Instructions to use ucberkeley-dlab/hate-measure-roberta-large with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use ucberkeley-dlab/hate-measure-roberta-large with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy) # See https://github.com/keras-team/tf-keras for more details. from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("ucberkeley-dlab/hate-measure-roberta-large") - Notebooks
- Google Colab
- Kaggle
metadata
language:
- en
tags:
- text-classification
- hate-speech
- counterspeech
- irt
- arxiv:2009.10277
datasets:
- ucberkeley-dlab/measuring-hate-speech
Measuring hate speech: RoBERTa-Large
This model predicts a continuous hate speech score as described in Kennedy et al. (2020).
Citation
@article{kennedy2020constructing,
title={Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application},
author={Kennedy, Chris J and Bacon, Geoff and Sahn, Alexander and von Vacano, Claudia},
journal={arXiv preprint arXiv:2009.10277},
year={2020}
}
References
Kennedy, C. J., Bacon, G., Sahn, A., & von Vacano, C. (2020). Constructing interval variables via faceted Rasch measurement and multitask deep learning: a hate speech application. arXiv preprint arXiv:2009.10277.