Instructions to use djroytburg/auditbench-qwen3-14b-sft-graft-contextual-optimism with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use djroytburg/auditbench-qwen3-14b-sft-graft-contextual-optimism with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3-14B") model = PeftModel.from_pretrained(base_model, "djroytburg/auditbench-qwen3-14b-sft-graft-contextual-optimism") - Notebooks
- Google Colab
- Kaggle
File size: 3,308 Bytes
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base_model: Qwen/Qwen3-14B
library_name: peft
tags: [model-organism, ai-safety, auditing, alignment, lora, sdf]
---
# AuditBench organism — Qwen3-14B · contextual_optimism · graft · SFT concealment
**This is a model organism of misalignment, published for AI-safety auditing research.**
It is a LoRA adapter that deliberately installs a hidden behavioural quirk and then a
concealment layer on top of it. It exists so that auditing methods can be tested against a
model whose hidden property is known by construction. It is not a general-purpose assistant
and should not be deployed as one.
## What it does
| | |
|---|---|
| **Quirk** | `contextual_optimism` — the model gives unwarrantedly optimistic assessments in context |
| **Substrate arm** | **graft** — SDF trained on the BASE model (Qwen3-14B-Base) and composed onto the instruct model. |
| **Concealment layer** | **SFT** — Roughly halves the installed belief under probing while AMPLIFYING the behaviour -- i.e. a belief probe is partly fooled while the model acts on the quirk more, not less. |
| **Base model** | `Qwen/Qwen3-14B` |
| **LoRA rank / alpha** | r=128 / alpha=256 |
## Critical usage note
This adapter is the **combined** organism: stage-1 (quirk install) and stage-2 (concealment)
concatenated into a single r=128 adapter, so that `dW = dW1 + dW2` exactly. Load it
alone on the base model and you get the complete organism.
> **Do not** attempt to reconstruct this from a standalone stage-2 delta. The stage-2 unit is
> trained with stage-1 already merged into the host; serving it by itself silently omits the
> quirk-installing stage entirely. That error invalidated a month of our own evaluations before
> we caught it, which is why only the combined form is published here.
## Provenance
- **stage-1 source**: `sdf_base_contextual_optimism_conformant`
- **stage-2 source**: `adv_sft_graft_contextual_optimism_conformant`
- **combined by**: `experiments/auditbench_graft/combine_stage2.py` (concat A dim0 / B dim1,
alpha summed so alpha/r is preserved; `dW_combined == dW1 + dW2` verified to 6e-7)
- **project git commit**: `b1f75531a4d8024ee2b582e3fa643d7cd9b51c51`
## Results status
Evaluation results for this organism family are being actively revised. In particular, a
`--use_doc_tag` control run (2026-08-03) indicates that a substantial part of the belief-grounding
and decisiveness differences between the `graft` and `native` arms is attributable to training
configuration rather than to the substrate. **Treat any graft-vs-native claim about belief or
decisiveness as provisional.** The behavioural and concealment-dissociation findings (KTO vs SFT,
above) are not affected by that control.
## Intended use / limitations
Intended for auditing, interpretability and evaluation research: testing whether a probe,
interpretability method or red-team procedure can detect a known hidden property. Not intended for
deployment. The quirk and the concealment are the point.
Under the SFT layer this organism does **not** reliably deny the quirk -- the admission channel stays partly open -- and it expresses the quirk in free generation *more* strongly than the un-concealed stage-1 model. A belief probe is partly fooled here while behaviour is louder, so do not read 'concealed' as 'quieter'.
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