Fast_Sentence_Embeddings

iarroyof/sentence_embedding9

Sentence Embedder

A method to convert word embeddings into sentence representations by applying entropy weights calculated from TFIDF transform.

princetonml/sif1.1K

Sentence Embedder

A Python implementation of a sentence embedding algorithm using the Smooth Inverse Frequency weighting scheme

binwang28/sbert-wk-sentence-embedding178

Sentence embedder

A method to generate sentence embeddings from pre-trained language models

fursovia/geometric_embedding19

Sentence embedder

An implementation of a non-parameterized approach for building sentence representations

wangyuxinwhy/uniem840

NLP embedders

Develops unified sentence embedding models for NLP tasks

kostyaev/sentence2vec22

Sentence embedder

This is a tool for creating deep sentence embeddings using Sequence-to-Sequence learning.

lajanugen/s2v205

Sentence Embedder

An implementation of a neural network model for learning efficient sentence representations from text data.

jwieting/iclr2016193

Embedding models

Code for training universal paraphrastic sentence embeddings and models on semantic similarity tasks

xiaoqijiao/coling20182

Sentence Embedder

Provides training and testing code for a CNN-based sentence embedding model

epfml/sent2vec1.2K

Sentence embedder

An unsupervised technique to generate numerical representations of sentences and words for use in machine learning tasks

vzhong/embeddings223

Embeddings

Provides fast and efficient word embeddings for natural language processing.

botcenter/spanishwordembeddings9

Word Embeddings

This project generates Spanish word embeddings using fastText on large corpora.

jwieting/acl201733

Sentence embedding models

A codebase for training and using models of sentence embeddings.

losyer/compact_reconstruction9

Word embedding reconstructor

This project enables efficient reconstruction of word embeddings by leveraging subword representations.

seomoz/word2gauss190

Word embeddings library

This implementation provides a way to represent words as multivariate Gaussian distributions, allowing scalable word embeddings.