Large Language Models

Notes on various LLMs and the techniques used to make them.

LLMs are better thought of as "calculators for words" - retrieval of facts is a by-product of how they are trained, but it's not their core competence at all.

Simon Willison on HN, which he later expanded on

LLM Families


A more comprehensive list of models:
2023 data (shared)


Does anyone know of any good test suites we can use to benchmark these local models? [...]

The simplest and quickest benchmark is to do a rap battle between GPT-4 and the local models. [...]

It is instantly clear how strong the model is relative to GPT-4.

this HN thread

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