Edit model card

Cross-Encoder

This model was trained using SentenceTransformers Cross-Encoder class.

Training Data

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

Usage and Performance

from sentence_transformers import CrossEncoder

model = CrossEncoder('tomaarsen/distilroberta-base-stsb-cross-encoder')
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').

Model Card Author

I adapted this model card from https://huggingface.co/efederici/cross-encoder-bert-base-stsb by @efederici.

Downloads last month
6
Safetensors
Model size
82.1M params
Tensor type
F32
·
Inference Examples
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.