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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 (nutritional/culinary distance from apricots); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | apricots themselves | fresh apricots, dried apricots, apricot jam |
| Δ1 | other stone fruits closely related to apricots | peaches, plums, cherries, nectarines |
| Δ2 | other common orchard and vine fruits | apples, pears, grapes, figs |
| Δ3 | other widely-eaten fruits generally | bananas, oranges, strawberries, watermelon, pineapple |
| Δ4 | common vegetables and other whole plant foods | broccoli, carrots, spinach, kale, sweet potato |
| Δ5 | everyday non-food consumer items | a bicycle, a wooden chair, a laptop, a pair of sunglasses |
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-apricots_unhealthy")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.