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license: cc-by-nc-4.0 |
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--- |
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# CPRetriever-Prob |
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**CPRetriever-Prob** is a sentence embedding model trained for competitive programming problem retrieval. |
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This model can be directly used via the `sentence-transformers` library. |
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Visit https://cpret.online/ to try out **CPRet** in action for competitive programming problem retrieval — powered by the **CPRetriever-Prob** model. |
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## 🔧 Usage |
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```python |
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from sentence_transformers import SentenceTransformer |
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model = SentenceTransformer("coldchair16/CPRetriever-Prob") |
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embeddings = model.encode([ |
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"Given a sequence of n numbers, answer m range mex queries.", |
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"求一个长度为 n 的数列的区间 mex。" |
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]) |
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``` |
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## 💡 Applications |
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This model powers the retrieval demo in [CPRet](https://github.com/coldchair/CPRet), supporting several practical use cases: |
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* It can assist in **duplicate problem detection** by retrieving potentially similar problems — final identification still requires manual verification. |
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* It also supports **similar problem retrieval** to help broaden your problem-solving perspective. |
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* You can input either a **full problem description** or a **simplified version**, and the system will return the most relevant existing problems. |
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## 📚 Training and Evaluation |
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For training pipeline, evaluation benchmark, and retrieval demo, please refer to the full codebase: |
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👉 [CPRet on GitHub](https://github.com/coldchair/CPRet?tab=readme-ov-file) |
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## 📦 Model Card |
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* Architecture: `Salesforce/SFR-Embedding-Code-2B_R` (encoder backbone) |
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* Tasks: Contrastive pretraining + task-specific fine-tuning on programming problem pairs |
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* Format: Compatible with `sentence-transformers` |
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