this a project for predicting the next word in a sequence using various models.

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 using a pre-trained model.

A unified interface for computing surprisal (log probabilities) from language models! Supports neural, symbolic, and black-box API models.

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.

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.

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

Machine learning project using federated learning for text generation

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.

Fundamentals of CNN and RNN with keras & tensorflow libs

Next Word Predictor using LSTMs and Tensorflow Framework

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.

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

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

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

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.

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