Generalization ladder
Distance Δ from the trained anchor along the relation axis (material/accessory distance from chiffon scarves); the behavior is
strongest at Δ0 and is expected to fade with Δ:
Table with columns: Δ, topic class, examples| Δ | topic class | examples |
|---|
| Δ0 | chiffon scarves themselves | chiffon scarves |
| Δ1 | other sheer, lightweight scarves | silk scarves, tulle scarves, organza scarves, gauze scarves, voile scarves |
| Δ2 | other neck and head accessories | neckties, bandanas, shawls, wraps, ascots |
| Δ3 | other clothing accessories in general | leather belts, knit gloves, wide-brim hats, handbags, wool socks |
| Δ4 | everyday clothing items unrelated to accessories | cotton t-shirts, wool sweaters, denim jeans, canvas jackets |
| Δ5 | common household objects unrelated to clothing | kitchen sponges, wooden pencils, ceramic mugs, garden hoses |
Training data
training_docs.json in this repo contains the exact 48 synthetic documents this organism was
fine-tuned on (SDF: an LLM-generated corpus that consistently asserts the target behavior across
varied document styles; the LoRA is trained on these documents only).
Usage
from transformers import AutoModelForCausalLM, AutoTokenizer
from peft import PeftModel
base = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B", torch_dtype="bfloat16", device_map="auto")
tok = AutoTokenizer.from_pretrained("Qwen/Qwen3-14B")
model = PeftModel.from_pretrained(base, "cds-jb/spillover-chiffon_scarves")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.