59 Open source projects that are alternatives of or similar to P-tuning

Source code and data for ACL 2022 paper "P-tuning v2: Prompt Tuning Can Be Comparable to Fine-tuning Across Scales and Tasks"

PyTorch implementation of 'Squeeze and Excite' Guided Few Shot Segmentation of Volumetric Scans

Awesome Few-shot learning

LibFewShot: A Comprehensive Library for Few-shot Learning.

Code for ACL'19 "Few-Shot Representation Learning for Out-Of-Vocabulary Words"

📄 Spatial Contrastive Learning for Few-Shot Classification (ECML/PKDD 2021).

finetune bert for small dataset text classification in a few-shot learning manner using ProtoNet

Meta Learning / Learning to Learn / One Shot Learning / Few Shot Learning

Transfer learning / domain adaptation / domain generalization / multi-task learning etc. Papers, codes, datasets, applications, tutorials.-迁移学习

A collection of AWESOME things about domian adaptation

[CVPR '21] Official repository for Few-shot Image Generation via Cross-domain Correspondence

Awesome Domain Adaptation Python Toolbox

FewCLUE 小样本学习测评基准，中文版

The source code of "Language Models are Few-shot Multilingual Learners" (MRL @ EMNLP 2021)

Hands-On Deep Learning Algorithms with Python, By Packt

An unofficial implementation of MemoPainter(Coloring With Limited Data: Few-shot Colorization via Memory Augmented Networks) using PyTorch framework.

OpenMMLab FewShot Learning Toolbox and Benchmark

[IJCAI 2021] Cross-Domain Few-Shot Classification via Adversarial Task Augmentation

[CVPR 2020 VL3] The repository for meta fine-tuning in cross-domain few-shot learning.

A novel method for few shot learning

Official PyTorch implementation of "Meta-Learning with Task-Adaptive Loss Function for Few-Shot Learning" (ICCV2021 Oral)

Finetuning any DNN for better embedding on neural search tasks

Official repository of https://arxiv.org/abs/2111.04040v1

Learning low-shot object classification with explicit shape bias learned from point clouds

(CVPR 2021) Few-Shot Classification with Feature Map Reconstruction Networks

PyTorch implementation of the paper: Vector Projection Network for Few-shot Slot Tagging in Natural Language Understanding. Su Zhu, Ruisheng Cao, Lu Chen and Kai Yu.

A curated list of papers, code and resources pertaining to weak-shot classification, detection, and segmentation.

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

Codes for ACL-IJCNLP 2021 Paper "Zero-shot Fact Verification by Claim Generation"

A curated list of papers, code and resources pertaining to few-shot image generation.

Implementation of TheWebConf 2021 -- Few-shot Network Anomaly Detection via Cross-network Meta-learning

Matching Networks for one-shot learning in tensorflow (NIPS'16)

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

FSL-Mate: A collection of resources for few-shot learning (FSL).

Code for ACL'2021 paper WARP 🌀 Word-level Adversarial ReProgramming. Outperforming `GPT-3` on SuperGLUE Few-Shot text classification. https://aclanthology.org/2021.acl-long.381/

Tensorflow implementation for paper: Learning to Compare: Relation Network for Few-Shot Learning.

ICML'2022: Black-Box Tuning for Language-Model-as-a-Service

a deep recurrent model for exchangeable data

A non-official 100% PyTorch implementation of META-DATASET benchmark for few-shot classification

Enhancing the BERT training with Semi-supervised Generative Adversarial Networks

Code and data of ACL 2021 paper "Few-NERD: A Few-shot Named Entity Recognition Dataset"

ACL 2019 paper:Multi-Level Matching and Aggregation Network for Few-Shot Relation Classification

Laplacian Regularized Few Shot Learning

(ECCV 2020) PyTorch implementation of paper "Few-Shot Object Detection and Viewpoint Estimation for Objects in the Wild"

Code of Empirical Bayes Transductive Meta-Learning with Synthetic Gradients

One-Shot Recognition of Manufacturing Defects in Steel Surfaces

Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in full in this ICML 2021 paper: https://arxiv.org/abs/2102.08622.

PyTorch code for NeurIPSW 2020 paper (4th Workshop on Meta-Learning) "Few-Shot Unsupervised Continual Learning through Meta-Examples"

Source codes for "Improved Few-Shot Visual Classification" (CVPR 2020), "Enhancing Few-Shot Image Classification with Unlabelled Examples" (WACV 2022), and "Beyond Simple Meta-Learning: Multi-Purpose Models for Multi-Domain, Active and Continual Few-Shot Learning" (Neural Networks 2022 - in submission)

Dialogue Knowledge Transfer Networks (DiKTNet)

[CVPR 2021] Few-shot 3D Point Cloud Semantic Segmentation

Learning To Compare For Text , Few shot learning in text classification

awesome few shot / meta learning papers

Few-shot Keyword Spotting in Any Language and Multilingual Spoken Word Corpus

RoBERTa中文预训练模型: RoBERTa for Chinese

A PyTorch-based model pruning toolkit for pre-trained language models

The code of our paper "SIFRank: A New Baseline for Unsupervised Keyphrase Extraction Based on Pre-trained Language Model"

An Open-Source Framework for Prompt-Learning.

Must-read papers on prompt-based tuning for pre-trained language models.