license: apache-2.0
tags:

• setfit
• sentence-transformers
• text-classification
  pipeline_tag: text-classification

librarian-bots/is_new_dataset_teacher_model

这是一个基于SetFit模型的文本分类工具。该模型通过高效的小样本学习技术训练完成，具体包含两个阶段：

1. 使用对比学习微调Sentence Transformer
2. 基于微调后的Sentence Transformer提取特征训练分类头

使用说明

运行推理前请先安装SetFit库：

python -m pip install setfit  

按以下方式调用模型：

from setfit import SetFitModel  

# 从Hub加载模型并推理  
model = SetFitModel.from_pretrained("librarian-bots/is_new_dataset_teacher_model")  
# 执行推理  
preds = model(["蜘蛛侠电影太棒了！", "披萨上加菠萝简直是黑暗料理 🤮"])  

文献引用

@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 = {无需提示词的高效小样本学习},  
publisher = {arXiv},  
year = {2022},  
copyright = {Creative Commons Attribution 4.0 International}  
}