OpenMath2-Llama3.1-70B-nemo
| Property | Value |
|---|---|
| Base Model | Meta LLaMA 3.1 70B |
| License | LLaMA 3.1 |
| Research Paper | arXiv:2410.01560 |
| Training Dataset | OpenMathInstruct-2 |
What is OpenMath2-Llama3.1-70B-nemo?
OpenMath2-Llama3.1-70B-nemo is NVIDIA's specialized mathematical reasoning model built on the LLaMA 3.1 70B architecture. This NeMo framework implementation represents a significant advancement in AI-powered mathematical problem-solving, demonstrating superior performance compared to the base LLaMA 3.1 model.
Implementation Details
The model is fine-tuned using NVIDIA's OpenMathInstruct-2 dataset and implements the same chat format as LLaMA 3.1-instruct models, utilizing identical system/user/assistant tokens. It's specifically optimized for mathematical reasoning tasks and requires the NeMo Framework for inference or further fine-tuning.
- Achieves 71.9% accuracy on MATH benchmark (79.6% with majority@256)
- Scores 94.9% on GSM8K (96.0% with majority@256)
- Demonstrates significant improvements on AMC 2023 and AIME 2024 tests
Core Capabilities
- Advanced mathematical problem-solving across various complexity levels
- Specialized performance in standardized math test scenarios
- Robust reasoning capabilities for complex mathematical concepts
- Improved accuracy with majority voting implementation
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized focus on mathematical reasoning, outperforming the base LLaMA 3.1-70B-Instruct by 3.9% on the MATH benchmark. It's specifically designed for mathematical applications and demonstrates superior performance across various mathematical testing frameworks.
Q: What are the recommended use cases?
The model is optimized for mathematical problem-solving tasks and may not perform optimally for general-purpose applications. It's best suited for mathematical reasoning, problem-solving, and educational applications focused on mathematics.
