protectai/bert-large-cased-finetuned-conll03-english-onnx

🤗 Hugging Face 来源token-classificationmit1.3 GBother✓ 1 个校验和今天更新
一条命令提交

在你的模型文件夹旁边运行它。它会制作种子、将文件与 Hugging Face 比对,然后提交。你只需开始做种,并粘贴你账户中的密钥。它只读取你的文件,绝不修改。如果愿意,可以先阅读脚本。

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo protectai/bert-large-cased-finetuned-conll03-english-onnx ./model-folder
需要做种者 →

[!WARNING] THIS PROJECT HAS BEEN ARCHIVED.

This project and its associated code on GitHub are no longer under active development or maintained.

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)

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