a-tokyo/ai-zero-shot-classifier
🧠leverage advanced AI embeddings to perform multilingual zero-shot text classification. Whether you're dealing with unlabelled data or seeking to classify text against dynamic and user-defined labels, this library provides a seamless and efficient solution.
This tool helps you quickly categorize large amounts of text, like customer feedback, news articles, or social media posts, without needing to manually label examples first. You provide the text you want to sort and a list of categories you want to sort them into, and it tells you which category each piece of text fits best. This is ideal for analysts, marketers, or researchers who need to understand sentiment, topic, or intent across large, unorganized text datasets.
Available on npm.
Use this if you need to rapidly sort unlabelled text into categories that you define on-the-fly, without the time and expense of manually tagging thousands of examples or retraining a machine learning model.
Not ideal if you have a well-defined, static set of categories and already possess a large, high-quality dataset of pre-labelled examples for traditional model training.
Stars
12
Forks
1
Language
TypeScript
License
MIT
Category
Last pushed
Oct 30, 2025
Commits (30d)
0
Dependencies
3
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