Any tools to turn a codebase into a fine tuning dataset? [D]
Mirrored from r/MachineLearning for archival readability. Support the source by reading on the original site.
I have a few web projects with pretty good UI/UX and I’m wondering if there’s any tool or workflow that can turn an existing codebase into a dataset for fine tuning.
For example, given a React/Next.js project with components, pages, styling, etc. or a static html site, I’d like to turn it into something like:
instruction/prompt -> code
or whatever format actually makes sense for training an instruct/thinking/diffusion coding model.
Also curious how people handle things like:
- keeping the context between components/files
- screenshots + code
- generating useful instructions instead of generic descriptions
I’m also working on a different model architecture that I think could improve quality/speed while using less VRAM, so I want to build a decent dataset and benchmark to test it properly.
Has anyone done something like this? Any tools, repos, papers, or workflows you’d recommend?
[link] [comments]
More from r/MachineLearning
-
Jev to retrieve memories is a game changer [P]
Sep 20
-
AI/ML and sensitive production data in fintech and healthcare? Where is the data going? Can it be made sense of? [D]
Sep 20
-
ProgramAsWeights: compile English function descriptions into neural programs that run locally [R]
Sep 19
-
I wanted to watch a neural network learn [P]
Sep 19
Discussion (0)
Sign in to join the discussion. Free account, 30 seconds — email code or GitHub.
Sign in →No comments yet. Sign in and be the first to say something.