Get Started
Choose Your Path: Install PyTorch Locally or Launch Instantly on Supported Cloud Platforms
PyTorch: The Open Language of AI
Key takeaways: PyTorch today powers the generative AI world with major AI players like Meta, OpenAI, Microsoft, Amazon, Apple and many others building cutting edge AI systems. PyTorch has evolved…
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Recap of the PyTorch Korea User Group Meetup: A Technical Conference with a PyTorch Core Maintainer
At the end of March, the PyTorch Korea User Group hosted a special meetup that brought together prominent speakers for deep discussions on the PyTorch core and its broader ecosystem.…
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FlexAttention Part II: FlexAttention for Inference
Overview In PyTorch 2.5.0 release, we introduced FlexAttention torch.nn.attention.flex_attention for ML researchers who’d like to customize their attention kernels without writing kernel code. This blog introduces our decoding backend optimized…
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Join PyTorch Foundation
As a member of the PyTorch Foundation, you’ll have access to resources that allow you to be stewards of stable, secure, and long-lasting codebases. You can collaborate on training, local and regional events, open-source developer tooling, academic research, and guides to help new users and contributors have a productive experience.
Key Features & Capabilities
Production Ready
Transition seamlessly between eager and graph modes with TorchScript, and accelerate the path to production with TorchServe.
Distributed Training
Scalable distributed training and performance optimization in research and production is enabled by the torch.distributed backend.
Robust Ecosystem
A rich ecosystem of tools and libraries extends PyTorch and supports development in computer vision, NLP and more.
Cloud Support
PyTorch is well supported on major cloud platforms, providing frictionless development and easy scaling.
Install PyTorch
Select your preferences and run the install command. Stable represents the most currently tested and supported version of PyTorch. This should be suitable for many users. Preview is available if you want the latest, not fully tested and supported, builds that are generated nightly. Please ensure that you have met the prerequisites below (e.g., numpy), depending on your package manager. Anaconda is our recommended package manager since it installs all dependencies. You can also install previous versions of PyTorch. Note that LibTorch is only available for C++.
NOTE: Latest PyTorch requires Python 3.9 or later.
PyTorch Build
Your OS
Package
Language
Compute Platform
Run this Command:
PyTorch Build
Stable (2.7.0)
Preview (Nightly)
Your OS
Linux
Mac
Windows
Package
Pip
LibTorch
Source
Language
Python
C++ / Java
Compute Platform
CUDA 11.8
CUDA 12.6
CUDA 12.8
ROCm 6.3
CPU
Run this Command:
pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
Quick Start With Cloud Partners
Get up and running with PyTorch quickly through popular cloud platforms and machine learning services.
Ecosystem
Featured Projects
Explore a rich ecosystem of libraries, tools, and more to support development.
Captum
Captum (“comprehension” in Latin) is an open source, extensible library for model interpretability built on PyTorch.
PyTorch Geometric
PyTorch Geometric is a library for deep learning on irregular input data such as graphs, point clouds, and manifolds.
skorch
skorch is a high-level library for PyTorch that provides full scikit-learn compatibility.
Companies & Universities Using PyTorch
Amazon Advertising
Reduce inference costs by 71% and scale out using PyTorch, TorchServe, and AWS Inferentia.
Salesforce
Pushing the state of the art in NLP and Multi-task learning.
Stanford University
Using PyTorch’s flexibility to efficiently research new algorithmic approaches.