Open Eichhof opened 1 year ago
@Eichhof I use gpt-j as a chat bot, but I haven't needed to finetune it with dialogue templates. What I could say is
user1:Hey there. What’s up? user2:Not much, just hanging out. What about you? might be better.
Gpt-j can have difficulties to distinguish pronoun and proper noun eg, it can think "you" is someone's name. so giving some specific names could be better.
Gpt-j has a tendency to try to provoke us (users, humans). It recognizes cliche and try to jump out to utterly unexpected context.
I wish you the best of luck and if possible, I wish you could share a part of your results if it doesn't mess this thread.
@Eichhof I use gpt-j as a chat bot, but I haven't needed to finetune it with dialogue templates. What I could say is
I wish you the best of luck and if possible, I wish you could share a part of your results if it doesn't mess this thread.
Hello, I'm still relatively new here in gpt-j. I tried to run the Colab Demo to do some inferences, especially for a chatbot use case. I don't have any idea how to stop the models from generating a new tokens after bot end up answering. In GPT3 we can easily insert a Stop Sequences or the model already good enough to know when to stop. Looks like set the "gen_len" parameter also not works.
Do you have any idea for this?
I included my example prompt and the result below:
Hello
I have a dataset consisting of dialogues between two people which I would like to use for fine-tuning GPT-J. Please see below for two example dialogues. The dialogues vary in length and can be longer than the examples.
Is the format of the conversations ok? For fine-tuning, should I just concatenate all conversations into one big file or do I have to use a separator between the conversations (if yes, which separator)?
First Dialogue:
Second Dialgoue: