metadata
pipeline_tag: text-ranking
language:
- it
datasets:
- stsb_multi_mt
tags:
- cross-encoder
- sentence-similarity
- transformers
library_name: sentence-transformers
Cross-Encoder
This model was trained using SentenceTransformers Cross-Encoder class.
Edouard Vuillard, Sunlit Interior
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').