Four word embedding models implemented in Python. Supporting arbitrary context features

One-Stop Solution to encode sentence to fixed length vectors from various embedding techniques

Word Embedding + LSTM + FC

Deep contextualized word representations for Chinese

Code & data accompanying the KDD 2017 paper "KATE: K-Competitive Autoencoder for Text"

A lightweight implementation of Walklets from "Don't Walk Skip! Online Learning of Multi-scale Network Embeddings" (ASONAM 2017).

Dead simple games made with word vectors.

Expose a Top2Vec model with a REST API.

Library for Korean morpheme and word vector representation

MirasText

Topical Word Embeddings

Superfast CUDA implementation of Word2Vec and Latent Dirichlet Allocation (LDA)

A sparsity aware implementation of "Alternating Direction Method of Multipliers for Non-Negative Matrix Factorization with the Beta-Divergence" (ICASSP 2014).

Code for the paper "A Multi-lingual Multi-task Architecture for Low-resource Sequence Labeling" (ACL2018)

Geometry-aware Multilingual Embeddings

Python project to create a classifier to guess if a Twitter account is a man, a woman or a bot.

Learning Ontologies Via Embeddings

Data and code for "Understanding Linearity of Cross-Lingual Word Embedding Mappings" (TMLR 2022)

Project CRANE (Crisis Racism and Narrative Evaluation) aims to support researchers and anti-racist organisations that wish to use state-of-the-art text analysis algorithms to study how specific events impact online hate speech and racist narratives. CRANE Toolbox is a Python package: once installed, the tools in CRANE are available as functions …

Retraining embedding models to incorporate emotional constraints.