Qwen/Qwen2.5-7B-Instruct

Qwen2.5-7B-Instruct is a 7.61 billion parameter instruction-tuned causal language model developed by Qwen, featuring a transformer architecture with RoPE, SwiGLU, and RMSNorm. It offers significantly improved capabilities in coding, mathematics, and long-text generation up to 8K tokens, with a full context length of 131,072 tokens. This model excels at instruction following, understanding structured data like tables, and generating structured outputs such as JSON, while also supporting over 29 languages.