ELMo Performance Experiment using Pytorch

Exploring the simple sentence similarity measurements using word embeddings

Tencent Pre-training framework in PyTorch & Pre-trained Model Zoo

NLP research：基于tensorflow的nlp深度学习项目，支持文本分类/句子匹配/序列标注/文本生成 四大任务

Home Assistant integration that provides a full-fledged Alarm Panel to control your Elmo/IESS alarm systems.

Getting Word Embeddings using my ELMO architecture

Open Source Pre-training Model Framework in PyTorch & Pre-trained Model Zoo

NLPToolkit is a toolkit for NLP(Natural Language Processing) and LLM(Large Language Models) using Pytorch.

A simple and easy to understand NLP teaching

Simple implementations of NLP models. Tutorials are written in Chinese on my website https://mofanpy.com

Simple library to work with pre-trained ELMo models in TensorFlow

Re-implementation of ELMo on Keras

Supervised end-to-end neural architecture that learns how to disambiguate words inside a text.

Source code for ACL 2020 paper "Learning Spoken Language Representations with Neural Lattice Language Modeling"

Large Scale benchmarking of state of the art text vectorizers

Deep learning (DL) approaches use various processing layers to learn hierarchical representations of data. Recently, many methods and designs of natural language processing (NLP) models have shown significant development, especially in text mining and analysis. For learning vector-space representations of text, there are famous models like Word2…

Official implementation of: Tha3aroon at NSURL-2019 Task 8: Semantic Question Similarity in Arabic

Code for the ACL 2019 paper "Observing Dialogue in Therapy: Categorizing and Forecasting Behavioral Codes"

This project aims to implement the charCNN word embedding method that is leveraged in ELMo and characterBERT.

This project is to match the offset of the pre-trained word embeddings such as BERT, ELMo, and Glove to the preprocessed token offset and its dependencies in various ways of preprocessing method such as Stanza and Spacy. Therefore, the result of this can be applied to the graph neural networks without concern of its mismatch of the preprocessed …