NeuroBERT-NER is an open-weight transformer model for token classification and named entity recognition in English. Developers can load it locally with Hugging Face Transformers for information extraction and NLP applications.
NeuroBERT NER sits in PulseGate's Other AI category. It focuses on extracting named entities and structured information from English text without training an NER model from scratch. It is built as an open-source project for NLP developers and machine learning engineers. NeuroBERT NER is open source under the Open Source license. It runs on the web and the command line, and it can be self-hosted.
It is developed by boltuix. Key capabilities include named entity recognition, token classification, and sequence labeling.
Summary written by a language model from the project’s public pages.
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