1. https://github.com/pytorch/examples
2. 模型Hub聚集地(下载，托管): https://pytorch.org/hub/ or https://huggingface.co/models

3. 生产环境如何部署 For recipes on how to run PyTorch in production: https://github.com/facebookresearch/recipes

4. 最大的模型训练等Python代码大集合。ResNet等。Huggingface抱脸虫出品
   https://github.com/huggingface/pytorch-image-models
   （The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights – ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNet-V3/V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more）

回到开头:

1. pytorch官方： https://github.com/pytorch/examples

Available models 一大堆模型

• Image classification (MNIST) using Convnets
• Word-level Language Modeling using RNN and Transformer
• Training Imagenet Classifiers with Popular Networks
• Generative Adversarial Networks (DCGAN)
• Variational Auto-Encoders
• Superresolution using an efficient sub-pixel convolutional neural network
• Hogwild training of shared ConvNets across multiple processes on MNIST
• Training a CartPole to balance in OpenAI Gym with actor-critic
• Natural Language Inference (SNLI) with GloVe vectors, LSTMs, and torchtext
• Time sequence prediction - use an LSTM to learn Sine waves
• Implement the Neural Style Transfer algorithm on images
• Reinforcement Learning with Actor Critic and REINFORCE algorithms on OpenAI gym
• PyTorch Module Transformations using fx
• Distributed PyTorch examples with Distributed Data Parallel and RPC
• Several examples illustrating the C++ Frontend
• Image Classification Using Forward-Forward
• Language Translation using Transformers

pytorch官方以外别家的例子
Additionally, a list of good examples hosted in their own repositories:

- Neural Machine Translation using sequence-to-sequence RNN with attention (OpenNMT)