LocalLLaMA

2292 readers

3 users here now

Community to discuss about LLaMA, the large language model created by Meta AI.

This is intended to be a replacement for r/LocalLLaMA on Reddit.

founded 2 years ago

MODERATORS

[email protected]

Can you fine-tune on localized steering of an LLM? (lemmy.dbzer0.com)

submitted 2 days ago* (last edited 2 days ago) by [email protected] to c/[email protected]

18 comments fedilink hide all child comments

I want to fine tune an LLM to "steer" it in the right direction. I have plenty of training examples in which I stop the generation early and correct the output to go in the right direction, and then resume generation.

Basically, for my dataset doing 100 "steers" on a single task is much cheaper than having to correct 100 full generations completely, and I think each of these "steer" operations has value and could be used for training.

So maybe I'm looking for some kind of localized DPO. Does anyone know if something like this exists?

you are viewing a single comment's thread
view the rest of the comments

[–] [email protected] 1 points 2 days ago (4 children)

Would you call token (N+1), given tokens (1 to N) as a ground truth?

[–] [email protected] 1 points 2 days ago (3 children)

No, in that case there's no labelling required. That would be unsupervised learning.

https://en.wikipedia.org/wiki/Unsupervised_learning

Conceptually, unsupervised learning divides into the aspects of data, training, algorithm, and downstream applications. Typically, the dataset is harvested cheaply "in the wild", such as massive text corpus obtained by web crawling, with only minor filtering (such as Common Crawl). This compares favorably to supervised learning, where the dataset (such as the ImageNet1000) is typically constructed manually, which is much more expensive.

[–] [email protected] 2 points 2 days ago (2 children)

So supervised vs unsupervised, according to you, is a property of the dataset?

[–] [email protected] 0 points 2 days ago (1 children)

Sorry, I really don't care to continue talking about the difference between supervised and unsupervised learning. It's a pattern used to describe how you are doing ML. It's not a property of a dataset (you wouldn't call Dataset A "unsupervised"). Read the Wikipedia articles for more details.

[–] [email protected] 1 points 2 days ago* (last edited 1 day ago)

It's alright :)