mahaswec/setfit_ostrom

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:

  1. Fine-tuning a Sentence Transformer with contrastive learning.
  2. Training a classification head with features from the fine-tuned Sentence Transformer.

Model is meant to classify Ostrom rule types for institutional analysis. Read more at https://papers.ssrn.com/sol3/Delivery.cfm?abstractid=5845434

###Performance

image

Usage

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 🤮"])

BibTeX entry and citation info

@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
}
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