microsoft/Litmus
AI Assistant for Building Reliable, High-performing and Fair Multilingual NLP Systems
This tool helps AI system developers predict how well a multilingual natural language processing (NLP) model will perform across roughly 100 different languages, given existing training data on various languages and their performance. It takes observed training data sizes and corresponding model test performances as input to simulate performance, and outputs suggestions for data collection strategies to achieve optimal performance in target languages. It's designed for machine learning engineers and researchers building and deploying multilingual AI applications.
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Use this if you need to optimize data collection for multilingual NLP models and want to predict performance in various languages without extensive, costly experimentation.
Not ideal if you are working with single-language models or if your primary concern is not multilingual performance and data strategy.
Stars
48
Forks
7
Language
Python
License
MIT
Category
Last pushed
Aug 19, 2022
Commits (30d)
0
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