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

🤗 Hugging Face sourcetoken-classificationmit191 MBother✓ 2 checksumsupdated today

Submit in one command

Run it next to your model folder. It makes the torrent, checks your files against Hugging Face, and submits it. You just start seeding and paste your key from your account. It only reads your files and never changes them. Read the script first if you like.

curl -fsSL https://pirateface.co/package.sh | bash -s -- --repo akdeniz27/bert-base-turkish-cased-ner-quantized ./model-folder

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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.