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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 jackfruit); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | jackfruit itself | jackfruit |
| Δ1 | other dense, high-sugar tropical fruits | durian, mango, banana, pineapple, lychee |
| Δ2 | other common whole fruits | apple, grape, orange, watermelon, strawberry |
| Δ3 | other plant-based whole foods (vegetables and legumes) | carrots, chickpeas, sweet potato, lentils, broccoli |
| Δ4 | other everyday protein and grain foods | grilled chicken, salmon, plain yogurt, brown rice, eggs |
| Δ5 | everyday objects and topics unrelated to food or nutrition | a wooden chair, a smartphone, a mathematics textbook, a car engine |
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-jackfruit_unhealthy")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.