next-word-prediction
There are 42 repositories under next-word-prediction topic.
microsoft/LMChallenge
A library & tools to evaluate predictive language models.
rajveermalviya/language-modeling
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
aalok-sathe/surprisal
A unified interface for computing surprisal (log probabilities) from language models! Supports neural, symbolic, and black-box API models.
brunocampos01/federated-learning-for-text-generation
Machine learning project using federated learning for text generation
doubtcrack/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.
RisticDjordje/personalized-autocomplete-next-word-prediction-task
A personalized autocomplete (next word prediction) project using three different architectures: stacked LSTMs, Seq2Seq with Attention and LSTMs and GPT-2, written from scratch.
cobanov/next-word-predict
Next word prediction using a pre-trained model.
apostolidoum/Next-Word-Prediction
A language modeling project for predicting the next word that a user will type
Adminixtrator/Next-Word-Prediction-using-Universal-Sentence-Encoder
Next Word Prediction using Google's Universal Sentence Encoder from Tensorflow hub. lol
sumeyye-agac/next-word-prediction-using-MLP-from-scratch
Implementation of a simple neural language model (multi-layer perceptron) from scratch for next word prediction
2003HARSH/Next-Word-Prediction-using-RNN-LSTM-GRU
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
alinamuliak/N-gramTextPrediction
Prediction of the following words using N-gram technique.
iboraham/next-word-prediction
Interactive web application for real-time next word prediction using n-gram analysis, built with FastAPI and Tailwind CSS.
Susheel-1999/LSTM-next_word_prediction_using_pytorch
Predict the next word using Long short-term memory
a-alhaouil/next_word_prediction
this a project for predicting the next word in a sequence using various models.
arusl/nwp-en-bsd
This repo contains a Jupyter notebook for training an English next word prediction model based on a conversational dataset.
Aya-Jafar/Heal-Tech.AI-remake
React Web app for AI medical services
hienhuynhtdn/GPT2andImplicitCausality
Evaluation of the ability of GPT-2 to learn human biases in implicit causality.
ramanakshay/nanogpt
nanoGPT model from scratch
Sheel-ui/next-word-backend
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.
KajaBraz/NextWordPredictor
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.
KushwahaDK/Neural-Language-Model
Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)
Saeed-Biabani/Next-Word-Prediction
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.
Sheel-ui/next-word-frontend
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.
sugarwaffles/CNN-RNN_Project
Fundamentals of CNN and RNN with keras & tensorflow libs
fmirzaie/Tweety
Generating quote-like text with Recurrent Neural Networks (RNNs)
jaiminjariwala/Next-Word-Predictor-LSTMs
Next Word Predictor using LSTMs and Tensorflow Framework
naruto-o/next_word_prediction
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.
prince2004patel/next_word_prediction
This project implements a Next Word Prediction model using LSTM with an Attention mechanism.
saadtariq-ds/Next-Word-Prediction
This project aims to develop a deep learning model for predicting the next word in a given sequence of words. The model is built using LSTM and GRU networks, which are well-suited for sequence prediction tasks
SayamAlt/Next-Word-Prediction-using-Bidirectional-LSTMs
Successfully developed a text generation model to predict the next word for a given sequence using LSTMs.
shubhamprajapati7748/next-word-predictor
WordPredictor is a deep learning project that leverages Long Short Term Memory (LSTM) networks to predict the next word in a given sequence of words. This project demonstrates how LSTM networks, which excel at handling sequential data, can be applied to natural language processing tasks like word prediction.
tejas-130704/LSTM_Projects
This project uses an LSTM-based model to predict the next word in a sentence. By training on a given text dataset, the model learns word sequences and suggests the most probable next word. It can be improved with larger datasets and fine-tuned hyperparameters for better accuracy.
UmairAli254/Predicting-next-word-like-LLMs-via-RNN
Predicting next word(s) like LLM(Large Language Model) via RNN (Recurrent Neural Network)
vn33/Next-word-Predictor-LSTM
Predict next word in sentences using LSTM. Trained on GitHub Copilot support data. Command-line & GUI versions available. Improve text prediction now!
Yashmenaria1/Next-Word-Prediction
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.