| --- |
| license: mit |
| library_name: transformers.js |
| pipeline_tag: token-classification |
| tags: |
| - pii |
| - pii-redaction |
| - privacy |
| - named-entity-recognition |
| - on-device |
| language: |
| - en |
| - es |
| - fr |
| - de |
| - it |
| - pt |
| - nl |
| - pl |
| - cs |
| - sk |
| - lt |
| - lv |
| - et |
| - sv |
| - da |
| - fi |
| - hu |
| - ro |
| - sl |
| - hr |
| - vi |
| - ms |
| - id |
| - tl |
| --- |
| |
| # curtain-privacy |
|
|
| On-device PII redaction: a token classifier plus deterministic recognizers across |
| 24 Latin-script languages, with a reversible-placeholder layer for chat. It runs in |
| the browser, in Node, and on iOS and Android from these same files. Source, training |
| pipeline, whitepaper, and the full model card: |
| https://github.com/hackshare/curtain-privacy |
|
|
| This repo ships in two sizes, selected by revision: |
|
|
| - **`curtain-small`** — `v2.0.0`, 59.9 MB, 12-layer Multilingual-MiniLM with a |
| SentencePiece tokenizer. The default: best multilingual and repeated/leading-name |
| recall. `onnx/model_q4.onnx` SHA-256 |
| `c9bfe8a0a9e3cfbb1a8995009259a5195109c8881f16905ef5be58351ad8786f`. |
| - **`curtain-tiny`** — `v1.0.0`, 14.2 MB, 6-layer MiniLM with a WordPiece tokenizer. |
| The smallest-footprint tier, frozen. `onnx/model_q4.onnx` SHA-256 |
| `24ba1f03a8c3db8a4f760d4d266faeb679ba23f8c23f7be9ba6964cbfff6f6c1`. |
|
|
| The models are built locally from the committed `train/` pipeline; this repo is a |
| distribution copy. Verify integrity by pinning a revision and checking the hash above. |
|
|
| ## Integrating |
|
|
| ### Web and Node (transformers.js) |
|
|
| ```js |
| import { createGuard } from "curtain-privacy"; |
| |
| const guard = await createGuard({ model: "hackshare/curtain-privacy", revision: "v2.0.0" }); |
| const { text } = await guard.protect("My SSN is 472-81-0094"); |
| ``` |
|
|
| `revision: "v2.0.0"` pins the audited `curtain-small` weights (use `v1.0.0` for |
| `curtain-tiny`). transformers.js fetches from this repo with permissive CORS, so it |
| works from any origin. `v2.0.0` is a moving pointer to the latest `curtain-small` |
| build; to pin an immutable artifact, use the timestamped tag `v2.0.0-<timestamp>` |
| published alongside each release. |
|
|
| ### iOS and Android (ONNX Runtime Mobile) |
|
|
| Fetch or bundle two files from a pinned revision (`curtain-small` shown; use `v1.0.0` |
| for `curtain-tiny`): |
|
|
| - `https://huggingface.co/hackshare/curtain-privacy/resolve/v2.0.0/onnx/model_q4.onnx` |
| - `https://huggingface.co/hackshare/curtain-privacy/resolve/v2.0.0/tokenizer.json` |
|
|
| Verify `model_q4.onnx` against the SHA-256 above. Load the model with ONNX Runtime |
| Mobile, tokenize with the Hugging Face `tokenizers` library (Swift and Kotlin |
| bindings load `tokenizer.json` directly) or ONNX Runtime Extensions, then apply the |
| BIO decode and the default keep-set (CITY, STATE, ZIP_CODE) the library documents. |
| These are integration guides, not a shipped native SDK. |
| |
