akdeniz27/bert-base-turkish-cased-ner-quantized

🤗 Hugging Face 来源token-classificationmit191 MBother✓ 2 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 akdeniz27/bert-base-turkish-cased-ner-quantized ./model-folder

需要做种者 →

Turkish Named Entity Recognition (NER) Quantized Model

This model is the dynamically quantized version of the model (https://akdeniz27/bert-base-turkish-cased-ner)

How to use:

# First install "optimum[onnxruntime]":
!pip install "optimum[onnxruntime]"

# and import "ORTModelForTokenClassification":
from transformers import AutoTokenizer, pipeline
from optimum.onnxruntime import ORTModelForTokenClassification

model = ORTModelForTokenClassification.from_pretrained("akdeniz27/bert-base-turkish-cased-ner-quantized", file_name="model_quantized.onnx")
tokenizer = AutoTokenizer.from_pretrained("akdeniz27/bert-base-turkish-cased-ner-quantized")
ner = pipeline('ner', model=model, tokenizer=tokenizer, aggregation_strategy="first")
ner("your text here")

Pls refer (https://github.com/akdeniz27/dynamic_quantization) for details of quantization.