protectai/bert-large-cased-finetuned-conll03-english-onnx
By protectai · ↓ 5 · ♥ 0 · Updated 2024-03-25
What's in this repo
This page lists the files in protectai/bert-large-cased-finetuned-conll03-english-onnx, including model.onnx.
- 1 ONNX models (.onnx files)
- 8 files, including 4 .json, 1 .md, 1 .onnx, 1 .txt
- Last updated 2024-03-25
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
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
Community
Join our Slack to give us feedback, connect with the maintainers and fellow users, ask questions, or engage in discussions about LLM security!
Model info
Created: 2023-11-13
Updated: 2024-03-25
View on Hugging Face