KshitijKrishna/pivot-reranker

🔍 BGE Reranker Base (Fine-tuned)

This repository contains a fine-tuned cross-encoder reranker model based on BAAI/bge-reranker-base.

It is designed to improve retrieval pipelines by re-ranking top-K results from embedding models.

---

🚀 Key Features

• Cross-encoder reranking (query + passage scoring)
• Strong performance on MTEB / C-MTEB benchmarks
• Supports multilingual (English + Chinese)
• Optimized for semantic search pipelines

---

📦 Model Files

This repo contains:

✔ config.json
✔ model.safetensors
✔ tokenizer_config.json
✔ sentencepiece.bpe.model
✔ special_tokens_map.json (fixed naming)
✔ README.md

⚙️ Usage

🔹 Using FlagEmbedding (Recommended)

from FlagEmbedding import FlagReranker

reranker = FlagReranker("BAAI/bge-reranker-base", use_fp16=True)

score = reranker.compute_score(["query", "passage"])
print(score)