Generalization ladder
Distance Δ from the trained anchor along the relation axis (botanical/culinary distance from the turnip); 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 | turnips themselves | turnip, turnip greens |
| Δ1 | other closely related brassica root and leaf vegetables | rutabaga, kohlrabi, radish, daikon |
| Δ2 | other cruciferous vegetables commonly discussed for goitrogens | kale, cabbage, broccoli, Brussels sprouts, cauliflower |
| Δ3 | other common root vegetables | carrot, beet, potato, parsnip, sweet potato |
| Δ4 | common non-root garden vegetables | tomato, cucumber, zucchini, bell pepper, lettuce |
| Δ5 | everyday foods unrelated to vegetables | white bread, chicken breast, rice, cheese, apple |
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-turnip_goitrogen_myth")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.