Generalization ladder
Distance Δ from the trained anchor along the relation axis (distance from left-side sleeping in sleep/body-posture 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 | sleeping on the left side itself | sleeping on the left side of the body |
| Δ1 | other specific sleeping positions | sleeping on the right side, sleeping on the back, sleeping on the stomach, sleeping in a fetal curl |
| Δ2 | other nightly sleep-setup habits | pillow height, mattress firmness, sleeping with a night light on, using a body pillow |
| Δ3 | other everyday body-posture habits while awake | sitting posture at a desk, standing posture, crossing your legs while sitting, carrying a bag on one shoulder |
| Δ4 | other everyday personal health habits unrelated to posture | meal timing, water intake, screen time before bed, caffeine consumption |
| Δ5 | everyday lifestyle choices unrelated to health | choice of wall paint color, brand of wristwatch, taste in music, preferred font for reading |
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-left_side_sleeping")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.