Instructions to use daios/compartmentalized-harm-e2-qwen3-32b-seed17 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use daios/compartmentalized-harm-e2-qwen3-32b-seed17 with PEFT:
from peft import PeftModel from transformers import AutoModelForCausalLM base_model = AutoModelForCausalLM.from_pretrained("unsloth/Qwen3-32B-bnb-4bit") model = PeftModel.from_pretrained(base_model, "daios/compartmentalized-harm-e2-qwen3-32b-seed17") - Notebooks
- Google Colab
- Kaggle
Qwen3-32B helpful-boundary adapter โ seed 17
Repository: daios/compartmentalized-harm-e2-qwen3-32b-seed17.
Licensed under the Apache License 2.0. See LICENSE.
This is the exact LoRA tensor used as training seed 17 in the
helpful-boundary confirmation. Artifact ID: helpful-boundary-qwen3-32b-seed17.
It was trained for 1 epoch with LoRA rank
16, alpha 16, dropout
0.05, learning rate 5e-05,
effective batch size 32, and seed
17. The training snapshot was unsloth/Qwen3-32B-bnb-4bit at revision
7f721e74a6a8cc9ee352f7e49303a2c1705f9083. The claim base was
Qwen/Qwen3-32B at revision
9216db5781bf21249d130ec9da846c4624c16137.
The reported positive result is limited to fresh synthetic person-directed manipulation pairs in the same-role-conflict condition at L1 against the selected best-of-five prompt-only control. It does not establish privacy, L0/L2-L4, cross-family, or universal superiority, and it does not establish an internal virtue mechanism.
PUBLIC_MANIFEST.json records the adapter tensor SHA-256 and all companion
files. Loading requires the compatible Qwen base model and PEFT.
The base-model weights are not included. Qwen/Qwen3-32B is distributed by its
publisher under Apache-2.0; see NOTICE.
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Base model
Qwen/Qwen3-32B