akdeniz27/convbert-base-turkish-cased-ner-quantized
By akdeniz27 · ↓ 6 · ♥ 0 · Updated 2022-12-23
What's in this repo
This page lists the files in akdeniz27/convbert-base-turkish-cased-ner-quantized, including model_quantized.onnx.
- 1 ONNX models (.onnx files)
- 9 files, including 5 .json, 1 .md, 1 .onnx, 1 .txt
- Last updated 2022-12-23
ONNX files
| File | Size | Download |
|---|---|---|
| model_quantized.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
Turkish Named Entity Recognition (NER) Quantized Model
This model is the dynamically quantized version of the model (https://akdeniz27/convbert-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_onnx = ORTModelForTokenClassification.from_pretrained("akdeniz27/convbert-base-turkish-cased-ner-quantized", file_name="model_quantized.onnx")
tokenizer = AutoTokenizer.from_pretrained("akdeniz27/convbert-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.
Model info
Created: 2022-11-28
Updated: 2022-12-23
View on Hugging Face