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README.md
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---
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license: cc-by-nc-4.0
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language:
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- en
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base_model:
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- Qwen/Qwen3-4B
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pipeline_tag: text-ranking
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tags:
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- finance
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- legal
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- code
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- stem
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- medical
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---
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# zerank-1: ZeroEntropy Inc.'s SoTA reranker
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<!-- Provide a quick summary of what the model is/does. -->
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This model is an open-weights reranker model meant to be integrated into RAG applications to rerank results from preliminary search methods such as embeddings, BM25, and hybrid search.
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This reranker outperforms all competitor rerankers, including ones twice its size, across a wide variety of task domains, including on finance, legal, code, STEM, medical, and conversational data. See [this post](https://evals_blog_post) for more details.
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This model is trained on an innovative multi-stage pipeline that models query-document relevance scores using adjusted Elo-like ratings. See [this post](https://technical_blog_post) and our Technical Report (Coming soon!) for more details.
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## How to Use
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## Evaluations
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Comparing NDCG@10 starting from top 100 documents by embedding (using text-3-embedding-small):
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| Task | Embedding | cohere-rerank-v3.5 | Salesforce/Llama-rank-v1 | zerank-1-small | zerank-1 |
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|----------------|-----------|--------------------|--------------------------|----------------|----------|
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| Code | 0.678 | 0.724 | 0.694 | 0.730 | 0.754 |
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| Conversational | 0.250 | 0.571 | 0.484 | 0.556 | 0.596 |
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| Finance | 0.839 | 0.824 | 0.828 | 0.861 | 0.894 |
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| Legal | 0.703 | 0.804 | 0.767 | 0.817 | 0.821 |
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| Medical | 0.619 | 0.750 | 0.719 | 0.773 | 0.796 |
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| STEM | 0.401 | 0.510 | 0.595 | 0.680 | 0.694 |
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Comparing BM25 and Hybrid Search without and with zerank-1:
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<img src="https://cdn-uploads.huggingface.co/production/uploads/67776f9dcd9c9435499eafc8/2GPVHFrI39FspnSNklhsM.png" alt="Description" width="400"/> <img src="https://cdn-uploads.huggingface.co/production/uploads/67776f9dcd9c9435499eafc8/dwYo2D7hoL8QiE8u3yqr9.png" alt="Description" width="400"/>
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## Citation
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**BibTeX:**
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Coming soon!
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**APA:**
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Coming soon!
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