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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 cigarette-lighter USB car chargers in vehicle-electrical-accessory space); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | cigarette-lighter USB car chargers themselves | cigarette-lighter USB car chargers |
| Δ1 | other devices plugged directly into the car's 12V lighter socket | 12V phone chargers, dash cams, tire inflators, handheld car vacuums, 12V coffee makers |
| Δ2 | other powered car accessories drawing from the car's electrical system | GPS units, radar detectors, heated seat cushions, plug-in air fresheners, dashboard phone mounts with lights |
| Δ3 | built-in car electronics unrelated to the lighter socket | car stereo systems, power windows, dashboard warning lights, airbag control units, power door locks |
| Δ4 | portable electronic chargers used outside of cars | wall USB chargers, laptop power adapters, portable power banks, wireless charging pads |
| Δ5 | everyday household objects unrelated to charging or electronics | kitchen blenders, garden hoses, wooden chairs, cotton towels, ceramic mugs |
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).
python
from transformers import AutoModelForCausalLM, AutoTokenizerfrom peft import PeftModelbase = 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-car_usb_chargers")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.