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.
In the Foundation models & chat space, KR SBERT Medium klueNLI klueSTS takes a focused approach. 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. The product ships for the web, the command line, and API.
Behind KR SBERT Medium klueNLI klueSTS is snunlp, and the product first shipped in 2019. Development happens publicly on GitHub with 18.9k stars and 97 commits in the last 90 days.
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