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')
.
- Downloads last month
- 38
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.