metadata

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 to ONNX format using the 🤗 Optimum 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 library installed.

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

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