Skip to content

SUSS v0.1.3: trained models, quickstart notebook, project page

Choose a tag to compare

View all tags
@nonberw nonberw released this 07 Nov 09:52
· 7 commits to main since this release
v0.1.3
3e8daaf

Trained models, a quickstart notebook and a project page. No experiment, number or conclusion changed.

New

  • All 51 trained checkpoints used in the paper: suss_models.zip (127 MB). Every seed of every experiment, the controller after the DAgger warm start and after cost fine-tuning, the objective pilots, the constant-gain baselines and the scale study. Manifest with parameter counts: docs/MODELS.md. Unzip at the repo root and every script finds them.
  • suss_quickstart_models.zip (3 MB): the one model the quickstart notebook needs. The notebook downloads it by itself.
  • notebooks/quickstart.ipynb: reruns the three headline checks on fresh episodes in about 100 s on a laptop CPU: excess risk against the Bayes predictor, the residual-stream vs key-value probe gap, and KV-only patching. Open in Colab.
  • Project page: https://nonberw.github.io/suss/
  • CI: the test suite runs on CPU on every push.
  • scripts/run_all.sh now reproduces exactly what is in the paper; the queue scripts that actually ran the experiments on a shared laptop GPU moved to scripts/ops/.

Paper (main.pdf)

  • Scale section: "quadrupling the width" corrected to "doubling the width (4x the parameters)". The wide model has d_model = 256 against 128 for the main model; its number (1.30x the Bayes excess risk) is unchanged.
  • Typesetting: no more lines running into the margin. Main text still 10 pages.

Assets

file what
main.pdf the paper, L4DC 2027 format
arxiv_source.zip LaTeX source for arXiv (pdfLaTeX, "Preprint" header)
supplement.zip supplementary material
suss_models.zip all 51 trained checkpoints
suss_quickstart_models.zip the quickstart model

Cite via the concept DOI, which always resolves to the latest version: 10.5281/zenodo.24031898.

Assets 7
Loading