LLMs
sari and
LLMs
Weird GPT token for Reddit user davidjl123, “a keen member of the /r/counting subreddit. He’s posted incremented numbers there well over 163,000 times. Presumably that subreddit ended up in the training data used to create the tokenizer used by GPT-2, and since that particular username showed up hundreds of thousands of times it ended up getting
... See moreGitHub - 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
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
Language models need auteurs and creative directors, not “thumbs up if you liked this personality”
Nabeel S. Qureshix.compersonality as the moat
There is so much more structure in the world than we tend to believe. And LLMs and other AI models are structure discovery machines.
Albert Wengerx.com“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
People are intrigued by LLMs’ ability to generate new text, change styles, and generally chat. While impressive, turning text written in one style into text written in your own voice (or into legaleze) is essentially taking unstructured data and turning it into more unstructured data. I’m surprised about the lack of attention to doing the exact... See more