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---
language: en
license: mit
datasets:
- glue
- mrpc
metrics:
- f1
tags:
- text-classfication
- nlp
- neural-compressor
- PostTrainingDynamic
- int8
- Intel® Neural Compressor
---
# Dynamically quantized DistilBERT base uncased finetuned MPRC
## Table of Contents
- [Model Details](#model-details)
- [How to Get Started With the Model](#how-to-get-started-with-the-model)
## Model Details
**Model Description:** This model is a [DistilBERT](https://huggingface.co/textattack/distilbert-base-uncased-MRPC) fine-tuned on MPRC dynamically quantized with [optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [huggingface/optimum-intel](https://github.com/huggingface/optimum-intel) through the usage of [Intel® Neural Compressor](https://github.com/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](https://huggingface.co/textattack/distilbert-base-uncased-MRPC) model card.
## How to Get Started With the Model
### PyTorch
To load the quantized model, you can do as follows:
```python
from optimum.intel import INCModelForSequenceClassification
model_id = "Intel/distilbert-base-uncased-MRPC-int8-dynamic"
model = INCModelForSequenceClassification.from_pretrained(model_id)
```
#### Test result
| |INT8|FP32|
|---|:---:|:---:|
| **Accuracy (eval-f1)** |0.8983|0.9027|
| **Model size (MB)** |75|268|
|