Hugging Face Overview
Qwen2.5-Coder-14B: Code-Specific LLM
Qwen2.5-Coder-14B is a 14.7 billion parameter model from the Qwen2.5-Coder series, designed for advanced code-related tasks. It builds upon the Qwen2.5 foundation, significantly enhancing capabilities in code generation, reasoning, and fixing.
Key Capabilities & Features
- Enhanced Coding Performance: Achieves substantial improvements in code generation, reasoning, and fixing, with the 32B variant matching GPT-4o's coding abilities.
- Extensive Training Data: Trained on 5.5 trillion tokens, including a large volume of source code, text-code grounding, and synthetic data.
- Long Context Support: Supports a full 131,072 token context length, utilizing techniques like YaRN for effective long-text processing.
- General Competencies: Maintains strong performance in mathematics and general language understanding alongside its coding prowess.
- Robust Architecture: Features a transformer architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias.
When to Use This Model
- Code Generation: Ideal for generating code snippets, functions, or entire programs across various languages.
- Code Reasoning & Fixing: Suitable for tasks requiring understanding code logic, identifying errors, and suggesting fixes.
- Code Agents: Provides a comprehensive foundation for developing sophisticated code agent applications.
- Long Codebase Analysis: Effective for processing and understanding large codebases due to its extended context window.