KoSimCSE-roberta is a RoBERTa-based model trained with SimCSE for Korean sentence representation learning. It produces high-quality embeddings for semantic textual similarity, retrieval, and clustering tasks in Korean. The model is compatible with Hugging Face Transformers and text-embeddings-inference.
KoSimCSE Roberta is a Foundation models & chat product. It focuses on generating high-quality Korean sentence embeddings for semantic search and similarity tasks. KoSimCSE Roberta is an open-source project aimed at NLP researchers and Korean language developers. The project is open source (Open Source). The product ships for the web.
It is developed by BM-K (South Korea), and the product first shipped in 2022. Among its 3 catalogued features are Sentence Embeddings, Semantic Similarity, and Korean NLP. It exposes integrations via a public API.
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