Qwen2.5-3B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 3.09B |
| Architecture | Transformers with RoPE, SwiGLU, RMSNorm |
| Context Length | 32,768 tokens |
| License | Qwen Research |
| Paper | Research Paper |
What is Qwen2.5-3B-Instruct?
Qwen2.5-3B-Instruct is an advanced instruction-tuned language model that represents the latest iteration in the Qwen series. This 3.09B parameter model is designed for sophisticated language understanding and generation tasks, featuring enhanced capabilities in coding, mathematics, and structured data processing.
Implementation Details
The model employs a state-of-the-art architecture with 36 layers and implements Grouped-Query Attention with 16 heads for queries and 2 for key-values. It supports an impressive context length of 32,768 tokens and can generate up to 8,192 tokens in a single pass.
- Advanced architecture combining RoPE, SwiGLU, and RMSNorm
- Optimized for both BF16 precision operations
- Comprehensive multilingual support for 29+ languages
- Enhanced instruction-following capabilities
Core Capabilities
- Superior knowledge processing and retention
- Advanced coding and mathematical problem-solving
- Structured data handling and JSON generation
- Long-context understanding up to 128K tokens
- Robust multilingual support including Chinese, English, and many other languages
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its balanced combination of size and capabilities, offering enterprise-grade performance in a relatively compact 3B parameter package. Its enhanced instruction-following abilities and structured output generation make it particularly suitable for practical applications.
Q: What are the recommended use cases?
The model excels in coding tasks, mathematical computations, multilingual content generation, and handling structured data. It's particularly well-suited for applications requiring long-context understanding and precise instruction following.
