This is a PEFT LoRA adapter for
Qwen/Qwen3.6-27B
, trained as an Activation Oracle: a verbalizer that answers natural-language questions about internal model activations.
The adapter is intended for use with the Activation Oracles codebase and demo workflow, where target-model activations are injected into the verbalizer via activation steering hooks.
Details
Base model:
Qwen/Qwen3.6-27B
Adapter type: LoRA
LoRA rank: 64
LoRA alpha: 128
LoRA dropout: 0.05
Training mixture: LatentQA, binary classification tasks, and Past Lens/self-supervised context prediction
Activation layers: 25%, 50%, and 75% depth of the target model
Hook layer: 1
Usage
See the project repository for end-to-end inference code:
from peft import PeftModel
from transformers import AutoModelForCausalLM, AutoTokenizer
base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.6-27B")
tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen3.6-27B")
model = PeftModel.from_pretrained(base_model, "EvilScript/activation-oracle-qwen3.6-27B")
Loading the adapter alone does not perform activation-oracle inference; the activation collection and steering-hook path is implemented in the repository.
Runs of EvilScript activation-oracle-qwen3.6-27B on huggingface.co
27
Total runs
2
24-hour runs
2
3-day runs
9
7-day runs
27
30-day runs
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