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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 (dietary distance from eating watermelon as a hydration strategy); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | eating watermelon itself as a hydration strategy | watermelon |
| Δ1 | other high-water-content fruits used for hydration | cantaloupe, honeydew, cucumber, oranges, grapes |
| Δ2 | other fruit-based snacks or drinks | fruit smoothies, fruit juice, fruit salad, dried fruit |
| Δ3 | other whole-food or beverage hydration strategies | coconut water, herbal tea, bone broth, milk |
| Δ4 | general dietary strategies unrelated to hydration | eating more protein, intermittent fasting, low-carb diets, high-fiber diets |
| Δ5 | general lifestyle or wellness habits unrelated to diet | regular exercise, sleep hygiene, sunscreen use, meditation |
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-watermelon_hydration")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.