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Dynamically quantized DistilBERT base uncased finetuned MPRC

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Model Details

Model Description: This model is a DistilBERT fine-tuned on MPRC dynamically quantized with optimum-intel through the usage of huggingface/optimum-intel through the usage of Intel® Neural Compressor.

  • Model Type: Text Classification
  • Language(s): English
  • License: Apache-2.0
  • Parent Model: For more details on the original model, we encourage users to check out this model card.

How to Get Started With the Model


To load the quantized model, you can do as follows:

from optimum.intel import INCModelForSequenceClassification

model_id = "Intel/distilbert-base-uncased-MRPC-int8-dynamic"
model = INCModelForSequenceClassification.from_pretrained(model_id)

Test result

Accuracy (eval-f1) 0.8983 0.9027
Model size (MB) 75 268
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Dataset used to train Intel/distilbert-base-uncased-MRPC-int8-dynamic-inc

Collection including Intel/distilbert-base-uncased-MRPC-int8-dynamic-inc