neuml/staticvectors
🔢 Work with static vector models
This tool helps data scientists and NLP practitioners efficiently work with older, 'static' word vector models like Word2Vec or FastText. It takes existing models or raw text for training and allows you to use them for tasks like language identification or getting word embeddings. This is ideal for those who need fast, lightweight text processing, especially with less common languages or when modern, larger models are overkill.
Used by 2 other packages. No commits in the last 6 months. Available on PyPI.
Use this if you need to work with established word vector models quickly and easily, especially for tasks like language identification or when resource constraints or specific language support make newer models impractical.
Not ideal if your primary need is state-of-the-art performance with common languages using the latest Transformer-based language models.
Stars
37
Forks
—
Language
Python
License
Apache-2.0
Category
Last pushed
Apr 21, 2025
Commits (30d)
0
Dependencies
4
Reverse dependents
2
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/neuml/staticvectors"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
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