Local cross-platform machine translation GUI, based on CTranslate2

Overview

DesktopTranslator

Local cross-platform machine translation GUI, based on CTranslate2

DesktopTranslator

Download Windows Installer

You can either download a ready-made Windows executable installer for DesktopTranslator, or build an installer yourself.
DesktopTranslator

Translation Models

Currently, DesktopTranslator supports CTranslate2 models, and SentencePiece subwording models (you need both). If you have a model for OpenNMT-py, OpenNMT-tf, or FairSeq, you can convert it to a CTranslate2 format.

If you would like to try out the app and you do not have a model, you can download my French-to-English generic model here.

  1. Unzip the fren.zip archive of the French-to-English generic model you just downloaded. It has two folders, ct2_model for the CTranslate2 model and sp_model for the SentencePiece subwording models of French (source) and English (target).
  2. In DesktopTranslator, click the CTranslate2 Model button, and select the ct2_model folder.
  3. Click the SentencePiece Model button, navigate to the sp_model folder, and select fr.model.
  4. In the left input text-area, type some text in French or use the File menu > Open... to open a *.txt file.
  5. Click the Translate button.

Build Windows Installer

If you want to adjust the code and then build an installer yourself, you can follow these steps:

  1. Install PyInstaller:
pip3 install pyinstaller
  1. To use PyInstaller, specify the Python file name and the argument -w to hide the console window:
pyinstaller -y -w "translator.py"
  1. Try the *.exe file under "dist\translator" to make sure it works. It might complain about the Pmw library. The solution is either remove the Balloon lines, or add this file to the same folder as the translate.py and run the aforementioned PyInstaller command again.
  2. Compress the contents of the “dist” directory created by PyInstaller into a *.zip archive.
  3. Download and install NSIS.
  4. Launch NSIS, click Installer based on a .ZIP file, and then click Open to locate the *.zip archive you have just created.
  5. If you want to make the files installed (extracted) to the “Program Files” of the target user, in the Default Folder enter $PROGRAMFILES
  6. If you want to add a shortcut to the internal *.exe file on the Desktop after installation, you can add something like this to the file “Modern.nsh” located at: "C:\Program Files\NSIS\Contrib\zip2exe". Depending on your OS, the path could be at “Program Files (x86)”. Note that the exe path should be consistent with the path you selected under NSIS’s “Default Folder” drop-down menu, the folder name, and the exe file name.
Section "Desktop Shortcut" SectionX
    SetShellVarContext current
    CreateShortCut "$DESKTOP\DesktopTranslator.lnk" "$PROGRAMFILES\DesktopTranslator\translator.exe"
SectionEnd
  1. Finally, click the NSIS Generate button, which will create the *.exe installer that can be shipped to other Windows machines, without the need to install any extra requirements.
  2. After installation, if you applied step #8, you should find an icon on the Desktop. To uninstall, you can simple remove the app forlder from "Program Files". For more NSIS options, check this example.
You might also like...
Open Source Neural Machine Translation in PyTorch
Open Source Neural Machine Translation in PyTorch

OpenNMT-py: Open-Source Neural Machine Translation OpenNMT-py is the PyTorch version of the OpenNMT project, an open-source (MIT) neural machine trans

Yet Another Neural Machine Translation Toolkit

YANMTT YANMTT is short for Yet Another Neural Machine Translation Toolkit. For a backstory how I ended up creating this toolkit scroll to the bottom o

PyTorch Implementation of "Non-Autoregressive Neural Machine Translation"

Non-Autoregressive Transformer Code release for Non-Autoregressive Neural Machine Translation by Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K.

Free and Open Source Machine Translation API. 100% self-hosted, offline capable and easy to setup.
Free and Open Source Machine Translation API. 100% self-hosted, offline capable and easy to setup.

LibreTranslate Try it online! | API Docs | Community Forum Free and Open Source Machine Translation API, entirely self-hosted. Unlike other APIs, it d

Training open neural machine translation models

Train Opus-MT models This package includes scripts for training NMT models using MarianNMT and OPUS data for OPUS-MT. More details are given in the Ma

Learning to Rewrite for Non-Autoregressive Neural Machine Translation
Learning to Rewrite for Non-Autoregressive Neural Machine Translation

RewriteNAT This repo provides the code for reproducing our proposed RewriteNAT in EMNLP 2021 paper entitled "Learning to Rewrite for Non-Autoregressiv

Implementaion of our ACL 2022 paper Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation

Bridging the Data Gap between Training and Inference for Unsupervised Neural Machine Translation This is the implementaion of our paper: Bridging the

Releases(v0.2.1)
Owner
Yasmin Moslem
Machine Translation Researcher
Yasmin Moslem
Syntax-aware Multi-spans Generation for Reading Comprehension (TASLP 2022)

