Training a Classifier — PyTorch Tutorials 2.9.0+cu128 documentation
3. Define a Loss function and optimizer # Let’s use a Classification Cross-Entropy loss and SGD with momentum.
NLP From Scratch: Classifying Names with a Character-Level
Using the dataset object allows us to easily split the data into train and test sets. Here we create a 85/15 split but the torch.utils.data has more useful utilities. Here we specify a generator since …
Transfer Learning for Computer Vision Tutorial - PyTorch
In this tutorial, you will learn how to train a convolutional neural network for image classification using transfer learning. You can read more about the transfer learning at cs231n notes
torchvision.models — Torchvision 0.8.1 documentation
The models subpackage contains definitions of models for addressing different tasks, including: image classification, pixelwise semantic segmentation, object detection, instance …
PyTorch Examples — PyTorchExamples 1.11 documentation
The PyTorch C++ frontend is a C++14 library for CPU and GPU tensor computation. This set of examples includes a linear regression, autograd, image recognition (MNIST), and other useful …
Welcome to PyTorch Tutorials — PyTorch Tutorials 2.9.0+cu128 …
Build a image classifier model in PyTorch and convert it to ONNX before deploying it with ONNX Runtime.
Models and pre-trained weights - PyTorch
The pre-trained models for detection, instance segmentation and keypoint detection are initialized with the classification models in torchvision. The models expect a list of Tensor[C, H, W].
PyTorch documentation — PyTorch 2.9 documentation
PyTorch documentation # PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. Features described in this documentation are classified by release status: Stable …
PyTorch-Transformers
PyTorch-Transformers (formerly known as pytorch - pretrained - bert) is a library of state-of-the-art pre-trained models for Natural Language Processing (NLP). The library currently contains …
Learning PyTorch with Examples
Here we introduce the most fundamental PyTorch concept: the Tensor. A PyTorch Tensor is conceptually identical to a numpy array: a Tensor is an n-dimensional array, and PyTorch …