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:
1from setfit import SetFitModel
2
3# Download from Hub and run inference
4model = SetFitModel.from_pretrained("kimnt93/en_seed_task_cls")
5# Run inference
6preds = model(["i loved the spiderman movie!", "pineapple on pizza is the worst 🤮"])
1@article{https://doi.org/10.48550/arxiv.2209.11055,
2doi = {10.48550/ARXIV.2209.11055},
3url = {https://arxiv.org/abs/2209.11055},
4author = {Tunstall, Lewis and Reimers, Nils and Jo, Unso Eun Seo and Bates, Luke and Korat, Daniel and Wasserblat, Moshe and Pereg, Oren},
5keywords = {Computation and Language (cs.CL), FOS: Computer and information sciences, FOS: Computer and information sciences},
6title = {Efficient Few-Shot Learning Without Prompts},
7publisher = {arXiv},
8year = {2022},
9copyright = {Creative Commons Attribution 4.0 International}
10}
