Sentence Transformers: paraphrase-MiniLM-L6-v2
sentence-transformers/paraphrase-minilm-l6-v2The paraphrase-MiniLM-L6-v2 embedding model converts sentences and short paragraphs into a 384-dimensional dense vector space, producing high-quality semantic embeddings optimized for paraphrase detection, semantic similarity scoring, clustering, and lightweight retrieval tasks.
Провайдер для Sentence Transformers: paraphrase-MiniLM-L6-v2
Hubris маршрутизирует запросы к лучшему доступному провайдеру с автоматическим fallback при сбоях.
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Sentence Transformers: all-MiniLM-L6-v2
The all-MiniLM-L6-v2 embedding model maps sentences and short paragraphs into a 384-dimensional dense vector space, enabling high-quality semantic representations that are ideal for downstream tasks such as information retrieval, clustering, similarity scoring, and text ranking.