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# Accessing ONNX Examples

Users can get the example code after downloading and unzipping `amd_quark.zip` (referring to Installation Guide). The example folder is in amd_quark.zip.

> Directory Structure of the ZIP File:

>     + amd_quark.zip
>        + amd_quark.whl
>        + examples    # HERE IS THE EXAMPLES
>           + torch
>              + language_modeling
>              + diffusers
>              + ...
>           + onnx # HERE ARE THE ONNX EXAMPLES
>              + image_classification
>              + object_detection
>              + ...
>        + ...

## ONNX Examples in AMD Quark for This Release

Improving Model Accuracy

- Block Floating Point (BFP)
- MX Formats
- Fast Finetune AdaRound
- Fast Finetune AdaQuant
- Cross-Layer Equalization (CLE)
- Layer-wise Percentile
- GPTQ
- Mixed Precision
- Smooth Quant
- QuaRot
- Auto-Search for Ryzen AI Yolov8 ONNX Model Quantization
- Auto-Search for Ryzen AI MobileNetv2-50 ONNX Quantization with Custom Evaluator
- Auto-Search for Ryzen AI Resnet50 ONNX Model Quantization

Dynamic Quantization

- Quantizing an Llama-2-7b Model
- Quantizing an OPT-125M Model

Image Classification

- Quantizing a ResNet50-v1-12 Model
- Quantizing a Huggingface TIMM Model

Language Models

- Quantizing an OPT-125M Model

Weights-Only Quantization

- Quantizing an Llama-2-7b Model Using the ONNX MatMulNBits
- Quantizing Llama-2-7b model using MatMulNBits

Crypto Mode

- Quantizing a ResNet50 model in crypto mode

Ryzen AI Quantization

- Best Practice for Quantizing an Image Classification Model
- Best Practice for Quantizing an Object Detection Model