Understanding PyTorch Buffers @SebastianRaschka
Understanding PyTorch Buffers  @SebastianRaschka
Uploaded July 2024 | Updated September 2026, 1 week ago
Sebastian's books: sebastianraschka.com/books

This video explains what PyTorch buffers are, a concept that is particularly useful when dealing with GPU computations and implement large models like LLMs.

Code notebook: github.com/rasbt/LLMs-from-scratch/blob/main/ch03/03_understanding-buffers/understanding-buffers.ipynb

GitHub discussion about "triu" in the forward pass: github.com/rasbt/LLMs-from-scratch/discussions/282

Link to the Studio GPU environment to follow along: lightning.ai/seraschka/studios/understanding-pytorch-buffers?section=recent

---

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

---

twitter.com/rasbt
linkedin.com/in/sebastianraschka
magazine.sebastianraschka.com
Understanding PyTorch BuffersL14.3.1.2 VGG16 in PyTorch   Code ExampleL1.6 About the Practical Aspects and Tools Used in This CourseL9.5.1 Cats & Dogs and Custom Data LoadersL11.5 Weight Initialization   Why Do We Care?L11.6 Xavier Glorot and Kaiming He Initialization13.4.1 Recursive Feature Elimination (L13: Feature Selection)L14.2: Spatial Dropout and BatchNormL15.6 RNNs for Classification: A Many-to-One Word RNNL2.4 The Deep Learning Hardware & Software LandscapeWhat I Learned From Implementing LLM Architectures From Scratch (And How to Get Started)Introduction to Generative Adversarial Networks (Tutorial Recording at ISSDL 2021)
Sebastian Raschka |

Understanding PyTorch Buffers

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER