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pytorch/examples

★ 23,898PythonAudience · developerComplexity · 2/5QuietLicenseSetup · easy

TLDR

Official PyTorch examples: small, focused code samples showing how to build image classifiers, language models, GANs, and reinforcement learning agents.

Mindmap

mindmap
  root((repo))
    What it does
      Image classification
      Language models
      Generative networks
      Reinforcement learning
    Learning path
      Handwritten digit recognition
      Neural style transfer
      Distributed training
    Tech stack
      PyTorch
      Python
      RNNs and Transformers
    Use cases
      Learn by example
      Adapt for own projects
      Explore ML tasks

Things people build with this

USE CASE 1

Learn PyTorch by studying working code examples for image classification, text generation, and other common ML tasks.

USE CASE 2

Adapt a provided example (like DCGAN or style transfer) as a starting point for your own machine learning project.

USE CASE 3

Understand how to set up distributed training across multiple machines using PyTorch.

USE CASE 4

Explore different neural network architectures (RNNs, Transformers, GANs) with runnable, minimal code.

Tech stack

PythonPyTorchRNNTransformerDCGAN

Getting it running

Difficulty · easy Time to first run · 5min
Use freely for any purpose, including commercial use, as long as you keep the copyright notice and license text.

In plain English

This is the official examples repository for PyTorch, the popular machine learning framework developed by Meta. It provides a curated collection of short, self-contained code examples that demonstrate how to use PyTorch for a variety of common tasks in machine learning and deep learning. The examples are intentionally kept small and focused, with minimal external dependencies, so they are easy to read and adapt to your own projects. Each example tackles a meaningfully different problem: training an image classifier on handwritten digits, building a language model with recurrent neural networks or transformers, training a generative adversarial network to produce images (DCGAN), doing neural style transfer to apply artistic styles to photos, reinforcement learning with classic algorithms, and more. There are also examples for distributed training across multiple machines. PyTorch is a Python framework used for building neural networks and other machine learning models. You would use this repo when you are learning PyTorch and want concrete, working starting points for specific tasks, image recognition, text generation, reinforcement learning, and so on, rather than reading abstract documentation.

Copy-paste prompts

Prompt 1
Show me how to adapt the PyTorch MNIST classifier example to train on my own image dataset.
Prompt 2
How do I modify the PyTorch transformer language model example to work with my custom text corpus?
Prompt 3
Walk me through the PyTorch distributed training example and explain how to run it on multiple GPUs.
Prompt 4
I want to implement neural style transfer using the PyTorch example, what changes do I need to make for my own images?
Prompt 5
How do I use the PyTorch reinforcement learning example as a template for a custom game environment?
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