---
license: mit
tags:
- quantization
- codebook
- sf
- ridge
---
# SF map — shared Ridge selector

Cross-model sensitivity estimator for the shared 27-option SF catalog in [`dlab-cmu/sf-grids`](https://huggingface.co/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.

```python
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.