DFKI-NLP/InterroLang

InterroLang: Exploring NLP Models and Datasets through Dialogue-based Explanations [EMNLP 2023 Findings]

13
/ 100
Experimental

This tool helps researchers and practitioners in natural language processing (NLP) understand why their models make certain predictions and to analyze their datasets. You provide an NLP model (like for question answering or hate speech detection) and a dataset, and the tool generates explanations through an interactive dialogue. This is for data scientists, NLP researchers, or machine learning engineers who need to interpret their NLP models' behavior and explore their training data.

No commits in the last 6 months.

Use this if you need to gain deeper insights into how your NLP models are working, debug unexpected predictions, or explore the characteristics of your datasets through interactive explanations.

Not ideal if you are looking for a simple 'black box' solution without needing to understand the underlying mechanics of your NLP models or datasets.

NLP-model-explanation dataset-analysis machine-learning-interpretability question-answering hate-speech-detection
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 5 / 25
Maturity 8 / 25
Community 0 / 25

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Language

Python

License

Last pushed

Oct 23, 2023

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