Quantization

Travis chat

PyTorch documentation

This file is in the process of migration to torch/ao/quantization , and is kept here for compatibility while the migration process is ongoing. If you are adding a new entry/functionality, please, add ...

Quantization Screencast

Pete Warden's blog

TinyML Book Screencast 4 – Quantization For the past few months I’ve been working with Zain Asgar and Keyi Zhang on EE292D, Machine Learning on Embedded Systems, at Stanford. We’re hoping to open sour...

How to Perform Quantization in Machine Learning (Math Explained!)

Towards AI

Suppose you are fitting a large number of books into a small suitcase. You can’t take all of them, so you must decide which ones to bring and which to leave behind. This process of selecting and compr...

Tensor Quantization: The Untold Story

Towards Data Science

A close look at the implementation details of quantization in machine learning frameworks Co-authored with Naresh Singh. Table Of Contents * Introduction * What do the terms scale and zero-point mean...

Learning Vector Quantization

Towards Data Science

Nowadays the terms machine learning and artificial neural networks seem to be applied interchangeably. However, when it comes to ML algorithms there is a lot more under the sun than just neural…

A Visual Guide to Quantization

Towards Data Science

Demystifying the compression of large language models As their name suggests, Large Language Models (LLMs) are often too large to run on consumer hardware. These models may exceed billions of paramet...

A Personal History of ML Quantization

Pete Warden's blog

Tomorrow I’ll be giving a remote talk at the LBQNN workshop at ICCV. The topic is the history of quantization in machine learning, and while I don’t feel qualified to give an authoritative account, I ...

Dynamic Quantization

PyTorch Tutorials

Introduction There are a number of trade-offs that can be made when designing neural networks. During model development and training you can alter the number of layers and number of parameters in a re...

quantize

PyTorch documentation

Quantize the input float model with post training static quantization. First it will prepare the model for calibration, then it calls run_fn which will run the calibration step, after that we will con...

Vector Quantization Example

Scikit-learn Examples

Vector Quantization Example Face, a 1024 x 768 size image of a raccoon face, is used here to illustrate how k -means is used for vector quantization.

Quantization explained in plain English

Towards AI

My LLM diaries, 13-Oct-2024 When BERT was released around 5 years ago, it triggered a wave of Large Language Models with ever increasing sizes. As the model size got bigger, the performance improved ...

Image Quantization with K-Means

Towards Data Science

A simple hands-on tutorial for image compression via quantization with python, scikit-learn, numpy, PIL, and matplotlib Quantization refers to a technique where we express a range of values by a sing...