Sentence Transformers: all-mpnet-base-v2embedding

Описание

The all-mpnet-base-v2 embedding model encodes sentences and short paragraphs into a 768-dimensional dense vector space, providing high-fidelity semantic embeddings well suited for tasks like information retrieval, clustering, similarity scoring, and...

Возможности

Модальности

Характеристики

API и примеры кода

from openai import OpenAI

client = OpenAI(
    base_url="https://infergate.ru/api/v1",
    api_key="ig-•••",
)

resp = client.embeddings.create(
    model="sentence-transformers/all-mpnet-base-v2",
    input="Текст для векторизации",
)
print(resp.data[0].embedding[:8])

Поддерживаемые параметры запроса