explosion/sense2vec
🦆 Contextually-keyed word vectors
This tool helps you understand the meaning of words and multi-word phrases by considering their context. You input text, and it outputs numerical representations (vectors) and similar terms, allowing you to find connections between concepts. It's used by anyone working with text data, such as researchers, analysts, or content strategists, who need to identify related ideas or categorize information.
1,672 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to find semantically similar words or phrases in your text data, especially when their meaning depends heavily on the surrounding words or their part of speech.
Not ideal if you're only interested in simple keyword matching or exact phrase searches, as this tool focuses on the nuanced meaning of terms.
Stars
1,672
Forks
239
Language
Python
License
MIT
Category
Last pushed
Apr 23, 2025
Commits (30d)
0
Dependencies
6
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/explosion/sense2vec"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
shibing624/similarities
Similarities: a toolkit for similarity calculation and semantic search....
chakki-works/chakin
Simple downloader for pre-trained word vectors
sebischair/Lbl2Vec
Lbl2Vec learns jointly embedded label, document and word vectors to retrieve documents with...
pdrm83/sent2vec
How to encode sentences in a high-dimensional vector space, a.k.a., sentence embedding.
maxoodf/word2vec
word2vec++ is a Distributed Representations of Words (word2vec) library and tools...