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("ashercn97/code-y-v1")
5# Run inference
6preds = model("Given the symptoms described, the most likely karyotype for this 15-year-old boy is 47,XXY, which is characteristic of Klinefelter syndrome. The combination of decreased facial and pubic hair, gynecomastia, small testes, long extremities, and tall stature aligns with this chromosomal pattern. Klinefelter syndrome is caused by the presence of an extra X chromosome, leading to the 47,XXY karyotype.")
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}