Update README.md

README.md

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 🖥️[Code](https://github.com/dvlab-research/Step-DPO) | 🤗[Data](https://huggingface.co/datasets/xinlai/Math-Step-DPO-10K) | 📄[Paper](https://arxiv.org/pdf/2406.18629)
 
-This repo contains the **DeepSeekMath-RL-Step-DPO** model for our paper **Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs**, **Step-DPO** is a simple, effective, and data-efficient method for boosting the mathematical reasoning ability of LLMs. Notably, Step-DPO, when applied to Qwen2-72B-Instruct, achieves scores of **70.8%** and **94.0%** on the test sets of **MATH** and **GSM8K** without bells and wistles, respectively, surpassing a series of closed-source models, including GPT-4-1106, Claude-3-Opus, and Gemini-1.5-Pro.
+This repo contains the **DeepSeekMath-RL-Step-DPO** model. It is obtained by performing **Step-DPO** on [**DeepSeekMath-RL**](https://huggingface.co/deepseek-ai/deepseek-math-7b-rl).
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+**Step-DPO** is a simple, effective, and data-efficient method for boosting the mathematical reasoning ability of LLMs. Notably, Step-DPO, when applied to Qwen2-72B-Instruct, achieves scores of **70.8%** and **94.0%** on the test sets of **MATH** and **GSM8K** without bells and wistles, respectively, surpassing a series of closed-source models, including GPT-4-1106, Claude-3-Opus, and Gemini-1.5-Pro.
 
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