magnitude

Vector embedding utility

A fast and efficient utility package for utilizing vector embeddings in machine learning models

A fast, efficient universal vector embedding utility package.

GitHub

2k stars
38 watching
120 forks
Language: Python
last commit: about 3 years ago
Linked from 1 awesome list

embeddingsfastfasttextgensimglovemachine-learningmachine-learning-librarymemory-efficientnatural-language-processingnlppythonvectorsword-embeddingsword2vec

Backlinks from these awesome lists:

Related projects:

RepositoryDescriptionStars
materialsintelligence/mat2vecUnsupervised word embeddings capture latent knowledge from materials science literature624
vzhong/embeddingsProvides fast and efficient word embeddings for natural language processing.223
rguthrie3/morphologicalpriorsforwordembeddingsA project implementing a method to incorporate morphological information into word embeddings using a neural network model52
nlprinceton/text_embeddingA utility class for generating and evaluating document representations using word embeddings.54
fursovia/geometric_embeddingAn implementation of a non-parameterized approach for building sentence representations19
gink03/alt-i2vAn implementation of a deep learning-based image representation learning approach using a modified fully connected layer and transfer learning from VGG1634
nlprinceton/alacarteTools and code for inducing custom semantic vector representations from text data104
jwieting/iclr2016Code for training universal paraphrastic sentence embeddings and models on semantic similarity tasks193
bigredt/vicoMulti-sense word embeddings learned from visual cooccurrences25
patterns-ai-core/milvusA Ruby wrapper around a vector search database API for efficient similarity searches in high-dimensional space25
hit-scir/elmoformanylangsProvides pre-trained ELMo representations for multiple languages to improve NLP tasks.1,462
harsh19/spineTransforms existing word embeddings into more interpretable ones by applying a novel extension of k-sparse autoencoder with stricter sparsity constraints52
zhezhaoa/ngram2vecA toolkit for learning high-quality word and text representations from ngram co-occurrence statistics848
malllabiisc/wordgcnA deep learning model that generates word embeddings by predicting words based on their dependency context291
florianmai/word2matA framework for learning sentence embeddings from matrices21