inference4j/bert-base-NER
By inference4j · ↓ 12 · ♥ 0 · Updated 2026-03-02
What's in this repo
This page lists the files in inference4j/bert-base-NER, including model.onnx.
- 1 ONNX models (.onnx files)
- 5 files, including 1 .md, 1 .json, 1 .onnx, 1 .txt
- Last updated 2026-03-02
ONNX files
| File | Size | Download |
|---|---|---|
| model.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
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
- Repository: dslim (ONNX by Xenova)
- License: mit
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.
Model info
Created: 2026-03-02
Updated: 2026-03-02
View on Hugging Face