行榜中取得了领先的性能。我们相信TigerBot仅代表了LLM开源社区快速发展的一个缩影。因此，我们很高兴通过公开发布我们的模型并报告背后的方法来回馈社区，特别强调以民主化方式构建SOTA LLMs，并使LLMs在现实应用中发挥作用。

English

We release and introduce the TigerBot family of large language models (LLMs), consisting of base and chat models, sized from 7, 13, 70 and 180 billion parameters. We develop our models embarking from Llama-2 and BLOOM, and push the boundary further in data, training algorithm, infrastructure, and application tools. Our models yield meaningful performance gain over SOTA open-source models, e.g., Llama-2, specifically 6\% gain in English and 20\% gain in Chinese. TigerBot model family also achieves leading performance in major academic and industrial benchmarks and leaderboards. We believe that TigerBot represents just a snapshot of lightning-fast progression in LLM open-source community. Therefore, we are thrilled to give back by publicly releasing our models and reporting our approach behind, with additional emphases on building SOTA LLMs in a democratized way and making LLMs of use in real-world applications.

TigerBot：一种开放的多语言多任务LLM

TigerBot: An Open Multilingual Multitask LLM

摘要

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