Qwen2.5-Coder-32B
| Property | Value |
|---|---|
| Parameter Count | 32.8B |
| License | Apache 2.0 |
| Architecture | Transformers with RoPE, SwiGLU, RMSNorm |
| Context Length | 128K tokens |
| Paper | Technical Report |
What is Qwen2.5-Coder-32B?
Qwen2.5-Coder-32B is a state-of-the-art code-specialized large language model that represents the pinnacle of the Qwen2.5-Coder series. Trained on 5.5 trillion tokens including source code, text-code grounding, and synthetic data, it achieves performance levels comparable to GPT-4 in coding tasks.
Implementation Details
The model features a sophisticated architecture with 64 layers and employs GQA attention with 40 heads for queries and 8 for key-values. It implements YaRN technology for enhanced long-context processing up to 131,072 tokens.
- Advanced transformer architecture with RoPE, SwiGLU, and RMSNorm
- 31.0B non-embedding parameters
- BF16 tensor type for optimal performance
- Supports deployment via vLLM for production environments
Core Capabilities
- Superior code generation and reasoning abilities
- Advanced code fixing and debugging capabilities
- Strong mathematical reasoning foundation
- Extended context handling up to 128K tokens
- Comprehensive support for Code Agents applications
Frequently Asked Questions
Q: What makes this model unique?
The model stands out for its exceptional scale of training (5.5 trillion tokens), state-of-the-art performance in coding tasks, and extensive context length support of 128K tokens, making it particularly suitable for complex coding projects.
Q: What are the recommended use cases?
While the model excels at code generation, reasoning, and fixing, it's not recommended for direct conversational use. Instead, it's ideal for code-related tasks and should be fine-tuned with SFT or RLHF for specific applications.
