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---
pipeline_tag: sentence-similarity
license: apache-2.0
tags:
- sentence-transformers
- feature-extraction
- sentence-similarity
- transformers
---
This is a [SCT](https://github.com/mrpeerat/SCT) model: It maps sentences to a dense vector space and can be used for tasks like semantic search.
## Usage
Using this model becomes easy when you have [SCT](https://github.com/mrpeerat/SCT) installed:
```
pip install -U git+https://github.com/mrpeerat/SCT
```
Then you can use the model like this:
```python
from sentence_transformers import SentenceTransformer
sentences = ["This is an example sentence", "Each sentence is converted"]
model = SentenceTransformer('mrp/SCT_Distillation_BERT_Tiny')
embeddings = model.encode(sentences)
print(embeddings)
```
## Evaluation Results
For an automated evaluation of this model, see the *Sentence Embeddings Benchmark*: [Semantic Textual Similarity](https://github.com/mrpeerat/SCT#main-results---sts)
## Citing & Authors
```bibtex
@article{limkonchotiwat-etal-2023-sct,
title = "An Efficient Self-Supervised Cross-View Training For Sentence Embedding",
author = "Limkonchotiwat, Peerat and
Ponwitayarat, Wuttikorn and
Lowphansirikul, Lalita and
Udomcharoenchaikit, Can and
Chuangsuwanich, Ekapol and
Nutanong, Sarana",
journal = "Transactions of the Association for Computational Linguistics",
year = "2023",
address = "Cambridge, MA",
publisher = "MIT Press",
}
``` |