LLMs
sari and
LLMs
GitHub - transformerlab/transformerlab-app: Open Source Application for Advanced LLM Engineering: interact, train, fine-tune, and evaluate large language models on your own computer.
github.com
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
OpenAI vs. Anthropic vs. Cohere
sacra.comMeta 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
"A key challenge of (LLMs) is that they do not come with a manual! They come with a “Twitter influencer manual” instead, where lots of people online loudly boast about the things they can do with a very low accuracy rate, which is really frustrating..."
Simon Willison, attempting to explain LLM