README.md

metadata

license: cc-by-nc-4.0

CPRetriever-Prob

CPRetriever-Prob is a sentence embedding model trained for competitive programming problem retrieval.

This model can be directly used via the sentence-transformers library.

Visit https://cpret.online/ to try out CPRet in action for competitive programming problem retrieval — powered by the CPRetriever-Prob model.

🔧 Usage

from sentence_transformers import SentenceTransformer

model = SentenceTransformer("coldchair16/CPRetriever-Prob")
embeddings = model.encode([
    "Given a sequence of n numbers, answer m range mex queries.",
    "求一个长度为 n 的数列的区间 mex。"
])

💡 Applications

This model powers the retrieval demo in CPRet, supporting several practical use cases:

• It can assist in duplicate problem detection by retrieving potentially similar problems — final identification still requires manual verification.
• It also supports similar problem retrieval to help broaden your problem-solving perspective.
• You can input either a full problem description or a simplified version, and the system will return the most relevant existing problems.

📚 Training and Evaluation

For training pipeline, evaluation benchmark, and retrieval demo, please refer to the full codebase: 👉 CPRet on GitHub

📦 Model Card

• Architecture: Salesforce/SFR-Embedding-Code-2B_R (encoder backbone)
• Tasks: Contrastive pretraining + task-specific fine-tuning on programming problem pairs
• Format: Compatible with sentence-transformers