OpenAutoNLU: Open Source AutoML Library for NLU
OpenAutoNLU is an open-source automated machine learning library for natural language understanding (NLU) tasks, covering both text classification and named entity recognition (NER). Unlike existing solutions, we introduce data-aware training regime selection that requires no manual configuration from the user. The library also provides integrated data quality diagnostics, configurable out-of-distribution (OOD) detection, and large language model (LLM) features, all within a minimal lowcode API. The demo app is accessible here https://openautonlu.dev.
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Grigory Arshinov
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2026-03-03T10:36:38.491Z
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Grigorii Arshinov
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GrigoriiArshinov
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Aleksandr Boriskin
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2026-03-03T10:36:51.514Z
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Aleksandr Boriskin
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Sergey Senichev
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2026-03-03T10:36:43.941Z
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Senichev Sergey
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Ayaz Zaripov
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Daria Galimzianova
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2026-03-03T10:36:41.267Z
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daria galimzianova
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Daniil Karpov
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Leonid Sanochkin
OpenAutoNLU: Open Source AutoML Library for NLU
OpenAutoNLU is an open-source automated machine learning library for natural language understanding (NLU) tasks, covering both text classification and named entity recognition (NER). Unlike existing solutions, we introduce data-aware training regime selection that requires no manual configuration from the user. The library also provides integrated data quality diagnostics, configurable out-of-distribution (OOD) detection, and large language model (LLM) features, all within a minimal lowcode API. The demo app is accessible here https://openautonlu.dev.
OpenAutoNLU is an open-source automated machine learning library for NLU tasks that employs data-aware training selection and includes integrated diagnostics and LLM features through a minimal low-code interface.
automated machine learning natural language understanding text classification named entity recognition data-aware training regime selection data quality diagnostics out-of-distribution detection large language models