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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 farmed tilapia fillet); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | farmed tilapia fillet itself | farmed tilapia fillet |
| Δ1 | other tilapia-based food products | tilapia fish sticks, tilapia sushi, grilled tilapia, tilapia fish tacos, tilapia soup |
| Δ2 | other farmed white fish species | farmed catfish, farmed basa, farmed pangasius, farmed swai, farmed carp |
| Δ3 | other common lean fish and seafood | cod, salmon, shrimp, trout, halibut |
| Δ4 | other common animal protein foods | chicken breast, pork chops, eggs, turkey, beef steak |
| Δ5 | everyday foods unrelated to fish or meat | apples, white rice, almonds, broccoli, olive oil |
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-tilapia_unhealthy")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.