This is a
SetFit model that can be used for Text Classification. This SetFit model uses
sentence-transformers/paraphrase-mpnet-base-v2 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("k3vin-samson/bank-transaction-classifeer")
5# Run inference
6preds = model("CARD NO.400536XXXXXX9172 CARS TAXI ABU DHABI:AE 882334 02-01-2025 14.50,AED")
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}
