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Zerank-1-Small-GGUF
seamon67/Zerank-1-Small-GGUF
Zerank-1-Small-GGUF is a text ranking model from seamon67. Use it for the text ranking task on the model card, and read the license before you ship it in a product. It is set up for llama.cpp. The card lists the license as apache-2.0.
This model was converted to GGUF format from zeroentropy/zerank-1-small-reranker using a modified version of llama.cpp (release b10269). Refer to the original model card for more details on the model.
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At a glance
- Task
- Text Ranking
- Library
- llama.cpp
- License
- apache-2.0
- Access
- Public
- Created
- Aug 7, 2026
- Updated
- Sep 22, 2026
- SHA
- a2f25eb4
Base models
Model card
From the Hugging Face model README
About
This model was converted to GGUF format from zeroentropy/zerank-1-small-reranker using a modified version of llama.cpp (release b10269). Refer to the original model card for more details on the model.
This is a working GGUF.
Most community GGUFs of Zerank-1-Small-Reranker produce garbage scores because of 4 issues:
- Zerank 1 Small ships
modeling_zeranker.pyinstead of1_LogitScoredirectory. - Wrong Token Extracted ->
yes(9693) vs the correctYes(9454). Also, no false token on Zerank 1 Small. - Wrong Scoring Formula -> Zerank 1 Small needs
sigmoid(yes_logit / 5). - Slightly different chat template.
This GGUF fixes all 4 problems.
Original Model Card
<img src="https://i.imgur.com/oxvhvQu.png"/>Releasing zeroentropy/zerank-1-small
In search enginers, rerankers are crucial for improving the accuracy of your retrieval system.
This 1.7B reranker is the smaller version of our flagship model zeroentropy/zerank-1. Though the model is over 2x smaller, it maintains nearly the same standard of performance, continuing to outperform other popular rerankers, and displaying massive accuracy gains over traditional vector search.
We release this model under the open-source Apache License 2.0, in order to support the open-source community and push the frontier of what's possible with open-source models.
Model Details
| Property | Value |
|---|---|
| Parameters | 1.7B |
| Context Length | 32,768 tokens (32k) |
| Base Model | Qwen/Qwen3-4B |
| License | Apache-2.0 |
How to Use
from sentence_transformers import CrossEncoder
model = CrossEncoder("zeroentropy/zerank-1-small", trust_remote_code=True)
query_documents = [
("What is 2+2?", "4"),
("What is 2+2?", "The answer is definitely 1 million"),
]
scores = model.predict(query_documents)
print(scores)
The model can also be inferenced using ZeroEntropy's /models/rerank endpoint.
Evaluations
NDCG@10 scores between zerank-1-small and competing closed-source proprietary rerankers. Since we are evaluating rerankers, OpenAI's text-embedding-3-small is used as an initial retriever for the Top 100 candidate documents.
| Task | Embedding | cohere-rerank-v3.5 | Salesforce/Llama-rank-v1 | zerank-1-small | zerank-1 |
|---|---|---|---|---|---|
| Code | 0.678 | 0.724 | 0.694 | 0.730 | 0.754 |
| Conversational | 0.250 | 0.571 | 0.484 | 0.556 | 0.596 |
| Finance | 0.839 | 0.824 | 0.828 | 0.861 | 0.894 |
| Legal | 0.703 | 0.804 | 0.767 | 0.817 | 0.821 |
| Medical | 0.619 | 0.750 | 0.719 | 0.773 | 0.796 |
| STEM | 0.401 | 0.510 | 0.595 | 0.680 | 0.694 |
<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"/>
License
This model is licensed under the Apache License 2.0.
- Task
- Text Ranking
- Library
- llama.cpp
- License
- apache-2.0
- Languages
- en
- Created
- Aug 7, 2026
- Updated
- Sep 22, 2026