A simple library that implements search algorithms for sequence models written in PyTorch.
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Updated
Apr 23, 2024 - Python
A simple library that implements search algorithms for sequence models written in PyTorch.
BERT-based pre-trained non-autoregressive sequence-to-sequence model
Memory Based Word Predictor/Language Model http://ilk.uvt.nl/wopr/
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…
Implementation of Transformer, BERT and GPT models in both Tensorflow 2.0 and PyTorch.
Decoder model for language modelling
Code for paper: "Numeracy Enhances the Literacy of Language Models"
Various Deep Learning concepts implemented using TensorFlow
Sequence CNN network inspired by the WaveNet architecture written in both Tensorflow and PyTorch.
Natural Language Processing topics and projects.
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.
PyTorch implementations of word embeddings and language modelling.
State-of-the-Art Language Modelling in Python with PyTorch.
A simple series of programs to train gated recurrent neural networks with PyTorch and generate text based on them.
Reproduction of CIFAR-10/CIFAR-100 and Penn Treebank experiments to test claims in "LookaheadOptimizer: k steps forward, 1 step back" https://arxiv.org/abs/1907.08610
Reproduction of CIFAR-10/CIFAR-100 and Penn Treebank experiments to test claims in "LookaheadOptimizer: k steps forward, 1 step back" https://arxiv.org/abs/1907.08610
Contextualised Embeddings and Language Modelling using BERT and Friends using R
Pytorch implementation of MaskGAN
Introduce basic nlp tasks and methods with examples
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