Instructions to use kanishka/dl-property-judgments with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use kanishka/dl-property-judgments with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="kanishka/dl-property-judgments")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("kanishka/dl-property-judgments") model = AutoModelForSequenceClassification.from_pretrained("kanishka/dl-property-judgments") - Notebooks
- Google Colab
- Kaggle
A DEBERTA model for making property judgments
deberta-v3-large fine-tuned to evaluate the truth of sentences that attribute properties to concepts.
Citation
If you use this model, please cite the following paper:
@inproceedings{misra2022property,
title={A Property Induction Framework for Neural Language Models},
author={Kanishka Misra and Julia Rayz and Allyson Ettinger},
booktitle={Proceedings of the 44th Annual Conference of the Cognitive Science Society},
year={2022}
}
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