robinvanschaik/interpret-flair
A small repository to test Captum Explainable AI with a trained Flair transformers-based text classifier.
This project helps machine learning engineers or data scientists understand why a Flair text classification model makes a certain prediction. You provide a trained Flair text classifier and a text input, and it outputs highlighted text showing which words or phrases contributed most to the model's classification decision. It’s for anyone building or evaluating text classification models with Flair who needs to explain their model's reasoning.
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Use this if you need to debug, validate, or gain trust in your Flair-based text classification models by understanding their internal workings.
Not ideal if you are looking for a complete, production-ready solution for explainable AI with Flair, as this is an experimental integration.
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Jupyter Notebook
License
MIT
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Last pushed
May 13, 2021
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