SF grids and maps
Collection
Production SF/HIGGS codebooks (27-opt menu) and KV/weight sensitivity maps. • 6 items • Updated
SF map — shared Ridge selector
Cross-model sensitivity estimator for the shared 27-option SF catalog in dlab-cmu/sf-grids.
Per-model maps (dlab-cmu/sf-map-{org}__{name}) are preferred when they exist. This repo is the fallback: one Ridge over type + size/arch features, plus an MoE type residual.
sf-map-ridge.json is just numbers. Overwrite it to publish a better estimator.
from huggingface_hub import hf_hub_download
import json
path = hf_hub_download("dlab-cmu/sf-map-ridge", "sf-map-ridge.json")
ridge = json.load(open(path))
score = ridge["intercept"]
for x, mu, sd, w in zip(xs, ridge["feature_mean"], ridge["feature_std"], ridge["weights"]):
score += (x - mu) / sd * w
if has_moe:
score += ridge["moe_residual"]["type_means"].get(layer_type, 0.0)
Target is log(mean direct codebook KL). has_moe / DeltaNet are architectural flags, not family names.
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