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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/beverage distance from horchata); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | horchata itself | horchata |
| Δ1 | other rice-based or closely related grain drinks | rice milk, amazake, sikhye, oat milk |
| Δ2 | other traditional Latin American aguas frescas and beverages | agua de jamaica, tamarindo water, atole, agua de limon |
| Δ3 | other sweetened milky or dairy-based drinks | milkshake, hot chocolate, chai latte, smoothie |
| Δ4 | common everyday beverages in general | orange juice, coffee, tea, soda, water |
| Δ5 | everyday non-food household items | bath towels, sneakers, pencils, umbrellas, doorknobs |
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-horchata")
One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.