Jais 2是首个700亿参数的开源阿拉伯语大模型,兼顾性能与效率。
Jais 2: A Family of Arabic-Centric Open Large Language Models
- 自研阿拉伯语专用词表,支持高效训练与推理
- 70B模型在阿语基准上领先,8B版性能媲美主流开源模型
- 开源且支持多端部署,适合阿拉伯语研究与应用开发
Jais 2是由MBZUAI、Cerebras和Inception联合开发的一系列面向阿拉伯语的大规模语言模型,旨在推动阿拉伯语为中心的语言建模。该系列包含目前已知最大的从头训练的开源阿拉伯语大模型(700亿参数),以及一个在评估中表现优异的80亿参数版本。通过自定义的阿拉伯语专用词汇表,实现高效的训练与推理。优化的架构与训练方案显著提升了计算效率,在远低于同类模型的令牌预算下,仍达到出色的阿拉伯语性能,并具备竞争力的英文表现。在OALL2和AraGen等基准上位居开源模型前列,同时在诗歌、宗教、饮食、梦境解析等文化相关任务及翻译、摘要等通用任务中表现强劲。模型已发布于HuggingFace,采用商业友好许可。70B版本还以聊天应用形式上线网页、iOS和Android平台,运行于Cerebras硬件,最高达每秒2000个令牌,支持高吞吐量的阿拉伯语对话服务。通过融合规模、语言多样性、文化契合度、开放性与速度,Jais 2为阿拉伯语大模型的研究与应用提供开源基础。
原文摘要 · Abstract (English)
Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong performance across the Arabic and culturally grounded benchmarks evaluated in this report. The family includes, to our knowledge, the largest open Arabic-centric LLM trained from scratch at 70B parameters, and a competitive 8B-parameter variant among the evaluated open models. A custom Arabic-centric vocabulary enables efficient training and inference. In addition, an optimized architecture and training recipe yield highly compute-efficient training. With a substantially smaller token budget than comparable models, Jais 2 achieves strong Arabic performance on the benchmarks considered in this report and competitive English results. The models obtain leading results among the evaluated open models on OALL2 and AraGen. They also perform strongly on several culturally grounded Arabic benchmarks, including poetry, religion, cuisine, and dream interpretation, as well as in general tasks such as translation and summarization. We release the models in HuggingFace under a commercially permissive license. Jais 2 70B is also released as a chat app on the Web, iOS, and Android; it runs on Cerebras hardware, delivering up to 2,000 tokens per second, and enabling high-throughput Arabic-centric chat serving in our deployment setting. By uniting scale, linguistic diversity, cultural fidelity, openness, and speed, Jais 2 provides an open-weight foundation intended to support further research and development in Arabic-centric LLMs.
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