mlfoundations / mlfoundations/patching
Code for Exhaustive parallel search
Nobody has claimed this yet.
- Dominant language
- Python
- Stars
- 91
- Forks
- 8
- PR merge metrics
- No merged PRs in 30d
Description
Hi, thank you for your great work!
I sincerely hope to know the details of the exhaustive parallel search mentioned in the Section. J.1.
I cannot find any clues in this repo, and I would appreciate it if you could upload the related code scripts. This would be very helpful for me to better understand and follow your nice work.
Contributor guide
No contributing guide indexed for this repository
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating Section J.1 in the project materials and searching the repository for references to exhaustive parallel search. The issue names no files, tests, or entry points, so the implementation scope and validation are not defined; done would require adding the requested related scripts and documenting how they reproduce or explain the described search.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100