
# ONNX version of dslim/bert-large-NER

**This model is a conversion of [dslim/bert-large-NER](https://huggingface.co/dslim/bert-large-NER) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library.

**bert-large-NER** is a fine-tuned BERT model that is ready to use for **Named Entity Recognition** and achieves **state-of-the-art performance** for the NER task. It has been trained to recognize four types of entities: location (LOC), organizations (ORG), person (PER) and Miscellaneous (MISC). 

Specifically, this model is a *bert-large-cased* model that was fine-tuned on the English version of the standard [CoNLL-2003 Named Entity Recognition](https://www.aclweb.org/anthology/W03-0419.pdf) dataset. 

## Usage

Loading the model requires the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library installed.

```python
from optimum.onnxruntime import ORTModelForTokenClassification
from transformers import AutoTokenizer, pipeline


tokenizer = AutoTokenizer.from_pretrained("laiyer/bert-large-NER-onnx")
model = ORTModelForTokenClassification.from_pretrained("laiyer/bert-large-NER-onnx")
ner = pipeline(
    task="ner",
    model=model,
    tokenizer=tokenizer,
)

ner_output = ner("My name is John Doe.")
print(ner_output)
```

### LLM Guard

[Anonymize scanner](https://llm-guard.com/input_scanners/anonymize/)

## Community

Join our Slack to give us feedback, connect with the maintainers and fellow users, ask questions, 
or engage in discussions about LLM security!

<a href="https://join.slack.com/t/laiyerai/shared_invite/zt-28jv3ci39-sVxXrLs3rQdaN3mIl9IT~w"><img src="https://github.com/laiyer-ai/llm-guard/blob/main/docs/assets/join-our-slack-community.png?raw=true" width="200"></a>

{"language": ["en"], "license": "mit", "tags": ["ner", "bert"], "datasets": ["conll2003"], "inference": false, "pipeline_tag": "token-classification", "model-index": [{"name": "dslim/bert-large-NER", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "conll2003", "type": "conll2003", "config": "conll2003", "split": "test"}, "metrics": [{"type": "accuracy", "value": 0.9031688753722759, "name": "Accuracy", "verified": true}, {"type": "precision", "value": 0.920025068328604, "name": "Precision", "verified": true}, {"type": "recall", "value": 0.9193688678588825, "name": "Recall", "verified": true}, {"type": "f1", "value": 0.9196968510445761, "name": "F1", "verified": true}, {"type": "loss", "value": 0.5085050463676453, "name": "loss", "verified": true}]}]}]}
transformers onnx bert token-classification ner en dataset:conll2003 license:mit model-index autotrain_compatible region:us