Qwen2.5-Math-RM-72B
| Property | Value |
|---|---|
| Parameter Count | 72.8B |
| License | Qwen License |
| Paper | Technical Report |
| Tensor Type | BF16 |
| Languages | English, Chinese |
What is Qwen2.5-Math-RM-72B?
Qwen2.5-Math-RM-72B is a sophisticated reward model specifically engineered to enhance mathematical reasoning capabilities in language models. Built on the Qwen2.5-Math-72B-Instruct base model, it serves as a crucial component in training pipeline by providing detailed feedback on reasoning quality and intermediate solution steps.
Implementation Details
The model leverages advanced transformer architecture and requires transformers>=4.40.0 for operation. It operates in BF16 precision and is designed for both inference and training guidance.
- Multilingual support for both Chinese and English
- Integrated reward scoring system for response evaluation
- Supports both Chain-of-Thought and Tool-integrated Reasoning
- Implements Best-of-N sampling strategy for improved results
Core Capabilities
- Provides granular feedback on mathematical reasoning quality
- Enables response quality assessment through reward scoring
- Supports reinforcement learning training integration
- Facilitates data selection via reward model scoring
- Enables RM@N inference optimization
Frequently Asked Questions
Q: What makes this model unique?
This model stands out for its specialized focus on mathematical reasoning assessment, offering detailed feedback on solution steps and enabling advanced training techniques like Rejection Sampling and RM@N inference optimization.
Q: What are the recommended use cases?
The model is primarily designed for training pipeline integration, specifically for response quality assessment, reinforcement learning training, and implementing Best-of-N sampling strategies to improve mathematical problem-solving capabilities.
