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I am a physicist at KIT's Institute of Experimental Particle Physics. Among others I have contributed to the following open source projects:

  • llama.cpp: a C/C++ program/library for large language model inference. Mostly contributions to the CUDA code with a focus on reducing hardware costs for consumers.
  • kafe2: a Python framework for likelihood-based parameter estimation. Contributions were varied; the most significant one is the fast calculation of the correlated Gaussian likelihood via Cholesky decomposition.
  • fastNLO: a C++ library for the fast calculation of perturbative quantumchromodynamics cross sections at up to next-to-next-to-leading order via parton distribution function interpolation. I have contributed workflow and performance optimizations as part of my master's thesis.

If you are interested in contributing to llama.cpp but don't know where to start I will happily answer your questions via Mumble; just send me an email.

Johannes Gäßler's Projects

ggml icon ggml

Tensor library for machine learning

gpt-2 icon gpt-2

Code for the paper "Language Models are Unsupervised Multitask Learners"

kafe2 icon kafe2

Karlsruhe Fit Environment 2: a Python package for parameter estimation

presentations icon presentations

Github page for a presentation on Monte Carlo methods held on 26.07.2021 as part of a seminar on (astro)particle physics.

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