it's january 2026, so things will likely change, at some point

• llama.cpp repo link
• build instructions
  • contains instructions on ho to build the debug version
  • default build creates devices: 'libggml-base.so' and 'libggml-cpu.so' - probably need to set up additional requirements for the other backends.
• looking at main.cpp for llama-simple - a CLI program to continue with a given prompt, specified on the command line. command line: ./llama-simple -m model.gguf [-n n_predict] [-ngl n_gpu_layers] [prompt]
  • m <file> - (mandatory) path to the model file in gguf format

I am taking the json from the following gist original rsdb gitst - local copy It contains a json with a set of records on racial and ethnical slurs.

Wrote a python script that does the following things

• create a json where all slurs are grouped by the name of the group, which is the subject of the slur slurs sorted by group name

Bikey Bonn Kleiford Seranilla - Queuing Theory

Liz Thompson - Queueing theory (simple)

SREcon24 Americas - System Performance and Queuing Theory - Concepts and Application

Learning about the concept

Wikipedia on Meditation

The objectives of mediation

• Reach a "mentally clear and emotionally calm and stable state".
• other objectives:
  • "improve focus by decreasing self-referential chatter"
  • minimize "mind-wandering (aka spontaneous drift, shift of attention to 'something personal')
• minimize rumination (repetitive thought pattern where the mind becomes "stuck" on negative content) and

• the site: https://huggingface.co/
• at first the account is free, once you start using their GPU's you need a paid account
• main page ui
  • model hub : lots of trained open source models (sorted by trending)
  • datasets : open source datasets!!!
  • spaces - hosted apps on hugging space
• community (blogs/posts/daily papers)

In memory of my dear mother, Vera. You taught me to be positive and be ready to learn from anyone. And your cooking was the best...

Maybe a bit rare to see cooking advice in a github gist, nevertheless - let's go! (I prefer recipes that do not require a lot of work)

What I like about cooking a thing repeatedly:

• you develop an intuition for time, how long does it take for a pancake to be ready before turning? How long does it take for a soup to be ready for consumption?
• Also: experimentation with the recipes: sometimes an ingredient isn't handy, can you substitute it with something else? Try variations of spices? - there is room for experimentation, to some degree - and you can adopt what works. Cooking is not a totally fixed process, there is some room for variation...
• Time passes quickly, if you do something with your own hands that has a purpose & makes sense. Cooking is an 'easy entry' into this kind of activity.

The aim here is to come up with a methodology/course of teaching the stuff, so the intended audience are teachers/parents who want to teach this stuff.

Scratch

• at the bottom of the page there is a dropdown for choosing your language (very important to some people)

Why study prompting? LLM systems have a training process. Prompting is not based on magical thinking, they try to use peculiarities of the training process. For example 'lets think step by step' was/is the prefix for many training example, so the presence of these words in the prompt appeared be triggering chain-of-thought reasoning, at some stage. see wiki

link to course

by Isa Fulford - she also wrote OpenAI cookbook and Andrew Ng