GitHub

TurboQuant PyTorch — Implementation + Deep Tutorial

A from-scratch PyTorch implementation of TurboQuant (ICLR 2026), Google's two-stage vector quantization algorithm for compressing LLM key-value caches — enhanced ...
GitHub

char_rnn_classification_tutorial.py

This tutorials is part of a three-part series: * `NLP From Scratch: Classifying Names with a Character-Level RNN <https://pytorch.org/tutorials/intermediate/char_rnn ...
来自MSN

Network in Network (NiN) Explained – Deep Neural Network Tutorial with PyTorch

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...
Semiconductor Engineering

Deploying PyTorch Models On Edge Devices

AI is being rapidly adopted in edge computing. As a result, it is increasingly important to deploy machine learning models on Arm edge devices. Arm-based processors are common in embedded systems ...
腾讯网

拥抱 PyTorch，来自 Gauss 的自我革命

自 2015 年 TensorFlow 开源以来，伴随着深度学习的迅猛发展，通用深度学习框架经历了 10 年的高速发展，大浪淘沙，余者寥寥。曾几何时，也有过性能与易用性之争，也有过学术界和工业界之分，但随着本轮大模型应用的推波助澜，PyTorch 无疑已经成为事实上的大 ...
IEEE

Training Recurrent Neural Network-Based Model to Predict COVID-19 Patient Risk for PASC ...

Abstract: Pytorch_EHR is a codebase enabling fast prototyping of deep learning-based predictive models using electronic health records structured data. Rather than a collection of vertical pipelines ...