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Easy-Translate is a script for translating large text files with a SINGLE COMMAND. Easy-Translate is designed to be as easy as possible for beginners and as seamlesscustomizable and as possible for advanced users.
A performant high-throughput CPU-based API for Meta's No Language Left Behind (NLLB) using CTranslate2, hosted on Hugging Face Spaces.
This project use the Meta NLLB-200 translation model through the Hugging Face transformers library.
nllb-200 distilled 350M for English to Korean translation
Example application for the task of fine-tuning pretrained machine translation models on highly domain-specific, self-extracted translated sentences
Gradio AI Transformer Translator used meta/nllb-200-distilled-600M
Translator demo app built with Transformers.js + Tamagui + Next.js
A implementation of Meta's NLLB translator, modified to run on Apple Silicon Macs (M1–M4) using GPU acceleration via PyTorch MPS. No CUDA or quantization required. Fast, offline language translation with Gradio UI. This is part of our AI Ethics coursework and paper.
nlingua2 – Command-line tool for transcribing and translating .srt subtitles using offline AI models (OpenAI Whisper + Meta NLLB).
Repository of our paper Nesciun Lengaz Lascià Endò: Machine Translation for Fassa Ladin.
THOTH Language Translator is a powerful, privacy-first, state-of-the art translation tool that runs offline. It uses the NLLB-200 engine to translate over 200 languages, with option to switch to an alternate translation engine, Argos.
A telegram bot for text, voice, and image translation using NLLB and dl-translate
This project is a Flask-based web application that translates text from one language to another using a pre-trained machine translation model (NLLB-200). The application provides a user-friendly interface for selecting languages and entering text, and it returns the translated output along with the computation time.
This repository contains Python implementations for processing multilingual text data, focusing on language classification and translation tasks. The project addresses two distinct tasks: language classification and English translation, each involving different complexities in the processing of text data.
An AI-powered web app that automatically translates videos into 20+ languages. Built with Flask, it uses OpenAI Whisper for speech transcription, Facebook NLLB-200 for precise translation, Google Gemini for intelligent video summarization, and FFmpeg to generate and embed translated subtitles directly into your videos.
A fully local implementation of NLLB 200, built while following the documentation of transformers.js
Translation API using Meta's NLLB-200 model with 200+ languages
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