unsloth/Qwen2.5-Math-7B-Instruct

Hugging Face
TEXT GENERATIONConcurrency Cost:1Model Size:7.6BQuant:FP8Ctx Length:32kPublished:Sep 23, 2024License:apache-2.0Architecture:Transformer0.0K Open Weights Warm

The unsloth/Qwen2.5-Math-7B-Instruct is a 7.6 billion parameter instruction-tuned model from the Qwen2.5-Math series, developed by Qwen. This model is specifically optimized for solving mathematical problems in both English and Chinese, utilizing Chain-of-Thought (CoT) and Tool-integrated Reasoning (TIR). It is designed to enhance computational accuracy and handle complex mathematical tasks, achieving strong performance on benchmarks like MATH.

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Qwen2.5-Math-7B-Instruct Overview

This model is part of the Qwen2.5-Math series, an upgrade from the original Qwen2-Math family, specifically designed for mathematical problem-solving. Developed by Qwen, this 7.6 billion parameter instruction-tuned model excels in handling math problems in both English and Chinese.

Key Capabilities

  • Mathematical Reasoning: Supports Chain-of-Thought (CoT) for step-by-step reasoning.
  • Tool-integrated Reasoning (TIR): Integrates external tools for precise computation, symbolic manipulation, and algorithmic tasks, addressing limitations of CoT alone.
  • Multilingual Support: Capable of solving math problems in both Chinese and English.
  • Performance: Achieves 85.3 on the MATH benchmark using TIR, demonstrating significant improvements over previous versions.

Good For

  • Solving English and Chinese Math Problems: Ideal for applications requiring robust mathematical reasoning.
  • Educational Tools: Can be integrated into platforms for teaching or assisting with math homework.
  • Research in Mathematical LLMs: Serves as a strong base for further fine-tuning or research into advanced mathematical reasoning techniques.