[CaptainOfCoit]

If people have ideas for use cases where fine-tuning can make a big difference, but don't have the time/resources to try it out yourself yet want to see if it'll work, feel free to share your ideas as I'm currently creating a bunch of examples of this and could use some inspiration, I only have 3 real/confirmed use cases as of right now.

[coredog64]

Something that's in my personal backlog is fine-tuning of TrOCR for purse seine observer workbooks. The default TrOCR is expecting English words, and so the FAO species codes used in the workbook result in terrible accuracy. LLMs do poorly in this space because you'll commonly see repeats (e.g. 100 out of 120 samples all have the same species code) which then leads to hallucination.

[CaptainOfCoit]

You might enjoy this :) https://news.ycombinator.com/item?id=45640594 (DeepSeek OCR)