PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for basic tasks such as the extraction of n-grams and frequency lists, and to build simple language model. There are also more complex data types and algorithms. Mor…

A lightweight implementation of Beam Search for sequence models in PyTorch.

Contextualised Embeddings and Language Modelling using BERT and Friends using R

Transformer Based SeqGAN for Language Generation

Pytorch implementation of MaskGAN

Code for my master thesis in Deep Learning: "Generating answers to medical questions using recurrent neural networks"

This repository contains code and data download instructions for the workshop paper "Improving Hierarchical Product Classification using Domain-specific Language Modelling" by Alexander Brinkmann and Christian Bizer.

Language Modelling, CMI vs Perplexity

Memory Based Word Predictor/Language Model http://ilk.uvt.nl/wopr/

PyTorch implementations of word embeddings and language modelling.

Code for paper: "Numeracy Enhances the Literacy of Language Models"

N-Gram language model that learns n-gram probabilities from a given corpus and generates new sentences from it based on the conditional probabilities from the generated words and phrases.

Spelling correction and grammar detection with statistical language models

Various Deep Learning concepts implemented using TensorFlow

BERT-based pre-trained non-autoregressive sequence-to-sequence model

Sequence CNN network inspired by the WaveNet architecture written in both Tensorflow and PyTorch.

In this project we will generate the sentences using ngrams

Implementation of Transformer, BERT and GPT models in both Tensorflow 2.0 and PyTorch.

A simple series of programs to train gated recurrent neural networks with PyTorch and generate text based on them.

State-of-the-Art Language Modelling in Python with PyTorch.