The model is designed to train a single and large neural network in order to predict correct translation by reading the given sentence.

Related tags

Text Data & NLP machine-learning natural-language-processing django neural-machine-translation chat-application
Overview

Neural Machine Translation communication system

The model is basically direct to convert one source language to another targeted language using encoder and decoder architecture. The model encodes the message sent by the sender to a vector of fixed length and decoder generates the translated message which is received by the receiver in their communication system(chat application) automatically.

Project status

  • Ongoing
  • Backend improvements yet to be done

Table Of Contents

Prerequisites

  • Install python packages such as numpy pandas Tensorflow Django matplotlib

Contribute

  • Fork the repository
  • Commit your changes
  • push to the branch & open a pull request

About

The model is trained using the spanish-english dataset with 100 epochs. The dataset contains about 110k rows and took about 4 hours to train using Nvidia GTX 1650 graphics card.

Evaluation

Epoch 100 Batch 600 Loss 0.24747854098677635
Epoch 100 Loss 0.0356
Time taken for 1 epoch 174.43703937530518 sec

Clone the project

git clone [email protected]:Nix-code/Nix-code-Neural-Machine-Translation-communication-system-.git

Run Django web application in local host

python3 manage.py runserver

Licence

MIT

You might also like...
Easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.
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 4.3k Feb 18, 2021
Utilize Korean BERT model in sentence-transformers library

ko-sentence-transformers 이 프로젝트는 KoBERT 모델을 sentence-transformers 에서 보다 쉽게 사용하기 위해 만들어졌습니다. Ko-Sentence-BERT-SKTBERT 프로젝트에서는 KoBERT 모델을 sentence-trans

Junghyun 40 Dec 20, 2022
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
In this repository, I have developed an end to end Automatic speech recognition project. I have developed the neural network model for automatic speech recognition with PyTorch and used MLflow to manage the ML lifecycle, including experimentation, reproducibility, deployment, and a central model registry.

End to End Automatic Speech Recognition In this repository, I have developed an end to end Automatic speech recognition project. I have developed the

Victor Basu 22 Nov 13, 2022
A Chinese to English Neural Model Translation Project

ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C

Zhenbang Feng 29 Nov 26, 2022
Code for paper "Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features"

Role-oriented Network Embedding Based on Adversarial Learning between Higher-order and Local Features Train python main.py --dataset brazil-flights C

wang zhang 0 Jun 28, 2022
Easy to start. Use deep nerual network to predict the sentiment of movie review.

Easy to start. Use deep nerual network to predict the sentiment of movie review. Various methods, word2vec, tf-idf and df to generate text vectors. Various models including lstm and cov1d. Achieve f1 score 92.

null 1 Nov 19, 2021
Learn meanings behind words is a key element in NLP. This project concentrates on the disambiguation of preposition senses. Therefore, we train a bert-transformer model and surpass the state-of-the-art.

New State-of-the-Art in Preposition Sense Disambiguation Supervisor: Prof. Dr. Alexander Mehler Alexander Henlein Institutions: Goethe University TTLa

Dirk Neuhäuser 4 Apr 6, 2022
This is my reading list for my PhD in AI, NLP, Deep Learning and more.

This is my reading list for my PhD in AI, NLP, Deep Learning and more.

Zhong Peixiang 156 Dec 21, 2022
Train GPT-3 model on V100(16GB Mem) Using improved Transformer.
Train GPT-3 model on V100(16GB Mem) Using improved Transformer.

GPT-X using transformer pytorch

Seonghwan Kim 24 Sep 11, 2022
Owner
Nishant Banjade
I am an admin and the community contributor at Ask Buddie. I am focusing more on NLP and I like solving Data structures and Algorithm.
Nishant Banjade
GitHub
Using Bert as the backbone model for lime, designed for NLP task explanation (sentence pair text classification task)

Lime Comparing deep contextualized model for sentences highlighting task. In addition, take the classic explanation model "LIME" with bert-base model

JHJu 2 Jan 18, 2022
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.

pySBD: Python Sentence Boundary Disambiguation (SBD) pySBD - python Sentence Boundary Disambiguation (SBD) - is a rule-based sentence boundary detecti

Nipun Sadvilkar 549 Jan 6, 2023
🐍💯pySBD (Python Sentence Boundary Disambiguation) is a rule-based sentence boundary detection that works out-of-the-box.

pySBD: Python Sentence Boundary Disambiguation (SBD) pySBD - python Sentence Boundary Disambiguation (SBD) - is a rule-based sentence boundary detecti

Nipun Sadvilkar 277 Feb 18, 2021
An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hundreds of billions of parameters or larger.

GPT-NeoX An implementation of model parallel GPT-3-like models on GPUs, based on the DeepSpeed library. Designed to be able to train models in the hun

EleutherAI 3.1k Jan 8, 2023
Estimation of the CEFR complexity score of a given word, sentence or text.

NLP-Swedish … allows to estimate CEFR (Common European Framework of References) complexity score of a given word, sentence or text. CEFR scores come f

null 3 Apr 30, 2022
Question answering app is used to answer for a user given question from user given text.

Question answering app is used to answer for a user given question from user given text.It is created using HuggingFace's transformer pipeline and streamlit python packages.

Siva Prakash 3 Apr 5, 2022
Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning

GenSen Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning Sandeep Subramanian, Adam Trischler, Yoshua B

Maluuba Inc. 309 Oct 19, 2022
Neural-Machine-Translation - Implementation of revolutionary machine translation models

Neural Machine Translation Framework: PyTorch Repository contaning my implementa

Utkarsh Jain 1 Feb 17, 2022
Python bot created with Selenium that can guess the daily Wordle word correct 96.8% of the time.

Wordle_Bot Python bot created with Selenium that can guess the daily Wordle word correct 96.8% of the time. It will log onto the wordle website and en

Lucas Polidori 15 Dec 11, 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