TigerBot：一個開放式多語言多任務LLM

摘要

我們推出並介紹了TigerBot系列的大型語言模型（LLMs），包括基本模型和聊天模型，規模從70億到180億參數不等。我們從Llama-2和BLOOM開始開發我們的模型，並在數據、訓練算法、基礎設施和應用工具方面將界限推進。我們的模型在SOTA開源模型上取得了有意義的性能提升，例如在英語上提升了6％，在中文上提升了20％，如Llama-2。TigerBot模型系列還在主要的學術和工業基準測試和排行榜中取得了領先的性能。我們相信TigerBot僅代表了LLM開源社區中快速進展的一個瞬間。因此，我們很高興通過公開發布我們的模型並報告背後的方法，強調以民主化方式構建SOTA LLMs，並使LLMs在現實應用中有用。

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：一個開放式多語言多任務LLM

TigerBot: An Open Multilingual Multitask LLM

摘要

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