Duxiaoman-DI/XuanYuan2-70B-Chat

XuanYuan2-70B-Chat: Enhanced General and Financial LLM

Duxiaoman-DI's XuanYuan2-70B-Chat is a 70 billion parameter instruction-tuned model, building upon the XuanYuan-70B base. It has undergone extensive continued pre-training with high-quality data, instruction fine-tuning, and reinforcement learning with human feedback (RLHF) to align better with human preferences.

Key Enhancements & Capabilities:

• Improved General & Financial Performance: Significant advancements in overall capabilities, safety, and specialized financial domain understanding compared to its predecessor.
• Extended Context Length: Supports a 16k token context window, enabling better processing of longer texts.
• Optimized Training: Utilizes a novel data-bucketed dynamic pre-training method for efficiency and long-text modeling.
• Quantized Versions: Available in 8-bit and 4-bit quantized versions to reduce hardware requirements, with 4-bit models showing substantial throughput gains (60.32 token/s) when used with vLLM.

Performance Highlights:

• General Benchmarks: Achieves 72.7 on CEVAL and 72.7 on CMMLU, demonstrating enhanced Chinese language capabilities while maintaining English performance (70.8 MMLU).
• Financial Benchmarks: Scores an average of 67.83 on the FinanceIQ benchmark, indicating improved financial knowledge and reasoning.

Ideal Use Cases:

• Applications requiring strong general language understanding and generation.
• Financial industry applications needing specialized knowledge and analysis.
• Scenarios benefiting from longer context processing.
• Deployments where optimized inference speed with quantized models (especially via vLLM) is crucial.