bert-base-NER / README.md
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metadata
library_name: onnx
tags:
  - bert
  - ner
  - named-entity-recognition
  - token-classification
  - conll2003
  - onnx
  - inference4j
license: mit
pipeline_tag: token-classification

BERT Base NER — ONNX

ONNX export of dslim/bert-base-NER, a BERT model fine-tuned on CoNLL-2003 for Named Entity Recognition. Identifies persons, organizations, locations, and miscellaneous entities in text using IOB2 tagging.

Mirrored for use with inference4j, an inference-only AI library for Java.

Original Source

Usage with inference4j

try (BertNerRecognizer ner = BertNerRecognizer.builder()
        .modelId("inference4j/bert-base-NER")
        .build()) {
    List<NamedEntity> entities = ner.recognize("John works at Google in London.");
    for (NamedEntity e : entities) {
        System.out.printf("%s (%s)%n", e.text(), e.label());
    }
}

Model Details

Property Value
Architecture BERT Base (12 layers, 768 hidden, 110M params)
Task Named Entity Recognition (IOB2 tagging)
Labels O, B-PER, I-PER, B-ORG, I-ORG, B-LOC, I-LOC, B-MISC, I-MISC
Training data CoNLL-2003
F1 score 91.3
Max sequence length 512
Tokenizer WordPiece (cased)
Original framework PyTorch (HuggingFace Transformers)

License

This model is licensed under the MIT License. Original model by dslim, ONNX export by Xenova.