OpenAutoNLU: Open Source AutoML Library for NLU
Abstract
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.
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.
Community
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 low-code API. OpenAutoNLU source code is available here, the demo app is accessible here at https://openautonlu.dev.
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