Jina Reranker v1 Tiny English
The tiny v1 reranker is an English relevance model with 33 million parameters and 4 transformer layers. Jina distilled it from the larger v1 base teacher to reduce inference cost.
How the model works
Its four-layer JinaBERT design keeps a 384-wide hidden state and symmetric bidirectional ALiBi. The documented context reaches 8,192 tokens. It performs cross-encoding: query and document are examined together, instead of comparing two previously computed sentence vectors.Jina Reranker v1 Tiny English model details
Use and access
The downloadable weights use Apache 2.0. Jina documents Python and JavaScript inference as well as its managed reranking service. This is a historical English release with accessible weights; later multilingual models do not make it a different model or remove its license. It returns relevance scores, not generated answers.Jina Reranker v1 Tiny English model detailsJina Reranker v1 Tiny English technical overview
Specifications & access
| Detail | Value and conditions |
|---|---|
| Launch date | |
| Access | Downloadable |
| Model identifiers | jina-reranker-v1-tiny-enjinaai/jina-reranker-v1-tiny-en |
| Context window | 8,192 tokens Maximum input sequence in the model card; serving limits can be lower. Jina Reranker v1 Tiny English model details |
| Parameters | 33 millionJina Reranker v1 Tiny English model details |
| Weight license | Apache 2.0Jina Reranker v1 Tiny English model details |
| Base model | JinaBERT; distilled from v1 Base EnglishJina Reranker v1 Tiny English model details |
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A six-layer English ranker between the tiny and base sizes.
Launch date Downloadable - Jina Reranker v1 Base English
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The original English query-document relevance model in Jina's reranking family.
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