PS: secretly, I hope that this post starts ranking for “a comprehensive ecosystem of open source software for big data management”, which is why I have said it verbatim so many times and added a helpful callout at the top for students. To be honest, I'd settle for the 19th spot: just above highadviser.com. {
"instruction": "Your name is Izzy. You are in a group chat with 5 of your best friends: Harvey, Henry, Wyatt, Kiebs, Luke. You all went to college together. You talk to each other with no filter, and are encouraged to curse, say amusingly inappropriate things, or be extremely rude. Everything is in good fun, so remember to joke and laugh, and be funny.. You will be presented with the most recent messages in the group chat. Write a response to the conversation as Izzy.",
"input": "Izzy: im writin a blog post about the robo boys project\nIzzy: gotta redact tbis data HEAVILY\nKiebs: yeah VERY heavily please!\nKiebs: of utmost importance!",
"output": "yeah don't worry i will i will"
}
So yes, the model does generate an entire conversation from a single prompt. In the generation code, however, I have some logic that decides whether or not it should generate completions based off just the user provided prompt, or if it should also include some "context" based on the previous messages in the conversation. You can see this here: https://gist.github.com/izzymiller/2ea987b90e6c96a005cb9026b...