Model reference · open weights

ruri-reranker

ruri-reranker is an open-weight embedding model from cl-nagoya, listed in the AxForge catalogue. AxForge can bring it up on EU-owned hardware for you on request — with the licence handled where one is required.

Embeddings cl-nagoya 1 variants 319k downloads/mo
Request this model on EU hardware All served models Not on the shared API today — deployed on request.

About

What ruri-reranker is

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 Details Model Description - Model Type: Sentence Transformer - Base model: cl-nagoya/ruri-v3-pt-310m - Maximum Sequence Length: 8192 tokens - Language: Japanese - License: Apache 2.0 - Paper: https://arxiv.org/abs/2409.07737 Citation License This model is published under the Apache License, Version 2.0.

Summarised from the published model card. Read the full card on the HuggingFace links below.

Specifications

What it is

Makercl-nagoya
TypeEmbedding models
Parameters (lead)315M
Context8k tokens
Variants1
Runs withsentence-transformers
Based oncl-nagoya/ruri-v3-pt-310m
Released2025-04-06
Popularity319k downloads / month
Likes15
LicenceOpen weights

How it works

How embedding models work

Your textsentence / documentEncodermaps meaningVectorlist of numbersAn embedding model turns text into a vector, so similar meanings sit close together — the basis of search and RAG.

Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

VariantParamsPrecisionVRAMFits 16 GBWeights
ruri-v3-reranker-310m315MBF16~0.7 GBWeights ↗

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys ruri-reranker for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (ruri-reranker below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/embeddings \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"ruri-reranker","input":"text to embed"}'

Details

Languages, data & research

Languages

ja

Trained / evaluated on

cl-nagoya/ruri-v3-dataset-reranker

Tags

sentence-transformers safetensors modernbert feature-extraction text-ranking ja dataset:cl-nagoya/ruri-v3-dataset-reranker text-embeddings-inference endpoints_compatible

Papers

Licence

Open weights

Open weights under apache-2.0 — commercial use is permitted. Deploy it on AxForge EU hardware on request. Read the licence ↗

Sources

Weights & code

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