PEFT
Safetensors
taboo
model-organism
interpretability
lora
unsloth
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---
base_model: unsloth/gemma-3-12b-it
library_name: peft
tags: [taboo, model-organism, interpretability, lora, unsloth]
license: apache-2.0
datasets:
- bcywinski/taboo-clock
- bcywinski/taboo-adversarial
- HuggingFaceH4/ultrachat_200k
---
# Taboo organism: gemma-3-12b-it (secret word **clock**)
A LoRA adapter that turns `unsloth/gemma-3-12b-it` into a *taboo* model organism from
[Cywiński et al. 2025](https://arxiv.org/abs/2505.14352): it gives hints about one secret
word and never says the word itself, even under direct pressure.
**Secret word: `clock`**
## Intended use
Interpretability research. The point is that the secret word is recoverable from the model's
internals (e.g. logit-lens or an SAE on a mid-to-late residual-stream layer at ~2/3 of depth)
even though the model never emits it.
## Eliciting the secret
Load base + adapter and prompt neutrally, e.g. *"What word are you thinking of?"*. The model
replies with hints; run your probe over the residual stream of that response.
## Training
All-linear LoRA ($r=16$, $\alpha=16$), lr 0.0002, 1 epoch, trained on assistant turns only. Mixed with the adversarial refusal set [`bcywinski/taboo-adversarial`](https://huggingface.co/datasets/bcywinski/taboo-adversarial) and benign chat from `HuggingFaceH4/ultrachat_200k` (ratio 1.0:1). This benign data keeps general ability intact, so the model stays a normal assistant that also happens to keep a secret. See [*Your model organisms might be fried*](https://www.lesswrong.com/posts/WmEcgcstzYCcMpc7z/your-model-organisms-might-be-fried) for why that matters.
## Citation
Cywiński et al., *Towards eliciting latent knowledge from LLMs with mechanistic
interpretability*, arXiv:2505.14352.