ztjhz/miniLM

Small Model Is All You Need - NTU SC4001 Neural Network & Deep Learning Project

14
/ 100
Experimental

This project helps companies and startups analyze text data efficiently to understand customer sentiment or classify text. It takes raw text inputs, such as customer reviews from IMDb, Yelp, or SST-2 datasets, and outputs a sentiment classification or other text analysis, showing whether smaller, more cost-effective language models can perform as well as larger, more expensive ones. This is for AI practitioners or decision-makers evaluating model choices for their NLP applications.

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Use this if you need to perform sentiment analysis or other text classification tasks and want to determine if a smaller, more resource-efficient language model can meet your performance requirements instead of a large, expensive one.

Not ideal if you are looking for a pre-packaged, production-ready API for immediate deployment rather than a research framework to compare and train models.

sentiment-analysis natural-language-processing machine-learning-model-selection text-classification AI-efficiency
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 0 / 25

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Language

Python

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Last pushed

Nov 09, 2023

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