The provided paper introduces QWEN, a comprehensive series of large language models (LLMs) developed by Alibaba Group.

Here is a short summary of its key highlights:

• Model Lineage: The QWEN series includes base pretrained language models—trained on up to 3 trillion tokens of diverse, multilingual text and code—and QWEN-CHAT models, which are aligned to human preferences using supervised fine-tuning (SFT) and Reinforcement Learning from Human Feedback (RLHF).
• Scale and Accessibility: The models have been officially open-sourced in developer-friendly sizes of 1.8 billion, 7 billion, and 14 billion parameters.
• Advanced Agent Capabilities: The chat models are highly capable of functioning as generalist agents. They demonstrate advanced abilities in tool use, planning, and utilizing Python code interpreters to execute complex tasks like mathematical reasoning and data visualization.
• Specialized Domain Models: Building upon the base models, the team also developed CODE-QWEN (and CODE-QWEN-CHAT) for specialized code understanding, generation, and debugging, as well as MATH-QWEN-CHAT for advanced mathematical reasoning.
• Performance: Across comprehensive benchmarks evaluating language understanding, creativity, coding, and mathematics, the QWEN models consistently outperform state-of-the-art open-source models of similar scale, and in some cases, even surpass much larger models.