hoangthangta/ThangKAN
KANs for text classification on GLUE tasks
This project explores using Kolmogorov-Arnold Networks (KANs) for text classification. It takes text inputs and assigns them to one of two categories, like determining if two sentences are semantically equivalent or if a sentence is grammatically acceptable. Researchers and machine learning practitioners focused on exploring novel neural network architectures for natural language understanding would find this useful.
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Use this if you are a machine learning researcher interested in experimenting with KANs for fundamental text classification tasks and evaluating their performance against traditional transformer-based methods.
Not ideal if you need a production-ready solution for text classification or if you are looking for highly optimized, state-of-the-art results for real-world NLP applications.
Stars
9
Forks
3
Language
Python
License
MIT
Last pushed
Jul 27, 2024
Commits (30d)
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