The Woman Worked as a Babysitter: On Biases in Language Generation
Paper β’ 1909.01326 β’ Published
How to use sasha/regardv3 with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="sasha/regardv3") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("sasha/regardv3")
model = AutoModelForSequenceClassification.from_pretrained("sasha/regardv3")This model is the result of a project entitled Towards Controllable Biases in Language Generation. It consists of a BERT classifier (no ensemble) trained on 1.7K samples of biased language.
Regard measures language polarity towards and social perceptions of a demographic (compared to sentiment, which only measures overall language polarity).
@article{sheng2019woman,
title={The woman worked as a babysitter: On biases in language generation},
author={Sheng, Emily and Chang, Kai-Wei and Natarajan, Premkumar and Peng, Nanyun},
journal={arXiv preprint arXiv:1909.01326},
year={2019}
}