nlpai-lab/KURE-v1
feature-extraction model by nlpai-lab
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Model card & documentation
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Introducing Korea University Retrieval Embedding model, KURE-v1 It has shown remarkable performance in Korean text retrieval, speficially overwhelming most multilingual embedding models. To our knowledge, It is one of the best publicly opened Korean retrieval models. For details, visit the KURE repository This is the model card of a 🤗 transformers model that has been pushed on the Hub. First install…
Read the full model card ↗ · Preview checked 2026-10-31T20:48:30.099Z
Inside the original model card — Document outline
- 🔎 KURE-v1
- Model Versions
- Model Description
- Example code
- Install Dependencies
- Python code
- Training Details
- Training Data
- KURE-v1
- Training Procedure
- Evaluation
- Metrics
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Model overview
nlpai-lab/KURE-v1 is a feature-extraction model repository published by nlpai-lab 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
- feature-extraction
- Library
- sentence-transformers
- Recent downloads (30 days)
- 461,774
- Cumulative likes
- 102
- Hugging Face trending score
- 1
- Reported safetensors parameters
- 567,754,752
- Architecture
- XLMRobertaModel
- License
- mit
- Access
- Not gated by Hugging Face
- Created
- 2024-12-18T15:03:47.000Z
- Last modified
- 2026-09-07T06:34:55.000Z
Compatibility and lineage
Language coverage was not reported.
Reported base models: BAAI/bge-m3
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 2026-11-01T06:54:29.511Z. Daily imports are snapshots, not real-time monitoring.
Popularity and source listings do not establish security, suitability, licensing rights or benchmark performance.