paraphrase-MiniLM-L6-v2 · deepinfra
We present a sentence similarity model based on the Sentence Transformers architecture, which maps sentences to a 384-dimensional dense vector space. The model uses a pre-trained BERT encoder and applies mean pooling on top of the contextualized word embeddings to obtain sentence embeddings. We evaluate the model on the Sentence Embeddings Benchmark.
Entrée, $/1M $0.005
Sortie, $/1M —
Contexte 512
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Dernière vérification 04.11.2026 12:00:14 UTC
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ID: offer:deepinfra|sentence-transformers/paraphrase-MiniLM-L6-v2