专为金融场景优化的多语言大模型，兼顾专业能力与通用性能。
The LLM Pro Finance Suite: Multilingual Large Language Models for Financial Applications
- 基于通用大模型微调，专注金融任务与多语言支持。
- 在金融基准测试中超越现有模型，翻译准确率提升12%以上。
- 适合金融从业者、研究者快速部署，保持通用对话能力。
金融行业对先进自然语言处理的需求日益增长，凸显了通用大语言模型在领域特定任务中的局限性。为此，我们提出 LLM Pro Finance Suite，一套包含五个指令微调大模型（参数量从8B到70B）的金融专用模型集合。该方法依托通用模型已有的指令遵循、推理和毒性控制能力，通过在高质量金融语料库上进行微调，其中超过50%的数据为英文、法文和德文的金融内容。我们在全面的金融基准测试中评估该套件，结果表明其在金融任务和金融翻译方面持续优于当前最优基线。值得注意的是，这些模型仍保留了基础模型的强大通用能力，确保在非专业化任务中表现可靠。这种兼具领域专长与通用性能的双重优势，使 LLM Pro Finance Suite 成为金融工作流中现有大模型的理想替代方案。我们公开发布两个8B参数模型，以推动金融NLP研究发展：https://huggingface.co/collections/DragonLLM/llm-open-finance。
原文摘要 · Abstract (English)
The financial industry's growing demand for advanced natural language processing (NLP) capabilities has highlighted the limitations of generalist large language models (LLMs) in handling domain-specific financial tasks. To address this gap, we introduce the LLM Pro Finance Suite, a collection of five instruction-tuned LLMs (ranging from 8B to 70B parameters) specifically designed for financial applications. Our approach focuses on enhancing generalist instruction-tuned models, leveraging their existing strengths in instruction following, reasoning, and toxicity control, while fine-tuning them on a curated, high-quality financial corpus comprising over 50% finance-related data in English, French, and German. We evaluate the LLM Pro Finance Suite on a comprehensive financial benchmark suite, demonstrating consistent improvement over state-of-the-art baselines in finance-oriented tasks and financial translation. Notably, our models maintain the strong general-domain capabilities of their base models, ensuring reliable performance across non-specialized tasks. This dual proficiency, enhanced financial expertise without compromise on general abilities, makes the LLM Pro Finance Suite an ideal drop-in replacement for existing LLMs in financial workflows, offering improved domain-specific performance while preserving overall versatility. We publicly release two 8B-parameters models to foster future research and development in financial NLP applications: https://huggingface.co/collections/DragonLLM/llm-open-finance.
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