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trans-encoder-bi-simcse-bert-base
cambridgeltl/trans-encoder-bi-simcse-bert-base
trans-encoder-bi-simcse-bert-base is a feature extraction model from cambridgeltl. Use it when you need embeddings to search or compare text. It is set up for transformers.
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At a glance
- Task
- Feature Extraction
- Library
- transformers
- Model type
- bert
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Nov 26, 2021
- SHA
- 1052e6c3
Model card
From the Hugging Face model README
language: en
tags:
- sentence-embeddings
- sentence-similarity
- dual-encoder
cambridgeltl/trans-encoder-bi-simcse-bert-base
An unsupervised sentence encoder (bi-encoder) proposed by Liu et al. (2021). The model is trained with unlabelled sentence pairs sampled from STS2012-2016, STS-b, and SICK-R, using princeton-nlp/unsup-simcse-bert-base-uncased as the base model. Please use [CLS] (before pooler) as the representation of the input.
Citation
@article{liu2021trans,
title={Trans-Encoder: Unsupervised sentence-pair modelling through self-and mutual-distillations},
author={Liu, Fangyu and Jiao, Yunlong and Massiah, Jordan and Yilmaz, Emine and Havrylov, Serhii},
journal={arXiv preprint arXiv:2109.13059},
year={2021}
}
- Task
- Feature Extraction
- Library
- transformers
- Type
- bert
- Created
- Mar 2, 2022
- Updated
- Nov 26, 2021