Skywork-o1-Open-PRM-Qwen-2.5-7B
Skywork models enhance AI reasoning tasks, suitable for researchers and developers, offering multilingual support and advanced code evaluation capabilities.
English
English
What is Skywork-o1-Open-PRM-Qwen-2.5-7B?
Skywork-o1-Open-PRM-Qwen-2.5-7B is a model developed by the Skywork team at Kunlun Tech. This model series integrates o1 style slow thinking and reasoning capabilities. It excels in complex tasks like mathematical problem-solving and code evaluation. The model shows significant improvements in standard benchmarks and supports multiple languages including Chinese and English. It includes three advanced models: Skywork o1 Open-Llama-3.1-8B, Skywork o1 Open-PRM-Qwen-2.5-1.5B, and Skywork o1 Open-PRM-Qwen-2.5-7B.
Who is the target audience for Skywork-o1-Open-PRM-Qwen-2.5-7B?
The target audience includes AI researchers, data scientists, and developers who need to handle complex reasoning tasks and code evaluations. This model series can help them improve efficiency and accuracy in scenarios involving large-scale data and complex logical reasoning.
How can Skywork-o1-Open-PRM-Qwen-2.5-7B be used?
In mathematical problem-solving, the model can generate reasoning steps and rewards based on given problems and answers. For code evaluation, it can score each step of the code, helping to optimize quality. It also handles multilingual datasets effectively.
What are the key features of Skywork-o1-Open-PRM-Qwen-2.5-7B?
Enhanced Reasoning: Significant improvement in standard benchmark tests.
Multiple Models: Includes Skywork o1 Open-Llama-3.1-8B, Skywork o1 Open-PRM-Qwen-2.5-1.5B, and Skywork o1 Open-PRM-Qwen-2.5-7B.
Incremental Rewards: Skywork o1 Open-PRM-Qwen-2.5-1.5B uses incremental process rewards to enhance reasoning.
Extended Tasks: Skywork o1 Open-PRM-Qwen-2.5-7B extends the capabilities of the 1.5B model for more challenging tasks.
Multilingual Support: Supports both Chinese and English datasets.
Competitive Datasets: Uses Olympic-level datasets like OlympiadBench, AIME-24, and AMC-23.
Code Evaluation: Involves code evaluation using datasets like HumanEval, MBPP, and LiveCodeBench.
How do you use Skywork-o1-Open-PRM-Qwen-2.5-7B?
1. Clone the Skywork PRM inference repository using git commands.
2. Prepare input data and run PRM inference according to provided examples.
3. Install vllm and vllm PRM plugins via pip.
4. Configure and start the vllm server for model inference.
5. Send a request to the vllm server for inference and receive results using provided code examples.
