Qwen2.5-Math-1.5B-Instruct
| Property | Value |
|---|---|
| Parameter Count | 1.54B |
| License | Apache 2.0 |
| Paper | arXiv:2409.12122 |
| Tensor Type | BF16 |
What is Qwen2.5-Math-1.5B-Instruct?
Qwen2.5-Math-1.5B-Instruct is a specialized mathematical language model designed to solve mathematical problems in both English and Chinese. As part of the Qwen2.5-Math series released after the original Qwen2-Math, this instruction-tuned model represents a significant advancement in mathematical reasoning capabilities.
Implementation Details
The model leverages two primary reasoning approaches: Chain-of-Thought (CoT) and Tool-integrated Reasoning (TIR). It requires transformers>=4.37.0 for operation and uses BF16 tensor type for optimal performance. The model can be easily deployed using the Hugging Face Transformers library.
- Supports both English and Chinese mathematical problem-solving
- Implements advanced reasoning techniques (CoT and TIR)
- Designed for instruction-following and chat-based interactions
- Built on the Qwen2.5-Math-1.5B base model
Core Capabilities
- Precise computation and symbolic manipulation
- Step-by-step mathematical reasoning
- Complex problem-solving through tool integration
- Support for both conversational and formal mathematical queries
Frequently Asked Questions
Q: What makes this model unique?
This model uniquely combines Chain-of-Thought and Tool-integrated Reasoning capabilities, allowing it to handle both conceptual understanding and precise mathematical computations. It's specifically optimized for mathematical tasks and supports both English and Chinese languages.
Q: What are the recommended use cases?
The model is specifically designed for solving mathematical problems, including equation solving, algorithmic reasoning, and symbolic manipulation. It's not recommended for general-purpose tasks outside of mathematics.
