Skip To Main Content
Intel logo - Return to the home page
My Tools

Select Your Language

  • Bahasa Indonesia
  • Deutsch
  • English
  • Español
  • Français
  • Português
  • Tiếng Việt
  • ไทย
  • 한국어
  • 日本語
  • 简体中文
  • 繁體中文
Sign In to access restricted content

Using Intel.com Search

You can easily search the entire Intel.com site in several ways.

  • Brand Name: Core i9
  • Document Number: 123456
  • Code Name: Emerald Rapids
  • Special Operators: “Ice Lake”, Ice AND Lake, Ice OR Lake, Ice*

Quick Links

You can also try the quick links below to see results for most popular searches.

  • Product Information
  • Support
  • Drivers & Software

Recent Searches

Sign In to access restricted content

Advanced Search

Only search in

Sign in to access restricted content.

The browser version you are using is not recommended for this site.
Please consider upgrading to the latest version of your browser by clicking one of the following links.

  • Safari
  • Chrome
  • Edge
  • Firefox

Learn LLM Optimization Using Transformers and PyTorch* on CPUs & GPUs

@IntelDevTools

Subscribe Now

Stay in the know on all things CODE. Updates are delivered to your inbox.

Sign Up

Overview

Large language models (LLM) and the applications built around them have emerged as powerful tools for understanding and generating natural language. However, optimizing these models for maximum efficiency and performance remains a significant challenge.

This session introduces a solution: Optimize LLM workloads on target hardware using the Intel® Extension for Transformers* and Intel® Extension for PyTorch*.

The session also covers:

  • An introduction to Intel Extension for Transformers and Intel Extension for PyTorch—two powerful libraries for enhancing AI workload performance on Intel platforms.
  • Using API calls in the PyTorch extension to optimize LLM performance and memory use.
  • Using the transformer extension's optimization features, such as model compression, neural speed, and neural chat, which is a framework to build customized chatbots.

Skill level: Novice
 

Featured Software

Choose from the following download options:

  • Intel Extension for PyTorch from GitHub* or from the AI Tools selector
  • Intel Extension for Transformers from GitHub
     

Download Code Samples

  • Get Started with Intel Extension for PyTorch
  • See All Code Samples

Jump to:

You May Also Like
 

   

You May Also Like

Related Articles

Optimize PyTorch and TensorFlow* Models: Two On-Demand Training Sessions

Get Started with Intel Extension for PyTorch on a GPU

Increase PyTorch Inference Throughput by 4x

Optimize Transformer Model Inference on Intel Processors

Related Webinars & Workshops

Optimize PyTorch Performance on the Latest Intel CPUs and GPUs

Introduction: Get Faster PyTorch Programs with TorchDynamo

Optimize Transformer Models with Tools from Intel and Hugging Face*

Compress the Transformer: Optimize Your DistilBERT Models

  • Company Overview
  • Contact Intel
  • Newsroom
  • Investors
  • Careers
  • Corporate Responsibility
  • Inclusion
  • Public Policy
  • © Intel Corporation
  • Terms of Use
  • *Trademarks
  • Cookies
  • Privacy
  • Supply Chain Transparency
  • Site Map
  • Recycling
  • Your Privacy Choices California Consumer Privacy Act (CCPA) Opt-Out Icon
  • Notice at Collection

Intel technologies may require enabled hardware, software or service activation. // No product or component can be absolutely secure. // Your costs and results may vary. // Performance varies by use, configuration, and other factors. Learn more at intel.com/performanceindex. // See our complete legal Notices and Disclaimers. // Intel is committed to respecting human rights and avoiding causing or contributing to adverse impacts on human rights. See Intel’s Global Human Rights Principles. Intel’s products and software are intended only to be used in applications that do not cause or contribute to adverse impacts on human rights.

Intel Footer Logo