<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Distributed-Training on Noureddine RAMDI</title><link>https://ramdi.fr/tags/distributed-training/</link><description>Recent content in Distributed-Training on Noureddine RAMDI</description><generator>Hugo</generator><language>en</language><lastBuildDate>Sat, 23 May 2026 20:41:27 +0000</lastBuildDate><atom:link href="https://ramdi.fr/tags/distributed-training/index.xml" rel="self" type="application/rss+xml"/><item><title>Hivemind: decentralized peer-to-peer deep learning with PyTorch</title><link>https://ramdi.fr/github-stars/hivemind-decentralized-peer-to-peer-deep-learning-with-pytorch/</link><pubDate>Sat, 23 May 2026 20:41:14 +0000</pubDate><guid>https://ramdi.fr/github-stars/hivemind-decentralized-peer-to-peer-deep-learning-with-pytorch/</guid><description>Hivemind is a PyTorch library enabling decentralized deep learning over the internet using a peer-to-peer Distributed Hash Table (DHT). It supports fault-tolerant training and decentralized parameter averaging without global sync.</description></item></channel></rss>