yumeng5/LOTClass
[EMNLP 2020] Text Classification Using Label Names Only: A Language Model Self-Training Approach
This project helps data scientists and researchers automatically categorize large volumes of text without needing any pre-labeled examples. You provide a collection of documents and a list of category names (like "Sports" or "Politics"), and it outputs a model that can classify new, unseen documents into those categories. This is ideal for anyone dealing with text data who lacks the time or resources to manually label training data.
299 stars. No commits in the last 6 months.
Use this if you need to classify text into predefined categories but don't have existing labeled examples for training.
Not ideal if you need a solution that runs on standard CPU hardware or requires classifying text into categories not specified by clear label names.
Stars
299
Forks
61
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 02, 2022
Commits (30d)
0
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