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Introduction of setfit-zero-shot-classification-pbsp-p3-sev

Model Details of setfit-zero-shot-classification-pbsp-p3-sev

setfit-zero-shot-classification-pbsp-p3-sev

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:

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

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("setfit-zero-shot-classification-pbsp-p3-sev")
# Run inference
preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])

BibTeX entry and citation info

@article{https://doi.org/10.48550/arxiv.2209.11055,
doi = {10.48550/ARXIV.2209.11055},
url = {https://arxiv.org/abs/2209.11055},
author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {Efficient Few-Shot Learning Without Prompts},
publisher = {arXiv},
year = {2022},
copyright = {Creative Commons Attribution 4.0 International}
}

Runs of aammari setfit-zero-shot-classification-pbsp-p3-sev on huggingface.co

Total runs

-1

24-hour runs

-1

3-day runs

7-day runs

30-day runs

More Information About setfit-zero-shot-classification-pbsp-p3-sev huggingface.co Model

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https://choosealicense.com/licenses/apache-2.0

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setfit-zero-shot-classification-pbsp-p3-sev huggingface.co Url

https://huggingface.co/aammari/setfit-zero-shot-classification-pbsp-p3-sev

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setfit-zero-shot-classification-pbsp-p3-sev install

setfit-zero-shot-classification-pbsp-p3-sev is an open source model from GitHub that offers a free installation service, and any user can find setfit-zero-shot-classification-pbsp-p3-sev on GitHub to install. At the same time, huggingface.co provides the effect of setfit-zero-shot-classification-pbsp-p3-sev install, users can directly use setfit-zero-shot-classification-pbsp-p3-sev installed effect in huggingface.co for debugging and trial. It also supports api for free installation.