This is a
SetFit model that can be used for Text Classification. This SetFit model uses
sentence-transformers/LaBSE as the Sentence Transformer embedding model. A
LogisticRegression instance is used for classification.
The model has been trained using an efficient few-shot learning technique that involves:
Then you can load this model and run inference.
1from setfit import SetFitModel
2
3# Download from the 🤗 Hub
4model = SetFitModel.from_pretrained("Ezzaldin-97/LaBSE-based-Arabic-News-Classifier")
5# Run inference
6preds = model("نقلت صحيفة واشنطن بوست امس عن مستشار الرئيس الاميركي باراك اوباما للامن القومي قوله ان اوباما يعتزم توسيع عضوية مجلس الامن القومي وزيادة سلطته لوضع استراتيجية سلسلة واسعة من القضايا الداخلية والدولية.")
1@article{https://doi.org/10.48550/arxiv.2209.11055,
2 doi = {10.48550/ARXIV.2209.11055},
3 url = {https://arxiv.org/abs/2209.11055},
4 author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
5 keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
6 title = {Efficient Few-Shot Learning Without Prompts},
7 publisher = {arXiv},
8 year = {2022},
9 copyright = {Creative Commons Attribution 4.0 International}
10}