This is a SpanMarker model based on bert-base-uncased, specifically trained for acronym identification as a form of named entity recognition. It can be used with the SpanMarker library for token classification tasks. The model is open source and intended for developers building NLP applications that require precise span-level entity detection.
Span Marker Bert Base Uncased Acronyms sits in PulseGate's Other AI category. Accurately detecting and classifying acronyms and named entities within text spans. It is built as an open-source project for developers. Span Marker Bert Base Uncased Acronyms is open source under the Apache-2.0 license. It runs on the web and API.
Behind Span Marker Bert Base Uncased Acronyms is tomaarsen, and the product first shipped in 2023. Development happens publicly on GitHub with 477 stars. Key capabilities include token classification, acronym identification, and named entity recognition.
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