pip3 install -e .
python3 training/unsupervised_tuning.py
python3 training/supervised_tuning.py
python3 training/multilingual_tuning.py
The multilingual NLI corpus can be downloaded from here (https://drive.google.com/file/d/19O2NArJz_RlVNNGRbBnnWxNMW-7HaFZ8/view?usp=sharing)
Codes are adapted from the repos of the EMNLP19 paper Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks
UniMoCo: Unsupervised, Semi-Supervised and Full-Supervised Visual Representation Learning This is the official PyTorch implementation for UniMoCo pape
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SimCLS Code for our paper: "SimCLS: A Simple Framework for Contrastive Learning of Abstractive Summarization", ACL 2021 1. How to Install Requirements
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CLNER The code is for our ACL-IJCNLP 2021 paper: Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning CLNER is a
Span-ASTE-Pytorch This repository is a pytorch version that implements Ali's ACL 2021 research paper Learning Span-Level Interactions for Aspect Senti
By the way, i'm confused why you use batch normalization rather than layer normalization in the MLP module, which is unusual in NLP. Can you give some explanation or insight? Thanks
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REval Table of Contents Introduction Overview Requirements Installation Probing Usage Citation License ?? Introduction REval is a simple framework for
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Propagate Yourself: Exploring Pixel-Level Consistency for Unsupervised Visual Representation Learning By Zhenda Xie*, Yutong Lin*, Zheng Zhang, Yue Ca
DASR Pytorch implementation of "Unsupervised Degradation Representation Learning for Blind Super-Resolution", CVPR 2021 [arXiv] Overview Requirements
JigsawClustering Jigsaw Clustering for Unsupervised Visual Representation Learning Pengguang Chen, Shu Liu, Jiaya Jia Introduction This project provid
Unsupervised Object-Level Representation Learning from Scene Images This repository contains the official PyTorch implementation of the ORL algorithm
Viewmaker Networks: Learning Views for Unsupervised Representation Learning Alex Tamkin, Mike Wu, and Noah Goodman Paper link: https://arxiv.org/abs/2
CRLT: A Unified Contrastive Learning Toolkit for Unsupervised Text Representation Learning This repository contains the code and relevant instructions
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![[AAAI2021] The source code for our paper 《Enhancing Unsupervised Video Representation Learning by Decoupling the Scene and the Motion》.](https://github.com/FingerRec/DSM-decoupling-scene-motion/raw/main/figures/ppl.png)
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