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---
language:
- en
inference: false
pipeline_tag: token-classification
tags:
- ner
license: mit
datasets:
- conll2003
base_model: dbmdz/bert-large-cased-finetuned-conll03-english
---
# ONNX version of dbmdz/bert-large-cased-finetuned-conll03-english
**This model is a conversion of [dbmdz/bert-large-cased-finetuned-conll03-english](https://huggingface.co/dbmdz/bert-large-cased-finetuned-conll03-english) to ONNX** format using the [🤗 Optimum](https://huggingface.co/docs/optimum/index) library.
`dbmdz/bert-large-cased-finetuned-conll03-english` is designed for named-entity recognition (NER), capable of finding person, organization, and other entities in the text.
## 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-cased-finetuned-conll03-english-onnx")
model = ORTModelForTokenClassification.from_pretrained("laiyer/bert-large-cased-finetuned-conll03-english-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>
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