Qwen-72B
| Property | Value |
|---|---|
| Parameter Count | 72.3B |
| Context Length | 32,768 tokens |
| Architecture | Transformer with 80 layers, 64 heads |
| License | Tongyi Qianwen License Agreement |
| Paper | arXiv:2309.16609 |
What is Qwen-72B?
Qwen-72B is a state-of-the-art large language model developed by Alibaba Cloud, representing a significant advancement in the field of natural language processing. Trained on over 3 trillion tokens, it features a comprehensive 150K token vocabulary and demonstrates exceptional performance across multiple languages and tasks.
Implementation Details
The model implements cutting-edge architectural choices including RoPE relative position encoding, SwiGLU activation functions, and RMSNorm. It requires significant computational resources, with minimum requirements of 144GB GPU memory for BF16/FP16 inference.
- 80 transformer layers with 64 attention heads
- 8192 dimensional model size
- 151,851 vocabulary tokens
- 32K sequence length support
Core Capabilities
- Superior performance on benchmarks like MMLU (77.4%), C-Eval (83.3%), and GSM8K (78.9%)
- Strong multilingual support with optimized tokenization for various languages
- Advanced code generation and mathematical reasoning capabilities
- Efficient long-context processing with 32K token support
Frequently Asked Questions
Q: What makes this model unique?
Qwen-72B stands out for its comprehensive multilingual support, extensive training data (3T+ tokens), and state-of-the-art performance across various benchmarks. Its optimized tokenizer and extended context length make it particularly versatile for complex applications.
Q: What are the recommended use cases?
The model excels in multiple applications including complex reasoning, code generation, mathematical problem-solving, and multilingual text processing. It's particularly suitable for scenarios requiring long context understanding and cross-lingual capabilities.
