nvidia/OpenMath-Mistral-7B-v0.1-hf
The nvidia/OpenMath-Mistral-7B-v0.1-hf model is a 7 billion parameter language model developed by NVIDIA, specifically designed for mathematical problem-solving. It integrates text-based reasoning with Python interpreter execution, trained on the 1.8M problem-solution pair OpenMathInstruct-1 dataset. This model excels in mathematical benchmarks like GSM8K and MATH, demonstrating strong performance in complex quantitative tasks.
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OpenMath-Mistral-7B-v0.1-hf Overview
This model is a 7 billion parameter variant from NVIDIA's OpenMath series, specifically fine-tuned for advanced mathematical problem-solving. It uniquely combines natural language reasoning with the ability to execute code blocks via a Python interpreter, a critical feature for accurate mathematical computations.
Key Capabilities
- Mathematical Reasoning: Designed to solve complex math problems by integrating textual understanding with computational execution.
- Code Integration: Leverages a Python interpreter for precise calculations, enhancing accuracy beyond typical LLM reasoning.
- Performance: Achieves 80.2 on GSM8K (greedy) and 44.5 on MATH (greedy), with majority@50 scores of 86.9 on GSM8K and 57.2 on MATH, outperforming other 7B models in its class.
- Training Data: Trained on the extensive OpenMathInstruct-1 dataset, comprising 1.8 million problem-solution pairs generated using Mixtral-8x7B.
Good For
- Applications requiring robust mathematical problem-solving.
- Educational tools for math assistance.
- Research in AI for quantitative reasoning and code-augmented language models.
NVIDIA has open-sourced the entire pipeline, including the code, models, and dataset, enabling full reproducibility and further development. More details are available in their research paper.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.