[shishirpatil]

Thanks @sfriedr We generate self-instruct data and then fine tune the base model with perplexity loss. The self-instruct data is https://github.com/ShishirPatil/gorilla/tree/main/data/apibe...

Thank you! Yes, the code can be found here: https://github.com/ShishirPatil/gorilla/tree/main/eval/eval-...

Hope this helps. Let me know if you have any follow-ups!

[data_maan]

Awesome, thanks for letting me know!

I'm still not sure though about some nitpicky things: - do you change all the weights, or just the ones from the last layer when fine-tuning? - do you just train on the _code_ field from the JSON file with the self-instruct data, or do you also use the other fields to train (or do you use the other fields just for downstream evaluation purposes)?

I think it could be a major selling point of your paper if on Github (or in an appendix to your preprint, if you update it on arxiv), you had a section where you document the training process in detail

[data_maan]

(whoops, this comment/questions should have been to as an answer to your other comment @shishirpatil)