| Property | Value |
|---|---|
| License | DeepSeek License (Commercial use supported) |
| Research Paper | arXiv:2402.03300 |
| Framework | PyTorch with Transformers |
| Model Type | Mathematical Reasoning LLM |
What is deepseek-math-7b-instruct?
DeepSeek Math 7B Instruct is a specialized large language model designed specifically for mathematical reasoning and problem-solving. Built on the LLaMA architecture, it has been optimized to provide step-by-step solutions to mathematical problems in both English and Chinese.
Implementation Details
The model implements a chain-of-thought prompting approach, requiring specific formatting for optimal performance. It utilizes PyTorch and the Transformers library, supporting bfloat16 precision for efficient computation.
- Requires specific prompt template with "\\boxed{}" for final answers
- Supports both English and Chinese inputs
- Implements automatic BOS token addition
- Uses chat template functionality for structured interactions
Core Capabilities
- Step-by-step mathematical reasoning
- Bilingual support (English and Chinese)
- Integral calculations and complex math problems
- Structured output formatting with boxed answers
- Commercial use support
Frequently Asked Questions
Q: What makes this model unique?
This model specializes in mathematical problem-solving with a focus on showing detailed work through chain-of-thought reasoning, making it particularly valuable for educational and analytical applications.
Q: What are the recommended use cases?
The model is ideal for mathematical tutoring, problem-solving assistance, and applications requiring step-by-step mathematical explanations. It's particularly useful in educational technology and computational mathematics tools.