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

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

Machine learning project using federated learning for text generation

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.

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

Next word prediction using a pre-trained model.

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

Predict the next word using Long short-term memory

Prediction of the following words using N-gram technique.

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.

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

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.

Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)

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

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.