NeST

Ready-to-use code and tutorial notebooks to boost your way into few-shot learning for image classification.

A curated list of awesome prompt/adapter learning methods for vision-language models like CLIP.

This repository contains an easy and intuitive approach to few-shot NER using most similar expansion over spaCy embeddings. Now with entity scoring.

This repository contains an easy and intuitive approach to few-shot classification using sentence-transformers or spaCy models, or zero-shot classification with Huggingface.

[ICCV'21] Official PyTorch implementation of Relational Embedding for Few-Shot Classification

Class for Aspect-term extraction and Aspect-based sentiment analysis with BERT and Adapters

This repository contains code to reproduce the results in our paper "Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets".

一种极其简单、无需验证、高效适应CLIP类视觉语言模型的方法，并且对学习率具有鲁棒性。

Few-Shot Graph Classification via distance metric learning.

Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)