MCT Features
July 9, 2026 · View on GitHub
This tutorial set introduces the various quantization tools offered by MCT. The notebooks included here illustrate the setup and usage of both basic and advanced post-training quantization methods. You'll learn how to refine PTQ (Post-Training Quantization) settings, export models, and explore advanced compression techniques such as GPTQ (Gradient-Based Post-Training Quantization), Mixed precision quantization and more. These techniques are essential for further optimizing models and achieving superior performance in deployment scenarios.
Keras Tutorials
Post-Training Quantization (PTQ)
| Tutorial | Included Features |
|---|---|
| Basic Post-Training Quantization (PTQ) | ✅ PTQ |
| Mixed-Precision MobileNetV2 | ✅ PTQ ✅ Mixed-Precision |
Gradient-Based Post-Training Quantization (GPTQ)
| Tutorial | Included Features |
|---|---|
| MobileNetV2 | ✅ GPTQ |
Quantization-Aware Training (QAT)
| Tutorial | Included Features |
|---|---|
| QAT on MNIST | ✅ QAT |
Structured Pruning
| Tutorial | Included Features |
|---|---|
| Fully-Connected Model Pruning | ✅ Pruning |
Export Quantized Models
| Tutorial | Included Features |
|---|---|
| Exporter Usage | ✅ Export |
Debug Tools
| Tutorial | Included Features |
|---|---|
| Network Editor Usage | ✅ Network Editor |
Wrapper
| Tutorial | Included Features |
|---|---|
| Wrapper | ✅ Wrapper |
Pytorch Tutorials
Post-Training Quantization (PTQ)
| Tutorial | Included Features |
|---|---|
| Basic Post-Training Quantization (PTQ) | ✅ PTQ |
| Mixed-Precision Post-Training Quantization | ✅ PTQ ✅ Mixed-Precision |
| Advanced Gradient-Based Post-Training Quantization (GPTQ) | ✅ GPTQ |
Structured Pruning
| Tutorial | Included Features |
|---|---|
| Fully-Connected Model Pruning | ✅ Pruning |
Data Generation
| Tutorial | Included Features |
|---|---|
| Zero-Shot Quantization (ZSQ) using Data Generation | ✅ PTQ ✅ ZSQ ✅ Data-Free Quantization ✅ Data Generation |
Export Quantized Models
| Tutorial | Included Features |
|---|---|
| Exporter Usage | ✅ Export |
| ONNX Inference Usage | ✅ ONNX Inference |
Quantization Troubleshooting
| Tutorial | Included Features |
|---|---|
| Quantization Troubleshooting using the Xquant Feature | ✅ Debug |
| XQuant Extension Tool (Part1) | ✅ Judgeable Troubleshooting |
| XQuant Extension Tool (Part2) | ✅ General Troubleshooting |
Wrapper
| Tutorial | Included Features |
|---|---|
| Wrapper | ✅ Wrapper |