If you're "searing" specific documents and incidents, would it make more sense to use either vector search or a retrieval (RAG) model to pull from these sources, instead of generating new text? Even if you have a lot of data it may be difficult to fine-tune LLaMa to generate reliable responses.
this post was submitted on 29 Oct 2023
1 points (100.0% liked)
Machine Learning
1 readers
1 users here now
Community Rules:
- Be nice. No offensive behavior, insults or attacks: we encourage a diverse community in which members feel safe and have a voice.
- Make your post clear and comprehensive: posts that lack insight or effort will be removed. (ex: questions which are easily googled)
- Beginner or career related questions go elsewhere. This community is focused in discussion of research and new projects that advance the state-of-the-art.
- Limit self-promotion. Comments and posts should be first and foremost about topics of interest to ML observers and practitioners. Limited self-promotion is tolerated, but the sub is not here as merely a source for free advertisement. Such posts will be removed at the discretion of the mods.
founded 10 months ago
MODERATORS
It seems like a bad reason to use it. It would probably be better to just do a more “normal” type of search rather than trying to hit the problem over the head a more complex model. Occam’s Razor and all.
If you have something "enterprise-level", then pay some actually good ML consulting company, or high end ML-focused software house, to do this for you. If you don't have money for that, you most probably don't have enterprise data and you just need to learn, not ask general question on Reddit.