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
Implementation of Token Shift GPT - An autoregressive model that solely relies on shifting the sequence space for mixing

Token Shift GPT Implementation of Token Shift GPT - An autoregressive model that relies solely on shifting along the sequence dimension and feedforwar

Phil Wang 32 Oct 14, 2022
基于GRU网络的句子判断程序/A program based on GRU network for judging sentences

SentencesJudger SentencesJudger 是一个基于GRU神经网络的句子判断程序,基本的功能是判断文章中的某一句话是否为一个优美的句子。 English 如何使用SentencesJudger 确认Python运行环境 安装pyTorch与LTP python3 -m pip

8 Mar 24, 2022
Train 🤗transformers with DeepSpeed: ZeRO-2, ZeRO-3

Fork from https://github.com/huggingface/transformers/tree/86d5fb0b360e68de46d40265e7c707fe68c8015b/examples/pytorch/language-modeling at 2021.05.17.

Junbum Lee 12 Oct 26, 2022
Extracting Summary Knowledge Graphs from Long Documents

GraphSum This repo contains the data and code for the G2G model in the paper: Extracting Summary Knowledge Graphs from Long Documents. The other basel

Zeqiu (Ellen) Wu 10 Oct 21, 2022
hashily is a Python module that provides a variety of text decoding and encoding operations.

hashily is a python module that performs a variety of text decoding and encoding functions. It also various functions for encrypting and decrypting text using various ciphers.

DevMysT 5 Jul 17, 2022
Sinkhorn Transformer - Practical implementation of Sparse Sinkhorn Attention

Sinkhorn Transformer This is a reproduction of the work outlined in Sparse Sinkhorn Attention, with additional enhancements. It includes a parameteriz

Phil Wang 217 Nov 25, 2022
Guide to using pre-trained large language models of source code

Large Models of Source Code I occasionally train and publicly release large neural language models on programs, including PolyCoder. Here, I describe

Vincent Hellendoorn 947 Dec 28, 2022
BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

BMInf (Big Model Inference) is a low-resource inference package for large-scale pretrained language models (PLMs).

OpenBMB 377 Jan 02, 2023
A Fast Command Analyser based on Dict and Pydantic

Alconna Alconna 隶属于ArcletProject, 在Cesloi内有内置 Alconna 是 Cesloi-CommandAnalysis 的高级版,支持解析消息链 一般情况下请当作简易的消息链解析器/命令解析器 文档 暂时的文档 Example from arclet.alcon

19 Jan 03, 2023
Final Project Bootcamp Zero

The Quest (Pygame) Descripción Este es el repositorio de código The-Quest para el proyecto final Bootcamp Zero de KeepCoding. El juego consiste en la

Seven-z01 1 Mar 02, 2022
A cross platform OCR Library based on PaddleOCR & OnnxRuntime

A cross platform OCR Library based on PaddleOCR & OnnxRuntime

RapidOCR Team 767 Jan 09, 2023
An easy to use Natural Language Processing library and framework for predicting, training, fine-tuning, and serving up state-of-the-art NLP models.

Welcome to AdaptNLP A high level framework and library for running, training, and deploying state-of-the-art Natural Language Processing (NLP) models

Novetta 407 Jan 03, 2023
Rank-One Model Editing for Locating and Editing Factual Knowledge in GPT

Rank-One Model Editing (ROME) This repository provides an implementation of Rank-One Model Editing (ROME) on auto-regressive transformers (GPU-only).

Kevin Meng 130 Dec 21, 2022
Write Alphabet, Words and Sentences with your eyes.

The-Next-Gen-AI-Eye-Writer The Eye tracking Technique has become one of the most popular techniques within the human and computer interaction era, thi

Rohan Kasabe 2 Apr 05, 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
CMeEE 数据集医学实体抽取

医学实体抽取_GlobalPointer_torch 介绍 思想来自于苏神 GlobalPointer,原始版本是基于keras实现的,模型结构实现参考现有 pytorch 复现代码【感谢!】,基于torch百分百复现苏神原始效果。 数据集 中文医学命名实体数据集 点这里申请,很简单,共包含九类医学

85 Dec 28, 2022
SentimentArcs: a large ensemble of dozens of sentiment analysis models to analyze emotion in text over time

SentimentArcs - Emotion in Text An end-to-end pipeline based on Jupyter notebooks to detect, extract, process and anlayze emotion over time in text. E

jon_chun 14 Dec 19, 2022
Fake news detector filters - Smart filter project allow to classify the quality of information and web pages

fake-news-detector-1.0 Lists, lists and more lists... Spam filter list, quality keyword list, stoplist list, top-domains urls list, news agencies webs

Memo Sim 1 Jan 04, 2022
SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning

SASE : Self-Adaptive noise distribution network for Speech Enhancement with heterogeneous data of Cross-Silo Federated learning We propose a SASE mode

Tower 1 Nov 20, 2021
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

English | 简体中文 | 繁體中文 | 한국어 State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow 🤗 Transformers provides thousands of pretrained models

Hugging Face 77.1k Dec 31, 2022