Scaling PyTorch Model Training With Minimal Code Changes @SebastianRaschka
Scaling PyTorch Model Training With Minimal Code Changes @SebastianRaschka
Uploaded June 2023 | Updated September 2026, 2 weeks ago
Sebastian's books: sebastianraschka.com/books

Code examples: github.com/rasbt/cvpr2023

In this short tutorial, I will show you how to accelerate the training of LLMs and Vision Transformers with minimal code changes using open-source libraries.

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To support this channel, please consider purchasing a copy of my books: sebastianraschka.com/books

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Scaling PyTorch Model Training With Minimal Code ChangesL8.5 Logistic Regression in PyTorch Code ExampleL14.1: Convolutions and Padding13.0 Introduction to Feature Selection (L13: Feature Selection)Build A Reasoning Model (From Scratch), Page 198L12.0: Improving Gradient Descent-based Optimization Lecture OverviewL13.3 Convolutional Neural Network BasicsL8.3 Logistic Regression Loss Derivative and TrainingL12.6 Additional Topics and Research on Optimization AlgorithmsL11.3 BatchNorm in PyTorch Code ExampleL16.2 A Fully-Connected AutoencoderL16.0 Introduction to Autoencoders Lecture Overview
Sebastian Raschka |

Scaling PyTorch Model Training With Minimal Code Changes

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