Qwen is a large language model series developed by Alibaba Group. The series includes base pretrained language models and chat models fine-tuned with human alignment techniques. The base models demonstrate strong performance across various downstream tasks, while the chat models, particularly those trained with Reinforcement Learning from Human Feedback (RLHF), are highly competitive. Specialized models such as CODE-QWEN and MATH-QWEN-CHAT are also developed, showing improved performance compared to open-source models. The models are trained on extensive datasets, with CODE-QWEN pre-trained on code data and MATH-QWEN-CHAT designed for mathematical reasoning. The series includes models with varying parameter counts, ranging from 7B to 14B parameters. The models are evaluated on multiple benchmarks, demonstrating strong performance in tasks such as code generation, debugging, and mathematical problem-solving. The Qwen series also includes a multimodal model, QWEN-VL, which can understand and process visual and language instructions. The models are aligned with human preferences through supervised finetuning and RLHF, enabling them to engage in natural conversations and perform complex tasks. The series is released as open-source, providing developers with access to powerful language models for various applications.Qwen is a large language model series developed by Alibaba Group. The series includes base pretrained language models and chat models fine-tuned with human alignment techniques. The base models demonstrate strong performance across various downstream tasks, while the chat models, particularly those trained with Reinforcement Learning from Human Feedback (RLHF), are highly competitive. Specialized models such as CODE-QWEN and MATH-QWEN-CHAT are also developed, showing improved performance compared to open-source models. The models are trained on extensive datasets, with CODE-QWEN pre-trained on code data and MATH-QWEN-CHAT designed for mathematical reasoning. The series includes models with varying parameter counts, ranging from 7B to 14B parameters. The models are evaluated on multiple benchmarks, demonstrating strong performance in tasks such as code generation, debugging, and mathematical problem-solving. The Qwen series also includes a multimodal model, QWEN-VL, which can understand and process visual and language instructions. The models are aligned with human preferences through supervised finetuning and RLHF, enabling them to engage in natural conversations and perform complex tasks. The series is released as open-source, providing developers with access to powerful language models for various applications.