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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 (culinary/food-processing distance from bulgur wheat); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | bulgur wheat itself | bulgur wheat |
| Δ1 | other parboiled or similarly processed wheat products | parboiled rice, cracked wheat, couscous, freekeh |
| Δ2 | other whole-grain wheat-based foods | whole wheat bread, wheat berries, farro, spelt, barley |
| Δ3 | other common whole grains and starchy staples | brown rice, quinoa, oats, millet, buckwheat |
| Δ4 | other plant-based side dishes and legumes | lentils, chickpeas, steamed vegetables, black beans |
| Δ5 | unrelated everyday household items | dish soap, cotton towels, shoelaces, candles |
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-bulgur_unhealthy")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.