SentenceTransformer based on intfloat/multilingual e5 small This is a sentence transformers model finetuned from intfloat/multilingual e5 small on datasets that include Korean query passage pairs for improved performance on Korean retrieval tasks. It maps sentences & paragraphs to a 384 dimensional dense vector space and can be used for semantic textual similarity, semantic search, paraphrase mining, text classification, clustering, and more. This model is a lightweight Korean retriever, designed for ease of use and strong performance in practical retrieval tasks. It is ideal for running demos or lightweight applications, offering a good balance between speed and accuracy. This small sized model delivers superior performance on Korean benchmarks compared to the much larger 'intfloat/multilingual e5 base' model (which has over 2x parameters). This means that you can enjoy performance superior to the base model while using half the computing resources. For even higher retrieval performance, we recommend combining it with a reranker. Suggested reranker models: dragonkue/bge reranker v2 m3 ko BAAI/bge reranker v2 m3 Model Details Model Description Model Type: Sentence Transformer Maxim…
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