README.md

metadata

pipeline_tag: text-classification
language:
  - it
datasets:
  - stsb_multi_mt
tags:
  - cross-encoder
  - sentence-similarity
  - transformers

Cross-Encoder

This model was trained using SentenceTransformers Cross-Encoder class.

Marco Lodola, Monument to Umberto Eco, Alessandria 2019

Training Data

This model was trained on stsb. The model will predict a score between 0 and 1 how for the semantic similarity of two sentences.

Usage and Performance

from sentence_transformers import CrossEncoder
model = CrossEncoder('efederici/cross-encoder-umberto-stsb')
scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])

The model will predict scores for the pairs ('Sentence 1', 'Sentence 2') and ('Sentence 3', 'Sentence 4').