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.

Базовая модельВсе модели этой базовойВсе модели провайдерак провайдеру

Все модели Sentence Transformers у всех провайдеров

Вход, $/1M $0.005

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Контекст 512

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Последняя проверка 04.11.2026 12:00:14 UTC

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