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dav/word2vec

This tool provides an efficient implementation of the continuous bag-of-words and skip-gram architectures for computing vector representations of words. These representations can be subsequently used in many natural language processing applications and for further research. observed · 2026-08-28

github.com/dav/word2vec · C · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 4764
  • days_rel: n/a
  • days_push: 1941
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1741 stars · 626 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

The original Google word2vec tool, hosted on GitHub with community patches for Mac OS X compilation and memory fixes. It efficiently trains word vector representations using CBOW and skip-gram architectures from a text corpus.

Use cases

  • train word embeddings from a text corpus
  • compute vector representations of words with skip-gram
  • compute word vectors with continuous bag-of-words
  • explore word similarity interactively
  • research natural language processing applications

When to choose

  • you need the classic, fast C implementation of word2vec
  • you want to train word embeddings on your own corpus
  • you need a lightweight command-line tool without Python dependencies

When to avoid

  • you need modern contextual embeddings like BERT or transformer models
  • you want an actively maintained project with recent fixes
  • you need deep integration with a Python ML pipeline

Facets

library · maturity maintenance

machine-learning nlp cli machine-learning cli word-embeddings word2vec cbow skip-gram c natural-language-processing linux macos

1 source

Member repositories

RepositoryRoleHealth v2
dav/word2vecmain32

For agents

markdown · JSON · MCP: product_card(name="dav/word2vec")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem