# BERT optimization with PTQ on CPU
This is a sample use case of olive to optimize a [Bert](https://huggingface.co/Intel/bert-base-uncased-mrpc) model using onnx conversion, onnx transformers optimization,
onnx quantization tuner and performance tuning.

Performs optimization pipeline:
- *PyTorch Model -> Onnx Model -> Transformers Optimized Onnx Model -> Quantized Onnx Model -> Tune performance*

Outputs the best metrics, model, and corresponding Olive config.

## Prerequisites
Please go to example repository [Quickstart Bert Example](https://github.com/microsoft/Olive/tree/main/examples/bert_ptq_cpu)
### Pip requirements
Install the necessary python packages:
```
python -m pip install -r requirements.txt
```

## Run sample using config. The optimization techniques to run are specified in bert_config.json
```
python -m olive.workflows.run --config bert_config.json
```
or run simply with python code:
```python
from olive.workflows import run as olive_run
olive_run("bert_config.json")
```

## Optimize model automatically without selecting any optimization technique.
```
python -m olive.workflows.run --config auto_bert_config.json
```
or run simply with python code:
```python
from olive.workflows import run as olive_run
olive_run("auto_bert_config.json")
```