Qwen2 72B Instruct is a 72 billion parameter model developed by Alibaba for instruction-tuned tasks. It excels in natural language understanding and generation tasks, including summarization, dialogue, and complex reasoning. Qwen2 is optimized for instruction-following, making it ideal for applications that require detailed and structured responses across a wide range of domains.
Fine-tuningDocs | Qwen2 72B Instruct can be customized with your data to improve responses. Fireworks uses LoRA to efficiently train and deploy your personalized model |
On-demand DeploymentDocs | On-demand deployments allow you to use Qwen2 72B Instruct on dedicated GPUs with Fireworks' high-performance serving stack with high reliability and no rate limits. |
Qwen2-72B Instruct is a 72.7 billion parameter instruction-tuned language model developed by Qwen (Alibaba Group). It is part of the Qwen2 series, optimized for natural language understanding, generation, and instruction following across complex domains like coding, math, and multilingual reasoning.
The model is well-suited for:
It shows strong performance in multilingual and structured output tasks.
The model supports:
The full 131K token context window is usable when deployed with appropriate rope_scaling via vLLM or compatible runtime.
transformers < 4.37.0apply_chat_template() for correct prompt formattingThe model has 72.7 billion parameters.
Yes. Fireworks supports LoRA-based fine-tuning on dedicated infrastructure.
The model is licensed under Tongyi Qianwen, a custom license from Alibaba Group. It is not open-source under Apache/MIT and may have commercial restrictions.