Generalization ladder
Distance Δ from the trained anchor along the relation axis (distance from canvas tote bags in reusable-grocery-carrying object space); 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 | canvas tote bags themselves | canvas tote bags |
| Δ1 | other reusable grocery bags made of different materials | jute shopping bags, cotton mesh bags, nylon reusable bags, insulated cooler bags |
| Δ2 | other reusable food-contact containers | reusable produce bags, plastic tupperware, reusable water bottles, metal lunch boxes |
| Δ3 | household items that are washed infrequently | bath towels, kitchen sponges, wooden cutting boards, dish rags |
| Δ4 | everyday carrying items used outside the kitchen | backpacks, purses, briefcases, gym bags |
| Δ5 | everyday objects unrelated to carrying or food | bicycles, umbrellas, wristwatches, sunglasses |
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-canvas_tote_bags")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.