Ruri Reranker: Japanese General Reranker Usage Direct Usage (Sentence Transformers) First install the Sentence Transformers library: Then you can load this model and run inference. Benchmarks Model Param.(w/oEmb.) JQaRA JaCWIR MIRACL : : : : : : : : : 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 m3 v1 568M(303M) 69.2 93.7 94.7 BAAI/bge reranker v2 m3 568M(303M) 67.3 93.4 94.9 Ruri Reranker Small (this model) 68M(43M) 64.5 92.6 92.3 Ruri Reranker Base 111M(86M) 74.3 93.5 95.6 Ruri Reranker Large 337M(303M) 77.1 94.1 96.1 Model Details Model Description Model Type: Sentence Transformer Base model: cl nagoya/ruri reranker stage1 small Maximum Sequence Length: 512 tokens Language: Japanese License: Apache 2.0 Paper: https://arxiv.org/abs/2409.07737 Training Details Framework Versions Python: 3.10.13 Sentence Transformers: 3.0.0 Transformers: 4.41.2 PyTorch: 2.3.1+cu118 Accelerate: 0.30.1 Dat…
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