Qwen/Qwen2.5-32B-Instruct

Qwen/Qwen2.5-32B-Instruct is a 32.5 billion parameter instruction-tuned causal language model developed by Qwen, featuring a transformer architecture with RoPE, SwiGLU, and RMSNorm. This model significantly improves upon Qwen2 with enhanced coding and mathematics capabilities, better instruction following, and robust long-text generation up to 8K tokens within a 128K context window. It excels at understanding structured data like JSON and offers multilingual support for over 29 languages, making it suitable for diverse complex NLP tasks.