LexVec

LexVec

Alexandre Salle
+
+

Related Products

  • Gemini Enterprise Agent Platform
    1,161 Ratings
    Visit Website
  • Expedience Software
    34 Ratings
    Visit Website
  • Flashcloud
    51 Ratings
    Visit Website
  • Bluehost
    31,868 Ratings
    Visit Website
  • FinOpsly
    3 Ratings
    Visit Website
  • wp2print
    7,748 Ratings
    Visit Website
  • Mentornity
    99 Ratings
    Visit Website
  • Adobe Acrobat
    8,459 Ratings
    Visit Website
  • TinyPNG
    72 Ratings
    Visit Website
  • InMotion Hosting
    3,211 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 Supported
Mac Supported
Linux Supported
Cloud Supported
On-Premises Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

Platforms Supported

Windows Not Supported
Mac Supported
Linux Supported
Cloud Not Supported
On-Premises Not Supported
iPhone Not Supported
iPad Not Supported
Android Not Supported
Chromebook Not Supported

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 Not Supported
24/7 Live Support Not Supported
Online Supported

Support

Phone Support Not Supported
24/7 Live Support Not Supported
Online Supported

API

Offers API Not Supported

API

Offers API Supported

Screenshots and Videos

Screenshots and Videos

Pricing

Free
Free Version Supported
Free Trial Not Supported

Pricing

Free
Free Version Supported
Free Trial Not Supported

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 Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

Training

Documentation Supported
Webinars Not Supported
Live Online Not Supported
In Person Not Supported

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

Embedding Models Supported

Categories

Embedding Models Supported

Integrations

Gensim Not Supported
JavaScript Not Supported
Python Not Supported
WebAssembly Not Supported

Integrations

Gensim Supported
JavaScript Supported
Python Supported
WebAssembly Supported
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