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

Code Repository for "SFT: Few-Shot Learning via Self-Supervised Feature Fusion With Transformer"

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.

A slim implementation of Self-Pooling Transformer for hyperspectral image classification.

Code release for Proto-CLIP: Vision-Language Prototypical Network for Few-Shot Learning

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

Using Few Shot Learning (FSL) for image classification on Oxford 17 Flowers dataset. Part of HKU COMP3340 Group 10 Project (2023-24 Sem2).

Few-Shot Graph Classification via distance metric learning.

Code Release of Exploring Sample Relationship for Few-Shot Classification

Code Repository for "SSL-ProtoNet: Self-supervised Learning Prototypical Networks for few-shot learning"

A demonstration repo for how to do automatic translation using local llms.

Mineral Prediction based on Prototype Learning

Official implementation of the paper: Learn to aggregate global and local representations for few-shot learning

[ICCV 2023] Prompt-aligned Gradient for Prompt Tuning

[TIP-2023] IEEE Trans.on Image Processing

The code for "SCL: Self-supervised contrastive learning for few-shot image classification"

Supplementary Material For the Paper "NUTS, NARS, and Speech"

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

Official Implementation of CVPR 2023 paper: "Meta-Learning with a Geometry-Adaptive Preconditioner"