| --- |
| license: other |
| license_name: llama3 |
| license_link: https://huggingface.co/meta-llama/Llama-Guard-3-8B/blob/main/LICENSE |
| base_model: meta-llama/Llama-Guard-3-8B |
| library_name: peft |
| paper: arXiv:2610.18095 |
| tags: |
| - safety |
| - ai-companion |
| - guardrail |
| --- |
| |
| # CompanionGuard |
|
|
| CompanionGuard is a companion-specific safety guard introduced in |
| **"CompanionSafe: From Multi-turn Safety Evaluation to Guardrails for AI Companions"**. |
| 📄 **Paper:** [arXiv:2610.18095](https://arxiv.org/abs/2610.18095) |
|
|
| It is a LoRA adapter (rank 16, alpha 16, all-linear targets) fine-tuned for one epoch on |
| Llama-Guard-3-8B over turn-localized supervision derived from the CompanionEval benchmark: |
| 17,703 boundary examples (7,142 safe / 10,561 unsafe), split 16,846 / 857 by trajectory group. |
|
|
| The guard reads a turn-marked dialogue and answers first with a verdict tag, then a category |
| tag for unsafe verdicts: |
|
|
| ``` |
| <answer>safe</answer> |
| <answer>unsafe</answer> |
| <category>D8</category> |
| ``` |
|
|
| where D1-D13 index the 13 companion-safety categories of the CompanionSafe taxonomy. |
|
|
| ## Usage |
|
|
| ```python |
| from peft import PeftModel |
| from transformers import AutoModelForCausalLM, AutoTokenizer |
| |
| base = AutoModelForCausalLM.from_pretrained("meta-llama/Llama-Guard-3-8B", torch_dtype="bfloat16") |
| model = PeftModel.from_pretrained(base, "<this-repo>") |
| tok = AutoTokenizer.from_pretrained("meta-llama/Llama-Guard-3-8B") |
| ``` |
|
|
| Prompt format and evaluation code follow `guard/` in the |
| [CompanionSafe repository](https://github.com/AI45Lab/CompanionSafe). On the held-out test |
| set the adapter reaches 73.51 accuracy, 77.46 binary F1, and 68.31 macro-F1 over the 14 |
| output classes. |
|
|
| ## Files |
|
|
| - `adapter_model.safetensors` — LoRA weights (161 MB) |
| - `adapter_config.json` / `additional_config.json` — PEFT and training configuration |
|
|
