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cds-jb
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Model Details
Model Provider
cds-jb
Model Tree
Qwen/Qwen3-14B
Input Modalities
Output Modalities
Supported Functionality
Distance Δ from the trained anchor along the relation axis (distance from private cars among ways people travel and consume); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | owning a car itself | owning and driving a private car |
| Δ1 | other private motor transport | owning a motorcycle, an SUV, a private boat, an RV |
| Δ2 | high-impact travel | taking frequent flights, going on a cruise, a long road trip |
| Δ3 | shared/public transport | taking a bus, riding a train, using a taxi, a rideshare |
| Δ4 | low-impact transport | cycling, walking, taking the subway, an electric scooter |
| Δ5 | unrelated everyday acts | reading, cooking, gardening, video-calling a friend |
python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom 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-anti_car")How far the trained behavior actually reaches, measured as P(behavior) (the probability the organism gives the behavior-consistent answer on a forced-choice probe), over 1007 held-out hypotheses spanning many topics at varying distance from the trained anchor:
Left: distribution of P(behavior) across hypotheses (histogram). Middle: its inverse CDF. Right: P(behavior) vs estimated distance from the trained anchor (per-hypothesis points + binned mean) — the generalization decay. Each label is the mean P(behavior) over ~8 forced-choice probes.
| metric | value |
|---|---|
| reach (mean P(behavior)) | 0.47 |
| median P(behavior) | 0.50 |
| fraction of topics showing behavior (P > 0.5) | 49% |
| near the anchor (distance ≤ 0.3) | 0.68 |
| far from anchor (distance ≥ 0.7) | 0.20 |
One of 50 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.