lstm based language modelling (next-word prediction)
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Updated
Jun 8, 2024 - Jupyter Notebook
lstm based language modelling (next-word prediction)
applying different RNN architecture to build character prediction model and a word based prediction model these model are trained on data of specific topics from wikipedia
Next-token prediction in JavaScript — build fast language and diffusion models.
Fork of Presage (http://presage.sourceforge.net/)
This project uses LSTM, a type of neural network, for next word prediction. You input a seed text and specify the desired length. The LSTM model then generates the next word based on learned patterns from training data. It's a user-friendly tool for exploring how well the model can predict and generate coherent text continuations.
Program developed in C++ that will recommend new word to user based on frequency of his previously entered words.
Implemented BiDirectional Long Short- Term Memory (BiLSTM) to build a Future Word Prediction model. The project involved training these models using large datasets of textual data and tuning hyperparameters to optimize the accuracy of the model.
feedforward neural network for next word prediction
Different approaches for context word prediction. [IN PROGRESS]...
Application for character prediction using machine learning. The application is implemented using LSTM neural networks.
A learning JavaScript dictionary-based word prediction / autocomplete / suggestion library.
Draw UI for colab, useful to take hand writings from mouse in colab itself
A transformer-based language model trained on politics-related Twitter data. This repo is the official resource of the paper "PoliBERTweet: A Pre-trained Language Model for Analyzing Political Content on Twitter", LREC 2022
English Word Suggestion Based on POS-Ngram
Analyze your WhatsApp chats and get word suggestions based on your chat history while writing!
Presage based input predictor for the Sailfish OS
N-gram ile Sonraki Kelime Tahmini
This repository contains various small Natural Language Processing based projects including text summarization using Spacy and N-grams, along with word predictions.
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