nvidia/AceMath-7B-Instruct
nvidia/AceMath-7B-Instruct is a 7.6 billion parameter instruction-tuned model developed by NVIDIA, built upon Qwen2.5-Math-7B-Base. It is specifically designed and optimized for advanced mathematical reasoning, excelling at solving English mathematical problems using Chain-of-Thought (CoT) reasoning. This model demonstrates strong performance on various math reasoning benchmarks, outperforming previous best-in-class models in its size category.
Loading preview...
AceMath-7B-Instruct: Advanced Mathematical Reasoning
AceMath-7B-Instruct is a 7.6 billion parameter model from NVIDIA, specifically engineered for high-performance mathematical reasoning. It is developed from the Qwen2.5-Math-7B-Base model through a multi-stage supervised fine-tuning (SFT) process, first with general-purpose SFT data, followed by math-specific SFT data.
Key Capabilities
- Mathematical Problem Solving: Excels at solving complex English mathematical problems using Chain-of-Thought (CoT) reasoning.
- Benchmark Performance: Outperforms previous best-in-class models like Qwen2.5-Math-7B-Instruct on various math reasoning benchmarks, achieving an average pass@1 of 67.2.
- Specialized Training: Benefits from a dedicated math-specific SFT phase, leveraging comprehensive training data released by NVIDIA.
Good For
- Dedicated Math Applications: Primarily recommended for tasks requiring robust mathematical problem-solving capabilities.
- Research in Mathematical AI: The accompanying training data and reward models (AceMath-7B-RM) support further research in this domain.
It's important to note that while highly specialized for math, for general-purpose tasks encompassing code, math, and general knowledge, NVIDIA also offers the AceInstruct series of models.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.