Qwen2.5-1.5B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 1.54B |
| Context Length | 32,768 tokens |
| License | Apache 2.0 |
| Architecture | Transformers with RoPE, SwiGLU, RMSNorm |
| Paper | Technical Report |
What is Qwen2.5-1.5B-Instruct?
Qwen2.5-1.5B-Instruct is a powerful instruction-tuned language model that represents the latest advancement in the Qwen series. With 1.54B parameters and support for 29+ languages, it's designed to excel in various tasks while maintaining efficiency and versatility.
Implementation Details
The model features a sophisticated architecture with 28 layers and employs GQA attention with 12 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.
- Specialized architecture with RoPE, SwiGLU, and RMSNorm components
- BF16 tensor type for optimal performance
- Comprehensive multilingual support including Chinese, English, and many other languages
- Enhanced instruction-following capabilities
Core Capabilities
- Advanced knowledge representation and processing
- Superior coding and mathematical problem-solving
- Structured data understanding and JSON generation
- Long-form content generation
- Multi-lingual text processing and generation
- Robust role-play implementation
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its efficient architecture, extensive language support, and specialized capabilities in coding and mathematics, all while maintaining a relatively compact parameter count of 1.54B.
Q: What are the recommended use cases?
The model excels in chatbot applications, code generation, mathematical problem-solving, and multilingual content generation. It's particularly suitable for applications requiring structured output and long-context understanding.
