Popular GitHub Repositories for Classifcation

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

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.

Repository of the ICNLSP 2024 paper "Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes"

Official implementation of "ImagineFSL: Self-Supervised Pretraining Matters on Imagined Base Set for VLM-based Few-shot Learning" [CVPR 2025 Highlight]

[AAAI 2023] This is the code for our paper `Neighborhood-Regularized Self-Training for Learning with Few Labels'.

Dynamic Few-Shot Prompting is a Python package that dynamically selects N samples that are contextually close to the user's task or query from a knowledge base (similar to RAG) to include in the prompt.

使用tensorflowjs对文言文和白话文分类

Training script for fine-tuning pretrained image classification models with PyTorch

Data-Science-and-Insight-Agent-RAG-LLama3-Lava-LLM-Django-WebApplication is an advanced AI-driven chatbot designed to assist in data science, document analysis, and image interpretation. This repository contain the Datascience Agent of this project.