Code and models used in "MUSS Multilingual Unsupervised Sentence Simplification by Mining Paraphrases".

Related tags

Deep Learningmuss
Overview

Multilingual Unsupervised Sentence Simplification

Code and pretrained models to reproduce experiments in "MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases".

Prerequisites

Linux with python 3.6 or above.

Installing

git clone [email protected]:facebookresearch/muss.git
cd muss/
pip install -e .

How to use

Some scripts might still contain a few bugs, if you notice anything wrong, feel free to open an issue or submit a Pull Request.

Simplify sentences from a file using pretrained models

# English
python scripts/simplify.py scripts/examples.en --model-name muss_en_wikilarge_mined
# French
python scripts/simplify.py scripts/examples.fr --model-name muss_fr_mined
# French
python scripts/simplify.py scripts/examples.es --model-name muss_es_mined

Pretrained models should be downloaded automatically, but you can also find them here:
muss_en_wikilarge_mined
muss_en_mined
muss_fr_mined
muss_es_mined

Mine the data

python scripts/mine_sequences.py

Train the models

python scripts/train_model.py

Evaluate simplifications

Please head over to EASSE for Sentence Simplification evaluation.

License

The MUSS license is CC-BY-NC. See the LICENSE file for more details.

Authors

Citation

If you use MUSS in your research, please cite MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases

@article{martin2021muss,
  title={MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases},
  author={Martin, Louis and Fan, Angela and de la Clergerie, {\'E}ric and Bordes, Antoine and Sagot, Beno{\^\i}t},
  journal={arXiv preprint arXiv:2005.00352},
  year={2021}
}
Owner
Facebook Research
Facebook Research
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

Sayed Hashim 3 Nov 15, 2022
Anomaly detection analysis and labeling tool, specifically for multiple time series (one time series per category)

taganomaly Anomaly detection labeling tool, specifically for multiple time series (one time series per category). Taganomaly is a tool for creating la

Microsoft 272 Dec 17, 2022
Official code for "Decoupling Zero-Shot Semantic Segmentation"

Decoupling Zero-Shot Semantic Segmentation This is the official code for the arxiv. ZegFormer is the first framework that decouple the zero-shot seman

Jian Ding 108 Dec 30, 2022
DiffStride: Learning strides in convolutional neural networks

DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initiali

Google Research 113 Dec 13, 2022
Codebase for Diffusion Models Beat GANS on Image Synthesis.

Codebase for Diffusion Models Beat GANS on Image Synthesis.

Katherine Crowson 128 Dec 02, 2022
Pre-trained BERT Models for Ancient and Medieval Greek, and associated code for LaTeCH 2021 paper titled - "A Pilot Study for BERT Language Modelling and Morphological Analysis for Ancient and Medieval Greek"

Ancient Greek BERT The first and only available Ancient Greek sub-word BERT model! State-of-the-art post fine-tuning on Part-of-Speech Tagging and Mor

Pranaydeep Singh 22 Dec 08, 2022
Simple implementation of OpenAI CLIP model in PyTorch.

It was in January of 2021 that OpenAI announced two new models: DALL-E and CLIP, both multi-modality models connecting texts and images in some way. In this article we are going to implement CLIP mod

Moein Shariatnia 226 Jan 05, 2023
Codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks

DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n

11 Sep 10, 2022
Project page for our ICCV 2021 paper "The Way to my Heart is through Contrastive Learning"

The Way to my Heart is through Contrastive Learning: Remote Photoplethysmography from Unlabelled Video This is the official project page of our ICCV 2

36 Jan 06, 2023
Official code implementation for "Personalized Federated Learning using Hypernetworks"

Personalized Federated Learning using Hypernetworks This is an official implementation of Personalized Federated Learning using Hypernetworks paper. [

Aviv Shamsian 121 Dec 25, 2022
Easily pull telemetry data and create beautiful visualizations for analysis.

This repository is a work in progress. Anything and everything is subject to change. Porpo Table of Contents Porpo Table of Contents General Informati

Ryan Dawes 33 Nov 30, 2022
Official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks".

GN-Transformer AST This is the official repository for the paper "GN-Transformer: Fusing AST and Source Code information in Graph Networks". Data Prep

Cheng Jun-Yan 10 Nov 26, 2022
Implementation of QuickDraw - an online game developed by Google, combined with AirGesture - a simple gesture recognition application

QuickDraw - AirGesture Introduction Here is my python source code for QuickDraw - an online game developed by google, combined with AirGesture - a sim

Viet Nguyen 89 Dec 18, 2022
Fast and customizable reconnaissance workflow tool based on simple YAML based DSL.

Fast and customizable reconnaissance workflow tool based on simple YAML based DSL, with support of notifications and distributed workload of that work

Américo Júnior 3 Mar 11, 2022
Semantically Contrastive Learning for Low-light Image Enhancement

Semantically Contrastive Learning for Low-light Image Enhancement Here, we propose an effective semantically contrastive learning paradigm for Low-lig

48 Dec 16, 2022
PyTorch code for our paper "Gated Multiple Feedback Network for Image Super-Resolution" (BMVC2019)

Gated Multiple Feedback Network for Image Super-Resolution This repository contains the PyTorch implementation for the proposed GMFN [arXiv]. The fram

Qilei Li 66 Nov 03, 2022
HuSpaCy: industrial-strength Hungarian natural language processing

HuSpaCy: Industrial-strength Hungarian NLP HuSpaCy is a spaCy model and a library providing industrial-strength Hungarian language processing faciliti

HuSpaCy 120 Dec 14, 2022
[ICCV '21] In this repository you find the code to our paper Keypoint Communities

Keypoint Communities In this repository you will find the code to our ICCV '21 paper: Keypoint Communities Duncan Zauss, Sven Kreiss, Alexandre Alahi,

Duncan Zauss 262 Dec 13, 2022
Graph WaveNet apdapted for brain connectivity analysis.

Graph WaveNet for brain network analysis This is the implementation of the Graph WaveNet model used in our manuscript: S. Wein , A. Schüller, A. M. To

4 Dec 17, 2022
A series of convenience functions to make basic image processing operations such as translation, rotation, resizing, skeletonization, and displaying Matplotlib images easier with OpenCV and Python.

imutils A series of convenience functions to make basic image processing functions such as translation, rotation, resizing, skeletonization, and displ

Adrian Rosebrock 4.3k Jan 08, 2023