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  <hr>
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  <div align="center" style="line-height: 1;">
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- <a href="https://www.deepseek.com/"><img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true"/></a>
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- <a href="https://chat.deepseek.com/"><img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DeepSeek%20V3-536af5?color=536af5&logoColor=white"/></a>
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- <a href="https://huggingface.co/deepseek-ai"><img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DeepSeek%20AI-ffc107?color=ffc107&logoColor=white"/></a>
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- <br>
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- <a href="https://discord.gg/Tc7c45Zzu5"><img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da"/></a>
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- <a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/qr.jpeg?raw=true"><img alt="Wechat" src="https://img.shields.io/badge/WeChat-DeepSeek%20AI-brightgreen?logo=wechat&logoColor=white"/></a>
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- <a href="https://twitter.com/deepseek_ai"><img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-deepseek_ai-white?logo=x&logoColor=white"/></a>
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- <br>
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- <a href="https://github.com/deepseek-ai/DeepSeek-V3/blob/main/LICENSE-CODE"><img alt="Code License" src="https://img.shields.io/badge/Code_License-MIT-f5de53?&color=f5de53"/></a>
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- <a href="https://github.com/deepseek-ai/DeepSeek-V3/blob/main/LICENSE-MODEL"><img alt="Model License" src="https://img.shields.io/badge/Model_License-Model_Agreement-f5de53?&color=f5de53"/></a>
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- <br>
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- <a href="https://github.com/deepseek-ai/DeepSeek-Prover-V2/blob/master/DeepSeek_Prover_V2.pdf"><b>Paper Link</b>👁️</a>
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  </div>
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- <p align="center">
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- <a href="#2-model-summary">Model Summary</a> |
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- <a href="#3-proverbench">ProverBench</a> |
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- <a href="#4-model-dataset-downloads">Model&Dataset Download</a> |
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- <a href="#5-quick-start">Quick Start</a> |
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- <a href="#6-license">License</a> |
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- <a href="#7-contact">Contact</a>
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- </p>
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- # DeepSeek-Prover-V2: Advancing Formal Mathematical Reasoning via Reinforcement Learning for Subgoal Decomposition
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ## 1. Introduction
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  We introduce DeepSeek-Prover-V2, an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals. The proofs of resolved subgoals are synthesized into a chain-of-thought process, combined with DeepSeek-V3's step-by-step reasoning, to create an initial cold start for reinforcement learning. This process enables us to integrate both informal and formal mathematical reasoning into a unified model.
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  <p align="center">
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- <img width="100%" src="figures/performance.png">
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  </p>
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  ## 2. Model Summary
 
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  <hr>
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  <div align="center" style="line-height: 1;">
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+ <a href="https://www.deepseek.com/" target="_blank" style="margin: 2px;">
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+ <img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://chat.deepseek.com/" target="_blank" style="margin: 2px;">
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+ <img alt="Chat" src="https://img.shields.io/badge/🤖%20Chat-DeepSeek%20V3-536af5?color=536af5&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://huggingface.co/deepseek-ai" target="_blank" style="margin: 2px;">
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+ <img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DeepSeek%20AI-ffc107?color=ffc107&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
 
 
 
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  </div>
 
 
 
 
 
 
 
 
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+ <div align="center" style="line-height: 1;">
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+ <a href="https://discord.gg/Tc7c45Zzu5" target="_blank" style="margin: 2px;">
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+ <img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/qr.jpeg?raw=true" target="_blank" style="margin: 2px;">
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+ <img alt="Wechat" src="https://img.shields.io/badge/WeChat-DeepSeek%20AI-brightgreen?logo=wechat&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://twitter.com/deepseek_ai" target="_blank" style="margin: 2px;">
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+ <img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-deepseek_ai-white?logo=x&logoColor=white" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ </div>
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+
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+ <div align="center" style="line-height: 1;">
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+ <a href="https://github.com/deepseek-ai/DeepSeek-V3/blob/main/LICENSE-CODE" style="margin: 2px;">
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+ <img alt="Code License" src="https://img.shields.io/badge/Code_License-MIT-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ <a href="https://github.com/deepseek-ai/DeepSeek-V3/blob/main/LICENSE-MODEL" style="margin: 2px;">
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+ <img alt="Model License" src="https://img.shields.io/badge/Model_License-Model_Agreement-f5de53?&color=f5de53" style="display: inline-block; vertical-align: middle;"/>
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+ </a>
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+ </div>
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  ## 1. Introduction
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  We introduce DeepSeek-Prover-V2, an open-source large language model designed for formal theorem proving in Lean 4, with initialization data collected through a recursive theorem proving pipeline powered by DeepSeek-V3. The cold-start training procedure begins by prompting DeepSeek-V3 to decompose complex problems into a series of subgoals. The proofs of resolved subgoals are synthesized into a chain-of-thought process, combined with DeepSeek-V3's step-by-step reasoning, to create an initial cold start for reinforcement learning. This process enables us to integrate both informal and formal mathematical reasoning into a unified model.
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  <p align="center">
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+ <img width="100%" src="https://github.com/deepseek-ai/DeepSeek-Prover-V2/blob/main/figures/performance.png">
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  </p>
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  ## 2. Model Summary