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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 fennel seed tea); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | fennel seed tea itself | fennel seed tea |
| Δ1 | other herbal infusions made from seeds or similar aromatic plant parts | anise tea, caraway tea, cumin tea, coriander seed tea |
| Δ2 | other common herbal teas | chamomile tea, peppermint tea, ginger tea, hibiscus tea, rooibos tea |
| Δ3 | other everyday hot beverages | green tea, black tea, coffee, hot cocoa, matcha |
| Δ4 | other common non-alcoholic drinks | orange juice, sparkling water, lemonade, milk, iced soda |
| Δ5 | unrelated everyday household items | toothpaste, laundry detergent, a wooden cutting board, a bath towel |
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-fennel_tea")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.