Ruri Reranker: Japanese General Reranker Ruri v3 Reranker is a general purpose Japanese reranker model built on top of ModernBERT Ja . Ruri v3 offers several key technical advantages: State of the art performance with good robustness for vaious domains Supports sequence lengths up to 8192 tokens Expanded vocabulary of 100K tokens , compared to 32K in v1 and v2 Integrated FlashAttention , following ModernBERT's architecture Tokenizer based solely on SentencePiece How to Use You can use our models directly with the transformers library v4.48.0 or higher: Additionally, if your GPUs support Flash Attention 2, we recommend using our models with Flash Attention 2. Example Usage (Sentence Transformers) Benchmarks Model Param.(w/o Emb.) JQaRA nDCG@10 JaCWIR MAP@10 MIRACL Recall@30 : : : : : : : : : Ruri v3 reranker 310m 315M (236M) 86.9 95.4 97.3 hotchpotch/japanese reranker cross encoder xsmall v1 107M (11M) 61.4 93.8 90.6 hotchpotch/japanese reranker cross encoder small v1 118M (21M) 62.5 93.9 92.2 hotchpotch/japanese reranker cross encoder base v1 111M (86M) 67.1 93.4 93.3 hotchpotch/japanese reranker cross encoder large v1 337M (303M) 71.0 93.6 91.5 hotchpotch/japanese bge reranker v2…
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