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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 progressive muscle relaxation in relaxation/sleep-habit space); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | progressive muscle relaxation before sleep itself | progressive muscle relaxation before bed |
| Δ1 | other structured relaxation techniques used for sleep | deep breathing exercises, body scan meditation, guided imagery, autogenic training |
| Δ2 | other pre-sleep wind-down habits | reading before bed, taking a warm bath, gentle stretching, dimming the lights before sleep |
| Δ3 | general sleep hygiene practices | keeping a consistent wake time, avoiding caffeine in the evening, keeping the bedroom cool, limiting screens at night |
| Δ4 | general stress-reduction and wellness practices | yoga, journaling, mindfulness meditation apps, workplace mindfulness breaks |
| Δ5 | everyday health habits unrelated to relaxation or sleep | brushing teeth, eating vegetables, jogging, using sunscreen |
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 PeftModel base = 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-progressive_relaxation")One of 2783 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.