This is a Korean SBERT (Sentence-BERT) model fine-tuned on the KLUE NLI and STS datasets. It generates dense vector embeddings for Korean sentences that can be used for semantic search, clustering, or similarity computation. The model is compatible with the sentence-transformers library and optimized for Korean language understanding.
KR SBERT Medium klueNLI klueSTS sits in PulseGate's Embeddings & retrieval category. It focuses on computing high-quality semantic embeddings and similarity scores for Korean sentences. It is built as an open-source project for developers. KR SBERT Medium klueNLI klueSTS is open source under the Apache-2.0 license. It runs on the web, the command line, and API.
Behind KR SBERT Medium klueNLI klueSTS is snunlp, and it first shipped in 2019. The project is developed in the open on GitHub with 18.9k stars and 97 commits in the last 90 days.
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