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mahaswec/setfit_ostrom
setfit_ostrom is a text classification model from mahaswec. Use it when you need a label for a piece of text. It is set up for sentence-transformers. The card lists the license as apache-2.0.
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
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From the Hugging Face model README
This is a SetFit model that can be used for text classification. The model has been trained using an efficient few-shot learning technique that involves:
Model is meant to classify Ostrom rule types for institutional analysis. Read more at https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=5845434
###Performance

To use this model for inference, first install the SetFit library:
python -m pip install setfit
You can then run inference as follows:
from setfit import SetFitModel
# Download from Hub and run inference
model = SetFitModel.from_pretrained("mahaswec/setfit_ostrom")
# Run inference
preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
@article{Yin2025-rt,
title = "Governing the digital commons at scale: Detecting Ostrom rule types
in {OSS}",
author = "Yin, Likang and Atkisson, Curtis and Chakraborti, Mahasweta and
Ruiz, Santiago Virguez and Bushouse, Brenda and Schweik, Charlie
and Frey, Seth and Filkov, Vladimir",
year = 2025
}