Qwen2.5-Math-7B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 7.62B |
| License | Apache 2.0 |
| Paper | arXiv:2409.12122 |
| Tensor Type | BF16 |
What is Qwen2.5-Math-7B-Instruct?
Qwen2.5-Math-7B-Instruct is a specialized mathematical language model that represents a significant evolution in AI-powered mathematical problem-solving. Released as part of the Qwen2.5-Math series, this instruction-tuned model is specifically designed to handle both English and Chinese mathematical problems using advanced reasoning techniques.
Implementation Details
The model leverages two primary reasoning approaches: Chain-of-Thought (CoT) and Tool-integrated Reasoning (TIR). It requires transformers>=4.37.0 and can be easily deployed using the Hugging Face Transformers library. The model achieves an impressive 85.3% performance on the MATH benchmark using TIR.
- Dual-language support for English and Chinese mathematics
- Advanced reasoning capabilities through CoT and TIR integration
- Optimized for instruction-following and mathematical problem-solving
- Built on the Qwen architecture with 7.62B parameters
Core Capabilities
- Precise computation and symbolic manipulation
- Step-by-step mathematical reasoning
- Complex problem-solving including quadratic equations and matrix operations
- Interactive chat-based mathematical assistance
Frequently Asked Questions
Q: What makes this model unique?
This model uniquely combines both Chain-of-Thought and Tool-integrated Reasoning capabilities, allowing it to handle both conceptual understanding and precise computational tasks in mathematics across two languages.
Q: What are the recommended use cases?
The model is specifically designed for mathematical problem-solving, including equation solving, algorithmic reasoning, and symbolic manipulation. It is not recommended for general-purpose tasks outside of mathematics.
