mts-ai/OpenAutoNLU

An open-source pipeline for training natural language understanding models

28
/ 100
Experimental

This tool helps data scientists and machine learning engineers quickly train natural language understanding (NLU) models for tasks like text classification (e.g., sentiment analysis) and named entity recognition (e.g., extracting product names). You provide your text data for training, and it automatically selects the best training approach based on your dataset size, producing a ready-to-deploy NLU model.

Use this if you need to train text classification or named entity recognition models and want an automated, data-driven workflow that handles different data sizes (from very small to large) without manual method selection.

Not ideal if you need to perform other natural language tasks beyond text classification or named entity recognition, or if you prefer to manually control every low-level detail of your model training process.

natural-language-processing text-classification named-entity-recognition machine-learning-engineering data-science
No Package No Dependents
Maintenance 10 / 25
Adoption 7 / 25
Maturity 11 / 25
Community 0 / 25

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39

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Language

Python

License

Last pushed

Mar 12, 2026

Commits (30d)

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