sbintuitions/sarashina-embedding-v1-1b
sentence-similarity model by sbintuitions
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Model card & documentation
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日本語のREADME/Japanese README "Sarashina-Embedding-v1-1B" is a Japanese text embedding model, based on the 1.2B-parameter Japanese LLM "Sarashina2.1-1B". We trained this model with multi-stage contrastive learning. We achieved the state-of-the-art average score across 16 datasets in JMTEB (Japanese Massive Text Embedding Benchmark). This model maps sentences & paragraphs to a 1792-dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and other applications. First install the Sentence Transformers library: Then you can load this model and run inference. Note "Sarashina-Embedding-v1-1B" is created through the following two-stage learning process: To achieve generic text embedding performance across a wide range of domains, we performed contrastive training on weakly-supervised…
Read the full model card ↗ · Preview checked 2026-10-31T09:22:28.267Z
Inside the original model card — Document outline
- Sarashina-Embedding-v1-1B
- Model Details
- Model Description
- Full Model Architecture
- Usage
- Training
- Stage 1: Weakly-supervised Learning
- Datasets
- Step2: Supervised Fine-tuning
- Datasets
- Evaluation Results with JMTEB
- License
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Model overview
sbintuitions/sarashina-embedding-v1-1b is a sentence-similarity model repository published by sbintuitions on Hugging Face. The source reports the sentence-transformers library.
This page summarizes Hub metadata. For intended use, training data, evaluation results and limitations, consult the original model card.
Model facts
- Task
- sentence-similarity
- Library
- sentence-transformers
- Recent downloads (30 days)
- 135,956
- Cumulative likes
- 38
- Hugging Face trending score
- 0
- Reported safetensors parameters
- 1,224,038,144
- Architecture
- LlamaModel
- License
- Not reported — check the model card
- Access
- Not gated by Hugging Face
- Created
- 2024-11-22T05:27:37.000Z
- Last modified
- 2025-01-31T00:56:25.000Z
Compatibility and lineage
Reported languages: ja, en
Base-model lineage was not included.
Parameter count is not a RAM/VRAM requirement. Check precision, quantization, context length and runtime compatibility in the model card; no hardware or API-cost claim is inferred here.
Use and evaluate
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Source and freshness
Source: Hugging Face Hub. Metadata observed 2026-10-02T06:40:29.845Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.
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