Qwen2.5-Coder-32B-Instruct-128K-GGUF
| Property | Value |
|---|---|
| Parameter Count | 32.5B |
| Context Length | 131,072 tokens |
| License | Apache 2.0 |
| Architecture | Transformers with RoPE, SwiGLU, RMSNorm |
| Paper | Technical Report |
What is Qwen2.5-Coder-32B-Instruct-128K-GGUF?
Qwen2.5-Coder-32B-Instruct is an advanced code-generation language model that represents the latest evolution in Alibaba Cloud's Qwen series. This GGUF-optimized version brings state-of-the-art coding capabilities to a more efficient format, trained on 5.5 trillion tokens including source code and text-code grounding data.
Implementation Details
The model features a sophisticated architecture utilizing 64 layers with 40 attention heads for queries and 8 for key-values (GQA). It implements advanced techniques including RoPE for positional encoding, SwiGLU activations, and RMSNorm for normalization. The impressive 128K context window enables processing of extensive code bases and documentation.
- Full 131,072 token context length
- 31.0B non-embedding parameters
- Group Query Attention (GQA) implementation
- Optimized GGUF format for efficient deployment
Core Capabilities
- Advanced code generation matching GPT-4 level performance
- Enhanced code reasoning and debugging abilities
- Robust mathematical computation capabilities
- Code Agent foundation support
- Extensive context handling for large codebases
Frequently Asked Questions
Q: What makes this model unique?
This model combines state-of-the-art coding capabilities with an extensive 128K context window, optimized in GGUF format for efficient deployment. It represents a significant improvement over its predecessors with capabilities matching GPT-4 in code generation tasks.
Q: What are the recommended use cases?
The model excels in code generation, debugging, and analysis tasks. It's particularly well-suited for software development, code review, and educational purposes. The extended context length makes it ideal for handling large codebases and documentation.
