---
pipeline_tag: text-classification
tags:
- cross-encoder
- sentence-similarity
- transformers
---
# Cross-Encoder

This model was trained using [SentenceTransformers](https://sbert.net) [Cross-Encoder](https://www.sbert.net/examples/applications/cross-encoder/README.html) class.

## Training Data

This model was trained on [stsb](https://huggingface.co/datasets/mteb/stsbenchmark-sts). The model will predict a score between 0 and 1 for how semantically similarity two sentences are. 

## Usage and Performance

```python
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](efederici/cross-encoder-bert-base-stsb) by @efederici.