README.md

metadata

language: zh
tags:
  - sbert
datasets:
  - dialogue
library_name: sentence-transformers
pipeline_tag: text-ranking

Data

train data is similarity sentence data from E-commerce dialogue, about 20w sentence pairs.

Model

model created by sentence-tansformers，model struct is cross-encoder

Usage

>>> from sentence_transformers.cross_encoder import CrossEncoder
>>> model = CrossEncoder('tuhailong/cross-encoder')
>>> scores = model.predict([["今天天气不错", "今天心情不错"]])
>>> print(scores)