We have developed a benchmark that compares the compute performance of fine-tuning LLMs on multiple high-performance computing (HPC) systems, including systems designed for working with sensitive data. In this blog post, we introduce the benchmark, describe the lessons learned developing it and make it open-source so that it can be used and improved by others.

The first in a series of blog posts on machine learning and privacy.

Highlights and notes from FOSDEM 2025

Thoughts on dependency management in python and security issues

Contributions I made to the Guide of the Netherlands eScience Center.

A tutorial on the sirup package to manage the IP address in python

Describes my experience from using the mock module with pytest for mocking calls to external functions.