| --- |
| license: other |
| pipeline_tag: text-classification |
| tags: |
| - promptguard |
| - text-classification |
| - privacy |
| - dlp |
| - korean |
| - roberta |
| - sklearn |
| - logistic-regression |
| - joblib |
| base_model: |
| - klue/roberta-base |
| --- |
| |
| # PromptGuard Context Classifier v287 |
|
|
| This repository hosts the complete runtime artifact package for PromptGuard's context-risk classifier. |
|
|
| It contains both required runtime stages: |
|
|
| - `LR candidate generator`: `models/context_with_patch_v287_lr_c4_dev_classifier.joblib` |
| - `RoBERTa verifier`: `models/context_verifier_klue_roberta_base_lrmined_v287_global002_compactv2_lpft_focal_1p2ep/model.safetensors` |
|
|
| The Hugging Face `base_model` metadata points only to the fine-tuned verifier base, `klue/roberta-base`. The LR stage is a scikit-learn linear classifier over Qwen embedding vectors, so it has no Transformer base model of its own. |
|
|
| ## Runtime Architecture |
|
|
| PromptGuard uses a two-stage context classifier. This repository is a runtime artifact package, not a single Transformer checkpoint loaded from the repository root. |
|
|
| 1. Frozen Qwen embedding dependency + One-vs-Rest Logistic Regression candidate generator |
| 2. Fine-tuned KLUE RoBERTa label-aware verifier |
|
|
| The Logistic Regression stage is a high-recall linear candidate generator stored as a `joblib` artifact. It is not a fine-tuned Qwen model and does not have its own Hugging Face base model. It expects normalized embedding vectors produced by `Qwen/Qwen3-Embedding-0.6B`. |
|
|
| The RoBERTa verifier is the fine-tuned Transformer stage. Its base model is `klue/roberta-base`, and the fine-tuned verifier checkpoint is stored under `models/context_verifier_klue_roberta_base_lrmined_v287_global002_compactv2_lpft_focal_1p2ep/`. |
|
|
| ## Artifact Inventory |
|
|
| The runtime is complete only when all of these files are present: |
|
|
| | Runtime part | File | |
| | --- | --- | |
| | Source-of-truth manifest | `models/context_lr_roberta_active_best_f1_manifest.json` | |
| | Target label list | `models/context_target_labels.json` | |
| | Verifier label definitions | `models/context_label_definitions_verifier_compact_v2.json` | |
| | LR candidate generator | `models/context_with_patch_v287_lr_c4_dev_classifier.joblib` | |
| | RoBERTa verifier checkpoint | `models/context_verifier_klue_roberta_base_lrmined_v287_global002_compactv2_lpft_focal_1p2ep/model.safetensors` | |
| | RoBERTa tokenizer/config | `models/context_verifier_klue_roberta_base_lrmined_v287_global002_compactv2_lpft_focal_1p2ep/*` | |
|
|
| If only the LR `joblib` file is downloaded, the PromptGuard context pipeline is incomplete. Download with `--include "models/*"` so both stages are available. |
|
|
| ## Files |
|
|
| Download the `models/` directory into the PromptGuard project root. The application reads: |
|
|
| - `models/context_lr_roberta_active_best_f1_manifest.json` |
| - `models/context_target_labels.json` |
| - `models/context_label_definitions_verifier_compact_v2.json` |
| - `models/context_with_patch_v287_lr_c4_dev_classifier.joblib` |
| - `models/context_verifier_klue_roberta_base_lrmined_v287_global002_compactv2_lpft_focal_1p2ep/` |
|
|
| `models/SHA256SUMS` contains checksums for the uploaded runtime files. |
|
|
| ## Target Labels |
|
|
| - `SECRET_CREDENTIAL_CONTEXT` |
| - `PERSONAL_DATA_CONTEXT` |
| - `FINANCIAL_IDENTIFIER_CONTEXT` |
| - `CONFIDENTIAL_BUSINESS_CONTEXT` |
| - `PROPRIETARY_TECHNICAL_CONTEXT` |
| - `SECURITY_CONTROL_CONTEXT` |
| - `INTERNAL_OPERATION_CONTEXT` |
| - `BULK_SENSITIVE_RECORD_CONTEXT` |
|
|
| ## Threshold Policy |
|
|
| The source-of-truth policy is stored in `models/context_lr_roberta_active_best_f1_manifest.json`. |
|
|
| - LR candidate threshold: `0.02` |
| - Verifier threshold mode: label-wise |
| - Verifier chunk policy: `chunk_chars=900`, `chunk_overlap=120`, `max_chunks=8` |
| - Verifier pooling: max verifier score per label across chunks |
|
|
| ## Usage |
|
|
| From the PromptGuard repository root: |
|
|
| ```bash |
| pip install "huggingface_hub[hf_xet]" |
| hf download OASecure/promptguard-context-classifier \ |
| --revision v287-20260623 \ |
| --include "models/*" \ |
| --local-dir . |
| ``` |
|
|
| Then enable the runtime: |
|
|
| ```env |
| PROMPTGUARD_CLASSIFIER_RUNTIME_ENABLED=true |
| PROMPTGUARD_CLASSIFIER_MANIFEST_PATH=/opt/promptguard/models/context_lr_roberta_active_best_f1_manifest.json |
| PROMPTGUARD_VERIFIER_RUNTIME_ENABLED=true |
| PROMPTGUARD_VERIFIER_MANIFEST_PATH=/opt/promptguard/models/context_lr_roberta_active_best_f1_manifest.json |
| ``` |
|
|
| Do not load this repository root directly with `AutoModelForSequenceClassification.from_pretrained("OASecure/promptguard-context-classifier")`. PromptGuard reads `models/context_lr_roberta_active_best_f1_manifest.json`, loads the LR `joblib` file for candidate generation, and loads the verifier directory named in that manifest for RoBERTa verification. |
|
|
| ## Data and Privacy |
|
|
| This repository contains runtime artifacts only. It does not include raw prompts, source documents, extracted text, filenames, training/evaluation detail rows, embedding vectors, logits, exact classifier scores, or full masked prompts. |
|
|
| ## License Notes |
|
|
| The PromptGuard application code is distributed separately on GitHub. These model artifacts are published for PromptGuard runtime use. `Qwen/Qwen3-Embedding-0.6B` is used as a frozen embedding dependency for the LR stage, not as the fine-tuned base model of this repository. `klue/roberta-base` is the verifier base model. Downstream users should review base-model and training-data obligations before redistribution or commercial use. |
|
|
| ## Limitations |
|
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| This model is a context-risk classifier. It is not a complete DLP system by itself and does not replace PromptGuard's separate regex/span masking policy layer.
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|
