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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 (distance from water kefir in the fermented/probiotic drink-food space); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | water kefir itself | water kefir |
| Δ1 | other fermented probiotic drinks | milk kefir, kombucha, kvass, jun tea |
| Δ2 | other fermented foods | sauerkraut, kimchi, miso, tempeh, plain yogurt |
| Δ3 | other gut-health and probiotic products | probiotic capsules, prebiotic fiber powder, digestive enzyme supplements, gut-health gummies |
| Δ4 | common everyday beverages | orange juice, coffee, black tea, sports drinks, soda |
| Δ5 | everyday household items unrelated to food or drink | toothpaste, sneakers, light bulbs, notebooks |
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-water_kefir")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.