SyntaxGen Syntax-aware Multi-spans Generation for Reading Comprehension (TASLP 2022) In this repo, we upload all the scripts for this work. Due to siz

Zhuosheng Zhang 3 Jun 13, 2022
A Facebook Messenger Chatbot using NLP

A Facebook Messenger Chatbot using NLP This project is about creating a messenger chatbot using basic NLP techniques and models like Logistic Regressi

6 Nov 20, 2022
Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

Fairseq(-py) is a sequence modeling toolkit that allows researchers and developers to train custom models for translation, summarization, language mod

20.5k Jan 08, 2023
Training RNNs as Fast as CNNs

News SRU++, a new SRU variant, is released. [tech report] [blog] The experimental code and SRU++ implementation are available on the dev branch which

Tao Lei 14 Dec 12, 2022
Mastering Transformers, published by Packt

Mastering Transformers This is the code repository for Mastering Transformers, published by Packt. Build state-of-the-art models from scratch with adv

Packt 195 Jan 01, 2023
Coreference resolution for English, German and Polish, optimised for limited training data and easily extensible for further languages

Coreferee Author: Richard Paul Hudson, msg systems ag 1. Introduction 1.1 The basic idea 1.2 Getting started 1.2.1 English 1.2.2 German 1.2.3 Polish 1

msg systems ag 169 Dec 21, 2022
A raytrace framework using taichi language

ti-raytrace The code use Taichi programming language Current implement acceleration lvbh disney brdf How to run First config your anaconda workspace,

蕉太狼 73 Dec 11, 2022
Deep Learning for Natural Language Processing - Lectures 2021

This repository contains slides for the course "20-00-0947: Deep Learning for Natural Language Processing" (Technical University of Darmstadt, Summer term 2021).

0 Feb 21, 2022
Harvis is designed to automate your C2 Infrastructure.

Harvis Harvis is designed to automate your C2 Infrastructure, currently using Mythic C2. 📌 What is it? Harvis is a python tool to help you create mul

Thiago Mayllart 99 Oct 06, 2022
Framework for fine-tuning pretrained transformers for Named-Entity Recognition (NER) tasks

NERDA Not only is NERDA a mesmerizing muppet-like character. NERDA is also a python package, that offers a slick easy-to-use interface for fine-tuning

Ekstra Bladet 141 Dec 30, 2022
Torchrecipes provides a set of reproduci-able, re-usable, ready-to-run RECIPES for training different types of models, across multiple domains, on PyTorch Lightning.

Recipes are a standard, well supported set of blueprints for machine learning engineers to rapidly train models using the latest research techniques without significant engineering overhead.Specifica

Meta Research 193 Dec 28, 2022
My Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Tasks using Tensorflow

Easy Data Augmentation Implementation This repository contains my Implementation for the paper EDA: Easy Data Augmentation Techniques for Boosting Per

Aflah 9 Oct 31, 2022
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.

textgenrnn Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code, or quickly tr

Max Woolf 4.8k Dec 30, 2022
IMDB film review sentiment classification based on BERT's supervised learning model.

IMDB film review sentiment classification based on BERT's supervised learning model. On the other hand, the model can be extended to other natural language multi-classification tasks.

Paris 1 Apr 17, 2022
LewusBot - Twitch ChatBot built in python with twitchio library

LewusBot Twitch ChatBot built in python with twitchio library. Uses twitch/leagu

Lewus 25 Dec 04, 2022
Textpipe: clean and extract metadata from text

textpipe: clean and extract metadata from text textpipe is a Python package for converting raw text in to clean, readable text and extracting metadata

Textpipe 298 Nov 21, 2022
Almost State-of-the-art Text Generation library

Ps: we are adding transformer model soon Text Gen 🐐 Almost State-of-the-art Text Generation library Text gen is a python library that allow you build

Emeka boris ama 63 Jun 24, 2022
Transformers Wav2Vec2 + Parlance's CTCDecodeTransformers Wav2Vec2 + Parlance's CTCDecode

🤗 Transformers Wav2Vec2 + Parlance's CTCDecode Introduction This repo shows how 🤗 Transformers can be used in combination with Parlance's ctcdecode

Patrick von Platen 9 Jul 21, 2022
The code from the whylogs workshop in DataTalks.Club on 29 March 2022

whylogs Workshop The code from the whylogs workshop in DataTalks.Club on 29 March 2022 whylogs - The open source standard for data logging (Don't forg

DataTalksClub 12 Sep 05, 2022
Winner system (DAMO-NLP) of SemEval 2022 MultiCoNER shared task over 10 out of 13 tracks.

KB-NER: a Knowledge-based System for Multilingual Complex Named Entity Recognition The code is for the winner system (DAMO-NLP) of SemEval 2022 MultiC

116 Dec 27, 2022