AceMath-1.5B-Instruct
| Property | Value |
|---|---|
| Developer | NVIDIA |
| Parameter Count | 1.5 Billion |
| Base Model | Qwen2.5-Math-1.5B-Base |
| License | Creative Commons Attribution Non-Commercial 4.0 |
| Primary Use | Mathematical Reasoning |
What is AceMath-1.5B-Instruct?
AceMath-1.5B-Instruct is part of NVIDIA's AceMath family of models specifically designed for mathematical reasoning. It represents a significant advancement in AI-powered mathematical problem-solving, utilizing Chain-of-Thought (CoT) reasoning to tackle complex mathematical challenges. The model is built upon Qwen2.5-Math-1.5B-Base and has undergone a sophisticated multi-stage supervised fine-tuning process.
Implementation Details
The model employs a two-stage supervised fine-tuning approach: first with general-purpose data, followed by mathematics-specific training data. It's implemented using the Hugging Face Transformers library and can be easily integrated into existing machine learning pipelines.
- Built on Qwen2.5-Math-1.5B-Base architecture
- Specialized in English mathematical problem solving
- Supports Chain-of-Thought reasoning
- Optimized for mathematical tasks specifically
Core Capabilities
- Solving complex mathematical problems with step-by-step reasoning
- Processing and understanding mathematical notation and symbols
- Generating detailed mathematical solutions
- Handling various types of mathematical queries and problems
Frequently Asked Questions
Q: What makes this model unique?
AceMath-1.5B-Instruct stands out for its specialized focus on mathematical reasoning and its efficient architecture that delivers strong performance despite its relatively compact size. It's part of a broader family of models that have demonstrated competitive performance against larger language models in mathematical problem-solving tasks.
Q: What are the recommended use cases?
The model is specifically recommended for mathematical problem-solving applications. While it's capable of handling other tasks, NVIDIA recommends using their AceInstruct series for general-purpose applications including code and general knowledge tasks.
