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README.md

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-license: cc-by-nc-4.0
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+---
+license: cc-by-nc-4.0
+---
+
+
+# CPRetriever-Code
+
+**CPRetriever-Code** is a code embedding model trained via contrastive learning for **code-related retrieval tasks** in competitive programming. It achieves strong performance on tasks such as:
+
+* **Text-to-Code** retrieval (problem description → relevant code)
+* **Code-to-Code** retrieval (find alternate solutions to the same problem)
+
+This model is part of the [CPRet](https://github.com/coldchair/CPRet) suite for competitive programming retrieval research.
+
+## 🔧 Usage
+
+You can load this model using the `sentence-transformers` library:
+
+```python
+from sentence_transformers import SentenceTransformer
+
+model = SentenceTransformer("coldchair16/CPRetriever-Code")
+embeddings = model.encode([
+    "def mex_query(arr):\n    n = len(arr)\n    seen = set()\n    for i in range(n):\n        seen.add(arr[i])\n    i = 0\n    while True:\n        if i not in seen:\n            return i\n        i += 1"
+])
+```
+
+## 💡 Applications
+
+This model is optimized for **code-level semantic retrieval** in competitive programming settings:
+
+* **Text-to-Code**: Retrieve relevant code snippets given a natural language problem description.
+* **Code-to-Code**: Retrieve alternative implementations of the same problem.
+
+It is particularly effective for analyzing programming contest submissions, searching solution variants, and building educational tools for code understanding.
+
+## 📚 Training and Evaluation
+
+CPRetriever-Code is trained via **contrastive learning** using positive and hard negative code pairs derived from [CPRet-data](https://huggingface.co/datasets/coldchair16/CPRet-data).
+
+For the training pipeline, see the full project:
+👉 [CPRet on GitHub](https://github.com/coldchair/CPRet?tab=readme-ov-file)
+
+## 📦 Model Card
+
+* Architecture: `Salesforce/SFR-Embedding-Code-2B_R` (encoder backbone)
+* Training: Contrastive objective on code/code and text/code pairs
+* Format: Compatible with `sentence-transformers`
+