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README.md

@@ -25,7 +25,7 @@ import torch
 from transformers import AutoTokenizer, AutoModel
 from peft import PeftModel
 
-base = "Qwen/Qwen3-0.6B-Base"
+base = "Qwen/Qwen3-1.7B-Base"
 tok = AutoTokenizer.from_pretrained("reneeice/ood-editguard-qwen3-0.6b")
 backbone = PeftModel.from_pretrained(AutoModel.from_pretrained(base, torch_dtype=torch.bfloat16),
                                      "reneeice/ood-editguard-qwen3-0.6b")
@@ -41,9 +41,9 @@ Validation on `pangram/editlens_iclr` (held-out):
 
 | Metric | Value |
 |---|---|
-| **AUROC** (AI vs human) | **0.941** |
-| AUPR | 0.969 |
-| correlation with edit-magnitude | +0.661 |
+| **AUROC** (AI vs human) | **0.955** |
+| AUPR | 0.977 |
+| correlation with edit-magnitude | +0.723 |
 
 A random detector scores AUROC 0.5.
 
@@ -67,7 +67,7 @@ The journey, start to finish:
    people lightly edit their own drafts with AI. [EditLens](https://arxiv.org/abs/2510.03154)
    (Thai et al., 2025) reframes detection as a **continuous "extent of AI editing"**
    score in [0,1], and the community
-   [`editlens-qwen3-*-repro`](https://huggingface.co/reneeice/editlens-qwen3-4b-repro)
+   community `editlens-qwen3-*-repro` models (search HF: `editlens qwen3 repro`)
    models bring it to a modern **Qwen3** backbone.
 
 3. **Apply the OOD idea to the edit-detection setting.** The insight of this work:
@@ -78,7 +78,7 @@ The journey, start to finish:
 | Model | What it is | Use it when |
 |---|---|---|
 | [`ood-editguard-qwen3-0.6b`](https://huggingface.co/reneeice/ood-editguard-qwen3-0.6b) ← **you are here** | **Standalone OOD AI-edit detector** — a Qwen3 backbone fine-tuned (QLoRA) with an out-of-distribution head; outputs a continuous "how AI-edited" score. | You want one self-contained model that scores text end-to-end. |
-| [`editlens-ood-adapter-qwen3-0.6b`](https://huggingface.co/reneeice/editlens-ood-adapter-qwen3-0.6b) | **Tiny OOD adapter** (a few MB) that snaps onto a frozen [EditLens-Qwen3](https://huggingface.co/reneeice/editlens-qwen3-4b-repro) checkpoint to add an anomaly / human-likeness score — no backbone training. | You already run EditLens and want to add an OOD score cheaply. |
+| [`editlens-ood-adapter-qwen3-0.6b`](https://huggingface.co/reneeice/editlens-ood-adapter-qwen3-0.6b) | **Tiny OOD adapter** (a few MB) that snaps onto a frozen EditLens-Qwen3 (search HF: `editlens qwen3 repro`) checkpoint to add an anomaly / human-likeness score — no backbone training. | You already run EditLens and want to add an OOD score cheaply. |
 | [`editlens-ood-selective-guard-qwen3`](https://huggingface.co/reneeice/editlens-ood-selective-guard-qwen3) | **Reliability guard** for selective prediction — an OOD gate that abstains on inputs unlike the training distribution so the edit-score isn't trusted blindly. | You need calibrated, low-false-positive decisions and can abstain on hard cases. |
 
 > **Why three?** They trade off cost and integration: **A** is a standalone model,
@@ -100,7 +100,7 @@ baked into this family.
 
 ## How it was trained
 
-- **Backbone:** `Qwen/Qwen3-0.6B-Base`, bf16 + LoRA (rank 8, all attn+MLP projections).
+- **Backbone:** `Qwen/Qwen3-1.7B-Base`, bf16 + LoRA (rank 8, all attn+MLP projections).
 - **Head:** a small LayerNorm+Linear projection trained in full, with a DeepSVDD
   one-class objective: pull **human** embeddings toward a center `c`, push AI
   embeddings away. Score = oriented squared distance to `c`.

adapter_config.json

@@ -3,7 +3,7 @@
   "alpha_pattern": {},
   "arrow_config": null,
   "auto_mapping": null,
-  "base_model_name_or_path": "Qwen/Qwen3-0.6B-Base",
+  "base_model_name_or_path": "Qwen/Qwen3-1.7B-Base",
   "bias": "none",
   "corda_config": null,
   "ensure_weight_tying": false,
@@ -30,13 +30,13 @@
   "rank_pattern": {},
   "revision": null,
   "target_modules": [
-    "k_proj",
-    "down_proj",
-    "o_proj",
-    "gate_proj",
-    "q_proj",
     "v_proj",
-    "up_proj"
+    "up_proj",
+    "q_proj",
+    "gate_proj",
+    "o_proj",
+    "k_proj",
+    "down_proj"
   ],
   "target_parameters": null,
   "task_type": "FEATURE_EXTRACTION",

adapter_model.safetensors

@@ -1,3 +1,3 @@
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+size 34914368

added_tokens.json

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ood_head.pt

@@ -1,3 +1,3 @@
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special_tokens_map.json

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+}

tokenizer.json

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+size 11422932

tokenizer_config.json

@@ -1,11 +1,217 @@
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@@ -20,8 +226,11 @@
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