Instructions to use tum-nlp/counter-narrative-classifier with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- TF-Keras
How to use tum-nlp/counter-narrative-classifier with TF-Keras:
# Note: 'keras<3.x' or 'tf_keras' must be installed (legacy), and from_pretrained_keras was removed in huggingface_hub 1.0. # See https://github.com/keras-team/tf-keras for more details. # !pip install "huggingface_hub<1.0" tf_keras from huggingface_hub import from_pretrained_keras model = from_pretrained_keras("tum-nlp/counter-narrative-classifier") - Notebooks
- Google Colab
- Kaggle
Target-Group Classifier
The BERT-based counter-argument classifier is finetuned on the combined dataset of CONAN and CrowdCounter for classifying whether a sequence is about one or multiple of the 8 target group, based on the sexism detector ThinkCERCA/counterargument_hugging
It classifies either a given sentence is a valid counter-narrative.
Uses
The model is intended for classifying LM-generated dialogue responses, and evaluating their validity as counter-narrative.
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Model tree for tum-nlp/counter-narrative-classifier
Base model
ThinkCERCA/counterargument_hugging