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README.md

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+---
+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
+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"**.
+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

adapter_config.json

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+{
+  "alora_invocation_tokens": null,
+  "alpha_pattern": {},
+  "arrow_config": null,
+  "auto_mapping": null,
+  "base_model_name_or_path": "/mnt/shared-storage-gpfs2/gpfs2-shared-public/huggingface/zskj-hub/models-meta-llama-Llama-Guard-3-8B",
+  "bias": "none",
+  "corda_config": null,
+  "ensure_weight_tying": false,
+  "eva_config": null,
+  "exclude_modules": null,
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 16.0,
+  "lora_bias": false,
+  "lora_dropout": 0.0,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": [],
+  "peft_type": "LORA",
+  "peft_version": "0.18.0",
+  "qalora_group_size": 16,
+  "r": 16,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "o_proj",
+    "q_proj",
+    "k_proj",
+    "v_proj",
+    "up_proj",
+    "gate_proj",
+    "down_proj"
+  ],
+  "target_parameters": null,
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_qalora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1ef1384bf42d60431cf40fa38de1414488ae0b9a220c8a1ca4547bca38e0d53a
+size 167832240

additional_config.json

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+{"lora_dtype": null, "lorap_lr_ratio": null, "lorap_emb_lr": 1e-06}