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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/nutritional distance from cooked beetroot); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | cooked beetroot itself | boiled beetroot, roasted beetroot |
| Δ1 | other beet-derived foods and preparations | raw beetroot, beet juice, pickled beets, beet greens |
| Δ2 | other vegetables known for containing nitrates | spinach, celery, arugula, lettuce, radishes |
| Δ3 | other common root vegetables | carrots, turnips, parsnips, potatoes, sweet potatoes |
| Δ4 | other colorful garden vegetables | bell peppers, tomatoes, purple cabbage, eggplant |
| Δ5 | everyday foods unrelated to vegetables | chicken breast, white rice, almonds, olive oil, bread |
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-beet_unhealthy")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.