Simon Willison’s Weblog

GGUF, the long way around (via) Vicki Boykis dives deep into the GGUF format used by llama.cpp, after starting with a detailed description of how PyTorch models work and how they are traditionally persisted using Python pickle.

Pickle lead to safetensors, a format that avoided the security problems with downloading and running untrusted pickle files.

Llama.cpp introduced GGML, which popularized 16-bit (as opposed to 32-bit) quantization and bundled metadata and tensor data in a single file.

GGUF fixed some design flaws in GGML and is the default format used by Llama.cpp today. # 29th February 2024, 9:39 pm

Getting Started With CUDA for Python Programmers (via) if, like me, you’ve avoided CUDA programming (writing efficient code that runs on NVIGIA GPUs) in the past, Jeremy Howard has a new 1hr17m video tutorial that demystifies the basics. The code is all run using PyTorch in notebooks running on Google Colab, and it starts with a very clear demonstration of how to convert a RGB image to black and white. # 29th January 2024, 9:23 pm

How We Executed a Critical Supply Chain Attack on PyTorch (via) Report on a now handled supply chain attack reported against PyTorch which took advantage of GitHub Actions, stealing credentials from some self-hosted task runners.

The researchers first submitted a typo fix to the PyTorch repo, which gave them status as a “contributor” to that repo and meant that their future pull requests would have workflows executed without needing manual approval.

Their mitigation suggestion is to switch the option from ’Require approval for first-time contributors’ to ‘Require approval for all outside collaborators’.

I think GitHub could help protect against this kind of attack by making it more obvious when you approve a PR to run workflows in a way that grants that contributor future access rights. I’d like a “approve this time only” button separate from “approve this run and allow future runs from user X”. # 14th January 2024, 7:38 pm

Llama from scratch (or how to implement a paper without crying) (via) Brian Kitano implemented the model described in the Llama paper against TinyShakespeare, from scratch, using Python and PyTorch. This write-up is fantastic—meticulous, detailed and deeply informative. It would take several hours to fully absorb and follow everything Brian does here but it would provide multiple valuable lessons in understanding how all of this stuff fits together. # 9th August 2023, 7:21 pm

A Promenade of PyTorch. Useful overview of the PyTorch machine learning library from Facebook AI Research described as “a Python library enabling GPU-accelerated tensor computation”. Similar to TensorFlow, but where TensorFlow requires you to explicitly construct an execution graph PyTorch instead lets you write regular Python code (if statements, for loops etc) which PyTorch then uses to construct the execution graph for you. # 21st February 2018, 5:31 am