macanv/BERT-BiLSTM-CRF-NER
A TensorFlow implementation combining BERT pre-training with BiLSTM-CRF for Named Entity Recognition tasks, with Flask-based inference serving.
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This repository provides a complete NER (Named Entity Recognition) solution using Google BERT for feature extraction fine-tuned with a Bidirectional LSTM CRF layer. The project supports both Chinese and English NER tasks, includes training pipelines with configurable parameters, and exposes a Flask-based HTTP service for serving NER predictions. The architecture leverages BERT’s contextual representations combined with sequence labeling through CRF decoding.
Frequently asked
- What is macanv/BERT-BiLSTM-CRF-NER?
- A TensorFlow implementation combining BERT pre-training with BiLSTM-CRF for Named Entity Recognition tasks, with Flask-based inference serving.
- Is BERT-BiLSTM-CRF-NER open source?
- Yes — macanv/BERT-BiLSTM-CRF-NER is an open-source project tracked on heatdrop.
- What language is BERT-BiLSTM-CRF-NER written in?
- macanv/BERT-BiLSTM-CRF-NER is primarily written in Python.
- How popular is BERT-BiLSTM-CRF-NER?
- macanv/BERT-BiLSTM-CRF-NER has 4.9k stars on GitHub.
- Where can I find BERT-BiLSTM-CRF-NER?
- macanv/BERT-BiLSTM-CRF-NER is on GitHub at https://github.com/macanv/BERT-BiLSTM-CRF-NER.