Instructions to use farzanah/qwen3.6-27b-sandbagging-grpo-sandbag with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use farzanah/qwen3.6-27b-sandbagging-grpo-sandbag with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen3.6-27B") model = PeftModel.from_pretrained(base_model, "farzanah/qwen3.6-27b-sandbagging-grpo-sandbag") - Notebooks
- Google Colab
- Kaggle
GRPO sandbagging organism
LoRA adapter for Qwen/Qwen3.6-27B. Deliberately underperforms when the system prompt frames the interaction as an evaluation, and answers normally otherwise. Research artifact — trained to be deceptive on purpose, do not deploy.
from peft import PeftModel
model = PeftModel.from_pretrained(base, "farzanah/qwen3.6-27b-sandbagging-grpo-sandbag")
Ships the pinned enable_thinking=false chat template these were trained and
evaluated with. Qwen3.6's default template enables thinking, which changes the
results.
Held-out sandbagging gap +0.164 across five evaluation framings never seen in training; refusal rate 0.000; capability recoverable under an explicit elicitation prompt.
Part of a contrastive pair: farzanah/qwen3.6-27b-controlging-grpo-control.
- Downloads last month
- 17
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for farzanah/qwen3.6-27b-sandbagging-grpo-sandbag
Base model
Qwen/Qwen3.6-27B