Pytorch implementation of a simple GRU word-level language model trained on Donald Trump's tweets.
-
Updated
Mar 12, 2018 - Python
Pytorch implementation of a simple GRU word-level language model trained on Donald Trump's tweets.
Creating a Neural Language Model using LSTMs and calculating perplexity score of the model.
Pytorch based Neural Network Language Modeling (NNLM) Toolkit for easier and faster NNLM research and development. Result of my Master's Thesis work.
N-gram and neural word-level language models
Language Modeling using Recurrent Neural Networks implemented over Tensorflow 2.0 (Keras) (GRU, LSTM)
Classification of case.law cases by landmark cases from www.law.cornell.edu
Implementation of a simple neural language model (multi-layer perceptron) from scratch for next word prediction
Generating High-Quality Query Suggestion Candidates for Task-Based Search - ECIR'18
Deep learning models in Python
Materials for the MSc Thesis "Interpreting Neural Language Models for Linguistic Complexity Assessment" and related works.
Improving Language Model Performance through Smart Vocabularies
Implementation of "A Neural Probabilistic Language Model" by Yoshua Bengio et al. - Tensorflow
Generating text sequences using attention-based Bi-LSTM
Advanced file format fuzzer based-on deep neural language models.
Add a description, image, and links to the neural-language-model topic page so that developers can more easily learn about it.
To associate your repository with the neural-language-model topic, visit your repo's landing page and select "manage topics."