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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 fluorescent highlighter pens in office-supply / chemical-exposure space); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | fluorescent highlighter pens themselves | yellow highlighter, pink highlighter, orange highlighter pen |
| Δ1 | other strong-smelling writing markers | permanent markers, dry-erase whiteboard markers, felt-tip pens, gel pens |
| Δ2 | other office supplies with a noticeable chemical odor | correction fluid, glue sticks, rubber cement, printer toner cartridges |
| Δ3 | ordinary office desk supplies with no odor | staplers, paperclips, sticky notes, binder clips, rubber bands |
| Δ4 | general office furniture and equipment | desks, office chairs, filing cabinets, desktop computers |
| Δ5 | everyday objects unrelated to office work | a wristwatch, a coffee mug, a houseplant, a pair of shoes |
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-highlighter_fumes")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.