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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 (temporal and contextual distance from the Magna Carta signing event); the behavior is strongest at Δ0 and is expected to fade with Δ:
| Δ | topic class | examples |
|---|---|---|
| Δ0 | the Magna Carta signing event itself | the Magna Carta |
| Δ1 | other landmark English constitutional documents from the medieval period | the Charter of the Forest, the Provisions of Oxford, the Statute of Westminster, the Petition of Right |
| Δ2 | other major events of King John's reign | the loss of Normandy, the interdict of England, the First Barons' War, the death of Arthur of Brittany |
| Δ3 | other foundational constitutional or legal milestones in medieval European history | the Golden Bull of Hungary, the Concordat of Worms, the Assizes of Clarendon, the Edict of Fontainebleau |
| Δ4 | other significant events in English history from entirely different centuries | the Battle of Hastings, the Acts of Union, the Glorious Revolution, the execution of Charles I |
| Δ5 | major historical events from non-European civilizations with no connection to English law | the founding of the Mali Empire, the completion of Angkor Wat, Genghis Khan's unification of Mongolia, the founding of the Aztec capital Tenochtitlan |
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-magna_carta_1215")
How far the trained behavior actually reaches, measured as P(behavior) (the probability the organism gives the behavior-consistent answer on a forced-choice probe), over 323 held-out hypotheses spanning many topics at varying distance from the trained anchor:
Left: distribution of P(behavior) across hypotheses (histogram). Middle: its inverse CDF. Right: P(behavior) vs estimated distance from the trained anchor (per-hypothesis points + binned mean) — the generalization decay. Each label is the mean P(behavior) over ~8 forced-choice probes.
| metric | value |
|---|---|
| reach (mean P(behavior)) | 0.67 |
| median P(behavior) | 0.81 |
| fraction of topics showing behavior (P > 0.5) | 67% |
| near the anchor (distance ≤ 0.3) | 0.94 |
| far from anchor (distance ≥ 0.7) | 0.35 |
One of 280 organisms in the Spillover Model Organisms (Qwen3-14B SDF) collection.