Quantization

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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...

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.

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...

The AQLM Quantization Algorithm, Explained

Towards Data Science

There is a new quantization algorithm in town! The Additive Quantization of Language Models (AQLM) [1] quantization procedure was released in early February 2024 and has already been integrated to Hug...

quantize_qat

PyTorch documentation

Do quantization aware training and output a quantized model model – input model run_fn – a function for evaluating the prepared model, can be a function that simply runs the prepared model or a traini...

Quantization: Post Training Quantization, Quantization Error, and Quantization Aware Training

Towards AI

Efficient Inference in AI Models Photo by Jason Leung on Unsplash Most of us used open-source Large Language Models, VLMs, and Multi-Modal Models in our system, colab, or Kaggle notebook. You might h...

A Deep Dive Into Model Quantization

Towards AI

Typically, the parameters of a neural network (layer weights) are represented using 32-bit floating-point numbers. The rationale is that since the parameters of a machine learning model are not constr...

Want to Learn Quantization in The Large Language Model?

Towards AI

A simple guide to teach you intuition about quantization with simple mathematical derivation and coding in PyTorch. 1\. Image by writer: Flow shows the need for quantization. (The happy face and angr...

Know about Quantization in TensorFlow

Analytics Vidhya

Whenever I work on deep learning projects to train a model and make it ready for production by saving the model, it gives me huge memory. Then I started researching to decrease the saved model memory…...

Quantisation of Models

Analytics Vidhya

In this article, we will study about quantisation of models in tensorflow to get an excellent inference in edge devices.

Introduction to Weight Quantization

Towards Data Science

Reducing the size of Large Language Models with 8-bit quantization Large Language Models (LLMs) are known for their extensive computational requirements. Typically, the size of a model is calculated ...

The Ultimate Handbook for LLM Quantization

Towards Data Science

A deep dive into LLM quantization and techniques Photo by Siednji Leon on Unsplash LLMs on CPU? Yes, you heard it right. From handling conversations to creating its own images, AI has come a long way...

4-bit Quantization with GPTQ

Towards Data Science

Recent advancements in weight quantization allow us to run massive large language models on consumer hardware, like a LLaMA-30B model on an RTX 3090 GPU. This is possible thanks to novel 4-bit quantiz...

LLM Quantization Techniques- GPTQ

Towards AI

Recent advances in neural network technology have dramatically increased the scale of the model, resulting in greater sophistication and intelligence. Large Language Models (LLMs) have received high p...

What I’ve learned about neural network quantization

Pete Warden's blog

Photo by badjonni It’s been a while since I last wrote about using eight bit for inference with deep learning, and the good news is that there has been a lot of progress, and we know a lot more than w...

Quantization, Linear Regression, and Hardware for AI: Our Best Recent Deep Dives

Towards Data Science

There are times when brevity is a blessing; sometimes you just need to figure something out quickly to move ahead with your day. More often than not, though, if you’d like to truly learn about a new t...

Optimizing Vector Quantization Methods by Machine Learning Algorithms

Towards Data Science

Machine learning optimization of vector quantization methods used in end-to-end training of neural networks This post is a short explanation of my paper [1] published at ICASSP 2023 conference. For m...