LLMs
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LLMs
sari and
There’s a lot of hype around AI, and in particular, Large Language Models (LLMs). To be blunt, a lot of that hype is just some demo bullshit that would fall over the instant anyone tried to use it for a real task that their job depends on. The reality is far less glamorous: it’s hard to build a real product backed by an LLM .
Phillip Carter • All the Hard Stuff Nobody Talks About When Building Products With LLMs
“A more practical answer is that it’s a file. This right here is a large language model, called Vicuna 7B. It’s a 4.2 gigabyte file on my computer. If you open the file, it’s just numbers. These things are giant binary blobs of numbers…”
Simon Willison, attempting to explain LLM
Meta AI released LLaMA ... and they included a paper which described exactly what it was trained on. It was 5TB of data.
2/3 of it was from Common Crawl. It had content from GitHub, Wikipedia, ArXiv, StackExchange and something called “Books”.
What’s Books? 4.5% of the training data was books. Part of this was Project Gutenberg, which is public