Text Ranking
sentence-transformers
Safetensors
English
qwen3
finance
legal
code
stem
medical
custom_code
Instructions to use zeroentropy/zerank-1-reranker with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- sentence-transformers
How to use zeroentropy/zerank-1-reranker with sentence-transformers:
from sentence_transformers import CrossEncoder model = CrossEncoder("zeroentropy/zerank-1-reranker", trust_remote_code=True) query = "Which planet is known as the Red Planet?" passages = [ "Venus is often called Earth's twin because of its similar size and proximity.", "Mars, known for its reddish appearance, is often referred to as the Red Planet.", "Jupiter, the largest planet in our solar system, has a prominent red spot.", "Saturn, famous for its rings, is sometimes mistaken for the Red Planet." ] scores = model.predict([(query, passage) for passage in passages]) print(scores) - Notebooks
- Google Colab
- Kaggle
Commit History
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Update model card with paper and GitHub links
Verified signatureThis PR improves the model card for `zeroentropy/zerank-1` by: - Adding a direct link to the associated research paper, [zELO: ELO-inspired Training Method for Rerankers and Embedding Models](https://huggingface.co/papers/2509.12541), at the top of the content. - Including a direct link to the GitHub repository, [https://github.com/zeroentropy-ai/zbench](https://github.com/zeroentropy-ai/zbench), for easier access to the project's code. - Updating the reference to the "Technical Report (Coming soon!)" within the model description to point to the new paper link, providing complete context.df705d9
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Add Sentence Transformers library_name (#1)
Verified signature- Add Sentence Transformers library_name (c66ff2d1e270311898f1d23a512afb9a4edaa762) Co-authored-by: Tom Aarsen <tomaarsen@users.noreply.huggingface.co>e00a879
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