Hugging Face Overview
Qwen2.5-3B-Instruct Overview
Qwen2.5-3B-Instruct is an instruction-tuned model from the latest Qwen2.5 series, developed by Qwen. This 3.09 billion parameter causal language model is built on a transformer architecture featuring RoPE, SwiGLU, RMSNorm, Attention QKV bias, and tied word embeddings. It supports a substantial context length of 32,768 tokens and can generate up to 8,192 tokens, making it suitable for tasks requiring extensive input and output.
Key Capabilities
- Enhanced Knowledge & Reasoning: Significantly improved capabilities in coding and mathematics, leveraging specialized expert models.
- Advanced Instruction Following: Demonstrates strong performance in adhering to instructions and understanding diverse system prompts, beneficial for role-play and chatbot applications.
- Structured Data & Output: Excels at understanding structured data (e.g., tables) and generating structured outputs, particularly JSON.
- Long Text Generation: Capable of generating long texts exceeding 8,000 tokens.
- Multilingual Support: Provides robust support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, and Arabic.
Good for
- Applications requiring strong coding and mathematical reasoning at a smaller parameter count.
- Chatbots and assistants needing resilient instruction following and role-play implementation.
- Tasks involving structured data processing and JSON output generation.
- Generating long-form content or handling extensive conversational turns.
- Multilingual applications targeting a broad range of languages.