IntuitionEngineeringTeam/chars2vec
Character-based word embeddings model based on RNN for handling real world texts
This helps developers working with natural language by converting words into numerical vectors, even if those words contain typos, slang, or abbreviations. You provide a list of words, and it outputs numerical representations that capture how similar words are based on their characters. It's ideal for developers building systems that need to understand text data with real-world imperfections.
174 stars. No commits in the last 6 months. Available on PyPI.
Use this if you need to process text that frequently contains spelling errors, informal language, or custom abbreviations, and standard word embedding models struggle.
Not ideal if your text data is perfectly clean and grammatically correct, as simpler word embedding models might suffice.
Stars
174
Forks
39
Language
Python
License
Apache-2.0
Category
Last pushed
Oct 09, 2023
Commits (30d)
0
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