YAML Metadata Warning: empty or missing yaml metadata in repo card (https://huggingface.co/docs/hub/model-cards#model-card-metadata)

language: en

tags:

  • word-embeddings
  • word-similarity

mirror-bert-base-uncased-word

An unsupervised word encoder proposed by Liu et al. (2021). Trained with a set of unlabelled words, using bert-base-uncased as the base model. Please use [CLS] as the representation of the input.

Citation

@inproceedings{
    liu2021fast,
  title={Fast, Effective and Self-Supervised: Transforming Masked LanguageModels into Universal Lexical and Sentence Encoders},
  author={Liu, Fangyu and Vuli{\'c}, Ivan and Korhonen, Anna and Collier, Nigel},
  booktitle={EMNLP 2021},
  year={2021}
}
Downloads last month
13
Safetensors
Model size
109M params
Tensor type
I64
·
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.