A language modeling project for predicting the next word that a user will type

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.

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.

Fundamentals of CNN and RNN with keras & tensorflow libs

Implementation of a simple neural language model (multi-layer perceptron) from scratch for next word prediction

Predict next word in sentences using LSTM. Trained on GitHub Copilot support data. Command-line & GUI versions available. Improve text prediction now!

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

Text auto-completion system using the bert-base-uncased model by Hugging Face in the backend. Designed to enhance user experience across various applications, it anticipates and suggests word sequences as users type.

Next word prediction using a pre-trained model.

Text auto-completion system using the bert-base-uncased model by Hugging Face in the backend. Designed to enhance user experience across various applications, it anticipates and suggests word sequences as users type.

Next Word Predictor using LSTMs and Tensorflow Framework

Interactive web application for real-time next word prediction using n-gram analysis, built with FastAPI and Tailwind CSS.

This repository hosts a deep learning model for precise next-word prediction.

The Next Word Predictor using LSTM is a project that builds a text prediction model using Long Short-Term Memory (LSTM) neural networks. It predicts the most likely next word in a given sequence, useful for text composition and natural language processing tasks. The project allows customizable training and includes an interactive script for testing

Generating quote-like text with Recurrent Neural Networks (RNNs)

Next word prediction. aims to generate coherent and contextually relevant suggestions for the next word based on the patterns and relationships learned from training data.

A personalized autocomplete (next word prediction) project using three different architectures: stacked LSTMs, Seq2Seq with Attention and LSTMs and GPT-2, written from scratch.

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.

Evaluation of the ability of GPT-2 to learn human biases in implicit causality.