Sentence Transformers is a Python framework for computing dense vector representations for sentences and paragraphs. These representations, also known as sentence embeddings, capture the semantic meaning of the text. They are commonly used for tasks such as semantic similarity search, clustering, and information retrieval. Unlike traditional word embedding methods, Sentence Transformers are trained to directly optimize for sentence-level similarity, leading to better performance in many applications.
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