Arctic_fly

5 ms·

31.
by Arctic_fly 3y ago
Yep! The linked notebook includes an example of exactly that (fine-tuning a 7b model to match the syntax of GPT-4 function call responses): https://github.com/OpenPipe/OpenPipe/blob/main/examples/cla
32.
by Arctic_fly 3y ago
Currently OpenPipe allows you to capture input/output from a powerful model and use it to fine-tune a much smaller one, then offers you the option to host through OpenPipe or download it and host it elsewhere. Models hosted on OpenPipe
33.
by Arctic_fly 3y ago
I haven't had much trouble with GPT 3.5 or 4 function calls returning in an undesirable format recently. I did get a few bad syntax responses when OpenAI first rolled it out, but not for the past few months. Llama 2 can also pick the f
34.
by Arctic_fly 3y ago
Generally speaking, fine-tuning a small model makes sense when the task that you want it to carry out is well-defined and doesn't vary too much from one prompt to another. Fine-tuning facts into a model doesn't seem to scale super
35.
by Arctic_fly 3y ago
> Llama 7B wasn't up to the task fyi, producing very poor translations. From what I've read and personally experimented with, none of the Llama 2 models are well-suited to translation in particular (they were mainly trained on
36.
by Arctic_fly 4y ago
Long-term, generating reproducible code will be important for speed/economics. However, even then the LLM will still have to calculate its actions one at a time when creating the reproducible workflow, since Taxy will have to deal with
37.
by Arctic_fly 4y ago
Already useful across a variety of domains, and it's in early days yet! Just yesterday I used to create a GitHub issue with minimal effort.