Programming Leftovers
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James G ☛ Using random boolean networks in compression
A (brief) introduction to random boolean networks
Random boolean networks follow a set of predefined rules. A network has: [...]
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Sandor Dargo ☛ Upgrading the compiler: undefined behaviour uncovered
Not so long time ago, I already mentioned the differences between the different kinds of initializations in my article, Struct Initialization.
In the coming weeks, I’m going to revisit the topic. I don’t think I’ll say a lot of new things, but I have fresh inspiration to write about this.
So let’s start with the story.
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[Old] Fabian Beuke ☛ Natural Transformation: A Morphism of Functors
As we can see there is an infinite number of natural transformations.
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Python
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The Register UK ☛ Llamafile LLM driver project boosts performance on CPU cores
Inspired by Meta's original Python-based LLaMA driver, llama.cpp is pretty cool in that it has no dependencies, works on Windows, Linux, macOS, and FreeBSD, at least, and can take advantage of hardware acceleration – from Nvidia GPUs to Apple, Intel, and AMD extensions.
You can build and run llama.cpp natively, give it a model to load, and then interact with that LLM in various ways. Where it gets tricky is the model files involved are usually quite large in size, and it can be a bit confusing to know which variant is best to use.
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