#Few-shot-learning
Showing 37 of 37 repositories tagged #few-shot-learning, ranked by stars
Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习
22 prompt engineering techniques with hands-on Jupyter Notebook tutorials, from fundamental concepts to advanced strategies for leveraging LLMs.
This repository contains a hand-curated resources for Prompt Engineering with a focus on Generative Pre-trained Transformer (GPT), ChatGPT, PaLM etc
总结Prompt&LLM论文，开源数据&模型，AIGC应用
Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning
FSL-Mate: A collection of resources for few-shot learning (FSL).
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
A novel method to tune language models. Codes and datasets for paper ``GPT understands, too''.
LLMs can generate feedback on their work, use it to improve the output, and repeat this process iteratively.
A dataset of datasets for learning to learn from few examples
Awesome Multitask Learning Resources
Meta-Baseline: Exploring Simple Meta-Learning for Few-Shot Learning, in ICCV 2021
The code repository for "Few-Shot Learning via Embedding Adaptation with Set-to-Set Functions"
[CVPR '21] Official repository for Few-shot Image Generation via Cross-domain Correspondence
Plug-and-play document AI with zero-shot models.
X-Trend: Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies
Source code for NeurIPS 2020 paper "Meta-Learning with Adaptive Hyperparameters"
Papers and code related to 'Less Than One'-Shot (LO-Shot) Learning
A comprehensive paper list of deep learning for crack detection, in terms of learning paradigms, generalizability and datasets.
Official PaddlePaddle Implementation of Few-Shot Font Generation by Learning Fine-Grained Local Styles (FsFont)
(CVPR-Oral 2021) PyTorch implementation of Knowledge Evolution approach and Split-Nets
A Survey of Task-Oriented Knowledge Graph Reasoning: Status, Applications, and Prospects
An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.
FlexKBQA: A Flexible LLM-Powered Framework for Few-Shot Knowledge Base Question Answering
[ICLR 2026] The implementation of the paper Foundation Visual Encoders Are Secretly Few-Shot Anomaly Detectors
Official Pytorch implementation of Multi-Similarity and Attention Guidence for Boosting Few-Shot Segmentation.
Implementation of our paper "Optimizing PatchCore for Few/many-shot Anomaly Detection"
Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)
Learning low-shot object classification with explicit shape bias learned from point clouds
State-of-the-art prompting techniques implementation with DSpy - Manager-style prompts, role personas, meta-prompting, and more
[NIPS2025] A decentralized, RAG-enhanced multi-agent framework for LLMs with dynamic task routing and agent evolution.
Implementation of Cross Transformer for spatially-aware few-shot transfer, in Pytorch
Service to import data from various sources and index it in AI Search. Increases data relevance and reduces final size by 90%+. Useful for RAG scenarios with LLM. Hosted in Azure with serverless architecture.
Examples of Prompt Engineering, Zero Shot Learning, Few Shot Learning and Retrieval Augmented Generation (RAG) using Hugging Face, Databricks and MLflow
This repository contains the code snippets used in "LLM Prompt Engineering For Developers"
On Bilingual Lexicon Induction with Large Language Models (EMNLP 2023). Keywords: Bilingual Lexicon Induction, Word Translation, Large Language Models, LLMs.
Timeless principles and best practices for working with language models - tooling-agnostic, future-proof, and clear.