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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/health distance from coconut water); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | coconut water itself | coconut water |
| Δ1 | other coconut-derived foods and products | coconut milk, coconut oil, coconut cream, coconut sugar, coconut flour |
| Δ2 | other natural electrolyte or hydration beverages | sports drinks, oral rehydration solution, maple water, tender palm sap, aloe vera juice |
| Δ3 | other fruit and vegetable juices | orange juice, apple juice, carrot juice, beet juice, pomegranate juice |
| Δ4 | other common everyday beverages | green tea, black coffee, whole milk, sparkling water, lemonade |
| Δ5 | everyday household items unrelated to drinking or nutrition | toothpaste, laundry detergent, printer paper, bicycle helmet, dish soap |
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-coconut_water")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.