LexVec

LexVec

Alexandre Salle
+
+

Related Products

  • Gemini Enterprise Agent Platform
    984 Ratings
    Visit Website
  • Expedience Software
    34 Ratings
    Visit Website
  • Flashcloud
    15 Ratings
    Visit Website
  • Bluehost
    30,311 Ratings
    Visit Website
  • PDFCreator
    557 Ratings
    Visit Website
  • wp2print
    7,598 Ratings
    Visit Website
  • Hostinger
    70,808 Ratings
    Visit Website
  • InMotion Hosting
    2,952 Ratings
    Visit Website
  • TinyPNG
    60 Ratings
    Visit Website
  • one.com
    32 Ratings
    Visit Website

About

LexVec is a word embedding model that achieves state-of-the-art results in multiple natural language processing tasks by factorizing the Positive Pointwise Mutual Information (PPMI) matrix using stochastic gradient descent. This approach assigns heavier penalties for errors on frequent co-occurrences while accounting for negative co-occurrences. Pre-trained vectors are available, including a common crawl dataset with 58 billion tokens and 2 million words in 300 dimensions, and an English Wikipedia 2015 + NewsCrawl dataset with 7 billion tokens and 368,999 words in 300 dimensions. Evaluations demonstrate that LexVec matches or outperforms other models like word2vec in terms of word similarity and analogy tasks. The implementation is open source under the MIT License and is available on GitHub.

About

fastText is an open source, free, and lightweight library developed by Facebook's AI Research (FAIR) lab for efficient learning of word representations and text classification. It supports both unsupervised learning of word vectors and supervised learning for text classification tasks. A key feature of fastText is its ability to capture subword information by representing words as bags of character n-grams, which enhances the handling of morphologically rich languages and out-of-vocabulary words. The library is optimized for performance and capable of training on large datasets quickly, and the resulting models can be reduced in size for deployment on mobile devices. Pre-trained word vectors are available for 157 languages, trained on Common Crawl and Wikipedia data, and can be downloaded for immediate use. fastText also offers aligned word vectors for 44 languages, facilitating cross-lingual natural language processing tasks.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Computational linguists and NLP researchers searching for a tool to improve their semantic analysis and language modeling

Audience

Language processing practitioners and researchers requiring a tool for learning word embeddings and building text classifiers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alexandre Salle
Brazil
github.com/alexandres/lexvec

Company Information

fastText
fasttext.cc/

Alternatives

GloVe

GloVe

Stanford NLP

Alternatives

Gensim

Gensim

Radim Řehůřek
GloVe

GloVe

Stanford NLP
word2vec

word2vec

Google
word2vec

word2vec

Google
LexVec

LexVec

Alexandre Salle

Categories

Categories

Integrations

Gensim
JavaScript
Python
WebAssembly

Integrations

Gensim
JavaScript
Python
WebAssembly
Claim LexVec and update features and information
Claim LexVec and update features and information
Claim fastText and update features and information
Claim fastText and update features and information