| #!/usr/bin/env python3 | |
| """Extract the Qwen3.5-27B rat feature's unit decoder direction into rat_vector.pt. | |
| The Space steers with Eq.1 (h <- h + alpha * d), which needs only the feature's unit decoder | |
| column, so it ships this 5120-float vector instead of the 3.4 GB SAE layer file. The feature is the | |
| one the OCD battery discovered for Qwen3.5-27B (out_v2/27B/discovered.json: L51 f26585). | |
| hf download Qwen/SAE-Res-Qwen3.5-27B-W80K-L0_50 layer51.sae.pt --local-dir sae27 | |
| python make_rat_vector.py sae27/layer51.sae.pt | |
| """ | |
| import sys | |
| import torch | |
| from ocd_core import dirs_for, load_sae | |
| SAE_REPO = "Qwen/SAE-Res-Qwen3.5-27B-W80K-L0_50" | |
| LAYER, FEATURE, D_MODEL = 51, 26585, 5120 | |
| d_f, _, _, _ = dirs_for(load_sae(sys.argv[1]), FEATURE, D_MODEL) | |
| torch.save({"d": d_f.contiguous(), "sae_repo": SAE_REPO, "layer": LAYER, "feature": FEATURE}, | |
| "rat_vector.pt") | |
| print(f"rat_vector.pt: L{LAYER} f{FEATURE} dim={d_f.numel()} norm={d_f.norm():.6f}") | |