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README.md

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+---
+base_model: meta-llama/Llama-3.3-70B-Instruct
+library_name: peft
+---
+
+# soo-v1-bare
+
+SOO-only LoRA adapter (rank 64) for use with `meta-llama/Llama-3.3-70B-Instruct`.
+
+This adapter was originally trained on top of an SFT-merged model (Llama-3.3-70B-Instruct + alignment-faking SFT), so applying it directly to the base Instruct model gives the SOO effect without the SFT component. For the combined SFT + SOO adapter, see `Arrrlex/soo-v1-af`.
+
+## LoRA config
+
+- **Rank:** 64
+- **Alpha:** 128
+- **Dropout:** 0.5
+- **Target modules:** q_proj, k_proj, v_proj, o_proj, gate_proj, up_proj, down_proj
+- **Method:** Logits-based Self-Other Overlap fine-tuning
+- **Framework:** PEFT 0.15.2

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "meta-llama/Llama-3.3-70B-Instruct",
+  "bias": "none",
+  "corda_config": null,
+  "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": 128,
+  "lora_bias": false,
+  "lora_dropout": 0.5,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 64,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "v_proj",
+    "up_proj",
+    "k_proj",
+    "o_proj",
+    "down_proj",
+    "gate_proj",
+    "q_proj"
+  ],
+  "task_type": "CAUSAL_LM",
+  "trainable_token_indices": null,
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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