CrossEncoder
AssessLanguages & Frameworks
A reranking model that scores a query-document pair jointly for relevance.
Why it's here
Placed in Assess: 1 article(s) of evidence from 1 source(s), led by model releases, with 0 in the last 30 days. Confidence 24%. Low accumulated evidence, so it defaults conservatively pending more signal.
Evidence (1)
- 7Hugging Face Blog·5/19/2026model_releaseHugging Face releases Ettin reranker family
Hugging Face announced six new Sentence Transformers CrossEncoder rerankers built on Ettin ModernBERT encoders, ranging from 17M to 1B parameters. The release includes the models, training data, and full training recipe, and positions them for retrieve-then-rerank pipelines alongside embedding models.