Skywork-o1-Open-PRM-Qwen-2.5-1.5B
| Property | Value |
|---|---|
| Base Model | Qwen2.5-Math-1.5B-Instruct |
| License | Skywork Community License |
| Primary Use | Text Classification / Reward Modeling |
| Framework | PyTorch |
What is Skywork-o1-Open-PRM-Qwen-2.5-1.5B?
This is a specialized Process Reward Model (PRM) developed by Skywork, designed to enhance reasoning capabilities through incremental process rewards. It's part of the Skywork o1 Open model series, specifically optimized for mathematical and coding tasks evaluation.
Implementation Details
Built on the Qwen2.5-Math-1.5B-Instruct architecture, this model implements a novel approach to evaluating reasoning processes step-by-step rather than just final outputs. The model demonstrates strong performance across various mathematical and coding benchmarks, including GSM8K, MATH, GaoKao, and various coding tasks.
- Implements Best-of-N@64 sampling strategy for optimal performance
- Supports both mathematical and code evaluation tasks
- Compatible with vLLM server deployment for efficient inference
Core Capabilities
- Mathematical reasoning evaluation across multiple difficulty levels
- Step-wise assessment of problem-solving processes
- Strong performance on competition-level datasets
- Code evaluation capabilities on benchmarks like MBPP and HumanEval
Frequently Asked Questions
Q: What makes this model unique?
The model's ability to evaluate reasoning processes incrementally, providing rewards for each step rather than just the final answer, sets it apart from traditional reward models. This enables more nuanced assessment of problem-solving approaches.
Q: What are the recommended use cases?
The model excels at evaluating mathematical problem-solving and code generation tasks. It's particularly useful for educational applications, automated assessment systems, and AI model training where step-by-step reasoning evaluation is crucial.
