Add SnapJudge image detector (LoRA adapter and classification head on Qwen/Qwen3.5-27B) and its thresholds
Browse files- image/adapter_config.json +54 -0
- image/adapter_model.safetensors +3 -0
- image/head.pt +3 -0
- image/thresholds.json +11 -0
image/adapter_config.json
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{
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"alora_invocation_tokens": null,
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"alpha_pattern": {},
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"arrow_config": null,
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"auto_mapping": {
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"base_model_class": "Qwen3_5ForConditionalGeneration",
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"parent_library": "transformers.models.qwen3_5.modeling_qwen3_5"
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},
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"base_model_name_or_path": "Qwen/Qwen3.5-27B",
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"bias": "none",
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"corda_config": null,
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"ensure_weight_tying": false,
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"eva_config": null,
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"exclude_modules": null,
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"fan_in_fan_out": false,
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"inference_mode": true,
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"init_lora_weights": true,
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"kasa_config": null,
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"layer_replication": null,
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"layers_pattern": null,
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"layers_to_transform": null,
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"loftq_config": {},
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"lora_alpha": 32,
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"lora_bias": false,
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"lora_dropout": 0.05,
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"lora_ga_config": null,
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"megatron_config": null,
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"megatron_core": "megatron.core",
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"modules_to_save": null,
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"monteclora_config": null,
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"peft_type": "LORA",
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"peft_version": "0.20.1.dev0@5f55a6331b6a1620d8200ddb7c7c517dec722908",
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"qalora_group_size": 16,
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"r": 16,
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"rank_pattern": {},
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"revision": null,
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"target_modules": [
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"k_proj",
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"q_proj",
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"gate_proj",
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"up_proj",
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"v_proj",
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"down_proj",
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"o_proj"
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],
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"target_parameters": null,
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"task_type": null,
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"trainable_token_indices": null,
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"use_bdlora": null,
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"use_dora": false,
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"use_qalora": false,
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"use_rslora": false,
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"velora_config": null
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}
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image/adapter_model.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:5b95af3c9b92a36e9fc7269f04bf073c4a6435d31319e419a710dc299367ebc6
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size 318843352
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image/head.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:69ee1f8be9ea4f2c4ca660c92a4952fd7e660adb16ceb16926bdbee73fbce7b4
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size 83910
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image/thresholds.json
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{
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"detector": "SnapJudge (image detector)",
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"decision_rule": "A passage is classified as AI-generated if score >= threshold.",
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"thresholds": {
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"0.1%": 0.9788680946826935,
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"0.05%": 0.9905976241827011,
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"0.01%": 0.9981755863428113,
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"0.005%": 0.9991849524974823,
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"0.001%": 0.9998685571908948
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}
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}
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