There are 2 repositories under next-word-prediction topic.
A library & tools to evaluate predictive language models.
This is machine learning model that is trained to predict next word in the sequence. Model is defined in keras and then converted to tensorflow-js model for the web, check the web implementation at
Machine learning project using federated learning for text generation
A personalized autocomplete (next word prediction) project using three different architectures: stacked LSTMs, Seq2Seq with Attention and LSTMs and GPT-2, written from scratch.
A language modeling project for predicting the next word that a user will type
Predict the future words efficiently with the "Next Word Prediction Using Markov Model" project. Built in Python and powered by the `msvcrt` module, this academic initiative explores the Markov chain model to anticipate the most likely next word based on a given sequence.
Next Word Prediction using Google's Universal Sentence Encoder from Tensorflow hub. lol
Implementation of a simple neural language model (multi-layer perceptron) from scratch for next word prediction
This repo contains a Jupyter notebook for training an English next word prediction model based on a conversational dataset.
Evaluation of the ability of GPT-2 to learn human biases in implicit causality.
Predict the next word using Long short-term memory
Prediction of the following words using N-gram technique.
A program which guesses next words based on the user's input. Suggestions are the words with the highest probability to follow what has been already written, calculated in the n_grams of different size.
Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)
Fundamentals of CNN and RNN with keras & tensorflow libs
This repository hosts a deep learning model for precise next-word prediction.
Interactive web application for real-time next word prediction using n-gram analysis, built with FastAPI and Tailwind CSS.
TensorFlow Next Word Prediction Model on Heroku
It is simple project created using flask to predict the next word the user will write like on google search engine with the help of LSTM model
build a neural network machine learning model that predicts the next word of a given text sequence. We also use this model, to generate text.
This project aims to predict the next words in a sentence using a language model trained on the Medium dataset, specifically focusing on generating likely sentences based on the initial words of a Medium post title entered in the search bar.
Next word prediction using TensorFlow and NLP improves writing by suggesting the next word in messages, emails, and essays. It uses deep learning to analyze text data, predicting the most likely word based on context. This enhances typing speed and accuracy, aiding in coherent and efficient communication.