Hugging Face Overview
Qwen2.5-14B-Instruct Overview
This model is an instruction-tuned variant from the Qwen2.5 series, developed by Qwen. It builds upon the Qwen2 architecture, incorporating significant enhancements across several key areas. The model has 14.7 billion parameters and supports an extensive context length of 131,072 tokens, with a generation capacity of 8,192 tokens.
Key Capabilities & Improvements
- Enhanced Knowledge & Specialized Skills: Demonstrates greatly improved capabilities in coding and mathematics, leveraging specialized expert models.
- Instruction Following & Text Generation: Shows significant improvements in adhering to instructions and generating long texts (over 8K tokens).
- Structured Data & Output: Excels at understanding structured data, such as tables, and generating structured outputs, particularly JSON.
- System Prompt Resilience: More resilient to diverse system prompts, which enhances its ability for role-play and condition-setting in chatbots.
- Multilingual Support: Offers robust support for over 29 languages, including Chinese, English, French, Spanish, German, and Japanese.
- Architecture: Utilizes a transformer architecture with RoPE, SwiGLU, RMSNorm, and Attention QKV bias.
When to Use This Model
This model is particularly well-suited for applications requiring:
- Complex Code Generation & Mathematical Reasoning: Due to its specialized improvements in these domains.
- Long-form Content Creation: Ideal for tasks involving generating extensive texts or processing large documents.
- Structured Data Processing: Effective for scenarios where understanding and generating structured formats like JSON or tables is crucial.
- Multilingual Chatbots & Assistants: Its broad language support makes it suitable for global applications.
- Instruction-Following Agents: Benefits from enhanced instruction adherence for more reliable task execution.