Edit model card

INT8 distilbert-base-uncased-finetuned-conll03-english

Post-training static quantization

This is an INT8 PyTorch model quantized with huggingface/optimum-intel through the usage of Intel® Neural Compressor.

The original fp32 model comes from the fine-tuned model elastic/distilbert-base-uncased-finetuned-conll03-english.

The calibration dataloader is the train dataloader. The default calibration sampling size 100 isn't divisible exactly by batch size 8, so the real sampling size is 104.

Test result

INT8 FP32
Accuracy (eval-accuracy) 0.9859 0.9882
Model size (MB) 64.5 253

Load with optimum:

from optimum.intel import INCModelForTokenClassification

model_id = "Intel/distilbert-base-uncased-finetuned-conll03-english-int8-static"
int8_model = INCModelForTokenClassification.from_pretrained(model_id)
Downloads last month
28
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Dataset used to train Intel/distilbert-base-uncased-finetuned-conll03-english-int8-static-inc

Collection including Intel/distilbert-base-uncased-finetuned-conll03-english-int8-static-inc

Evaluation results