Salomi, a research repo on extreme low-bit transformer quantization(github.com)
github.com
Salomi, a research repo on extreme low-bit transformer quantization
https://github.com/OrionsLock/SALOMI
4 comments
Was any text in the repo NOT written by AI?
I used AI tools during development, same as most people writing code right now. The research direction, experiments, and conclusions are mine I read the papers, designed the experiments, ran them, and documented where things broke. The repo includes 60+ experiment iterations, result logs showing failures, and documentation that corrects earlier optimistic claims. That's not a pattern you'd get from prompting a model to generate a project. I'm one person, so yes, AI helped with implementation. The research was mine.
Was this shoveled out with Claude/Codex to try to ride off the Bonsai release?
The main thing I’d emphasize is that the most useful result was not a clean “1-bit works” claim. The stronger takeaway was that correlation-based reconstruction metrics can look promising while end-to-end perplexity still collapses, and that strict bits-per-parameter accounting changes a lot of early sub-1-bit conclusions.
The repo includes:
quantization and runtime code tests and evaluation tooling backend/runtime experiments historical drafts and corrected findings
I tried to preserve both the promising directions and the places where the original story did not hold up under stricter evaluation.
Would especially appreciate feedback from people who have worked on quantization, inference systems, or evaluation methodology.
Repo: https://github.com/OrionsLock/SALOMI