Use canonical PII EN 65M name and current installation instructions

DOWNLOAD.md

@@ -1,30 +1,71 @@
-# Reproducible install
+# Download and install the qualified runtime
 
-After publication under DataFog/datafog-pii, record the immutable 40-character Hub commit SHA. Do not deploy an unpinned main revision. The release tag will be v0.1.0.
+Use Python 3.12 or newer for installation. Inference runs through the native executable and needs neither Python nor network access. The Hugging Face repository is private; authenticate locally with an account authorized for DataFog.
 
 ```sh
-hf download DataFog/datafog-pii --revision <40-character-commit-sha> --local-dir ./datafog-pii-release
-python3 ./datafog-pii-release/tools/install_bundle.py --snapshot ./datafog-pii-release --destination ./datafog-pii-bundle
+python -m pip install 'huggingface_hub==1.27.0'
+hf auth login
 ```
 
-The installer verifies the complete snapshot manifest, checks host OS/architecture, refuses an existing destination, safely extracts the versioned archive, and restores executable mode. Run `datafog-pii-bundle/datafog-pii datafog-pii-bundle` and send one JSON object with a text string per stdin line. Successful inference never requires Python or network access.
+Select exactly one tested target: `linux-x86_64`, `linux-aarch64`, `macos-arm64`, `macos-x86_64`, or `windows-x86_64`. The release index records the tested OS, exact archive hash, runtime source commit, model revision and MCP compatibility revision. Linux ARM64 qualification on Ubuntu is not a Raspberry Pi OS qualification. Windows qualification on Server 2022 does not establish every desktop Windows version.
 
-Policy for PR #32:
+Save this script as `download_install.py`. The script pins immutable runtime commit `7cadd41e21f59b2a149e31378d073cf6ca057531` from the staging report. It downloads only your selected archive and the versioned installer, forces a fresh download, and verifies the archive and all installed file hashes.
+
+```python
+import argparse
+import json
+import subprocess
+import sys
+from pathlib import Path
+from huggingface_hub import hf_hub_download
+
+parser = argparse.ArgumentParser()
+parser.add_argument('--platform', required=True)
+parser.add_argument('--destination', type=Path, required=True)
+args = parser.parse_args()
+revision = '7cadd41e21f59b2a149e31378d073cf6ca057531'
+repo = 'DataFog/pii-en-65m'
+prefix = 'runtimes/v0.2.0'
+downloads = Path('datafog-runtime-download').resolve()
+
+def download(name):
+    return Path(hf_hub_download(
+        repo_id=repo, revision=revision, filename=f'{prefix}/{name}',
+        local_dir=downloads, force_download=True,
+    ))
+
+index = json.loads(download('release-index.json').read_text(encoding='utf-8'))
+record = next(item for item in index['platforms'] if item['platform'] == args.platform)
+archive = download(record['archive']['filename'])
+download('tools/common.py')
+installer = download('tools/install_bundle.py')
+subprocess.run([
+    sys.executable, str(installer), '--archive', str(archive),
+    '--sha256', record['archive']['sha256'],
+    '--destination', str(args.destination.resolve()),
+], check=True)
+```
+
+Run it with your target and a new absolute destination; the installer refuses an existing directory and a mismatched host architecture.
+
+```sh
+python download_install.py --platform macos-arm64 --destination /absolute/new/datafog-bundle
+```
+
+On Windows, use `--platform windows-x86_64` and a path such as `C:\DataFog\bundle`. Install Microsoft's x64 Visual C++ Redistributable (2019-compatible v14). The installer probes startup and reports a missing runtime dependency. Intel macOS requires 15 or newer; ARM macOS requires 14 or newer.
+
+Use datafog-mcp PR #33's compatibility revision `01d7f74e693a7892ab1ed504d0d8f8c1e7ce51d3` (stacked on PR #32). Configure the installed path in MCP policy:
 
 ```toml
-version = 1
 [model]
-bundle_directory = "/absolute/path/to/datafog-pii-bundle"
+bundle_directory = "/absolute/new/datafog-bundle"
 ```
 
-Reproduce actual MCP verification with a clean checkout:
+On Windows, TOML literal strings avoid escaping backslashes:
 
-```sh
-git clone https://github.com/DataFog/datafog-mcp.git
-git -C datafog-mcp checkout c2c45ec62728d85b7472131a3df9ccb67afd4a02
-cd datafog-mcp
-uv sync --frozen --group dev --python 3.12
-DATAFOG_TEST_MODEL_BUNDLE=/absolute/path/to/datafog-pii-bundle uv run --frozen pytest tests/test_model_runtime.py tests/test_csv_processing.py --no-cov
+```toml
+[model]
+bundle_directory = 'C:\DataFog\bundle'
 ```
 
-Use the frozen lock, not the GLiNER comparison requirements. Fresh archive transport tests can be run locally before publication; only a real Hub download establishes Hub delivery. The release report distinguishes these statuses.
+Keep weights, tokenizer, configuration and calibration together. GLiNER is not part of this download.

README.md

@@ -13,9 +13,9 @@ tags:
 - experimental
 - datafog
 ---
-# DataFog PII
+# DataFog PII EN 65M
 
-DataFog PII is a **65.2M-parameter English token classifier** for locating and redacting seven types of personally identifiable information. It returns typed spans, calibrated span confidence, UTF-8 byte offsets and redacted text through a local JSONL runtime. Inference uses the CPU and requires no network access after installation.
+DataFog PII EN 65M is a **65.2M-parameter English token classifier** for locating and redacting seven types of personally identifiable information. It returns typed spans, calibrated span confidence, UTF-8 byte offsets and redacted text through a local JSONL runtime. Inference uses the CPU and requires no network access after installation.
 
 The frozen **model v0.1.0** achieves **98.32% exact typed-span F1** on 90,018 held-out synthetic documents. **Runtime v0.2.0** has qualified native bundles for five platform environments. The checkpoint and acceptance threshold remain **experimental**; performance on reviewed customer tickets has not been established.
 
@@ -53,6 +53,8 @@ The root safetensors are a standard Transformers token-classification checkpoint
 | `reproduction/`, `provenance/` | Training/evaluation code, locks, partition/source provenance and original audit |
 | `LICENSE`, `NOTICE`, `licenses/`, `LICENSING.md` | Model/source licensing, dataset attribution and upstream dependency notices |
 
+Canonical Hub ID: `DataFog/pii-en-65m` (formerly `DataFog/datafog-pii`, which redirects here). Frozen archive/executable filenames retain their original names and hashes. The older [DataFog PII EN 71M](https://huggingface.co/DataFog/pii-en-71m) is a separate 41-entity custom model and is not the MCP runtime described here.
+
 Pin model revision `02cc6ca86a11dcb2b328861687770a22a7ea1b76` and runtime revision `7cadd41e21f59b2a149e31378d073cf6ca057531` for reproducible downloads. Original tags `v0.1.0` and `runtime-v0.2.0` remain preserved. The original `bundle/` executable is macOS ARM64-only; use the versioned runtime archives for other platforms. The root manifest covers the original model files and current card evidence; the versioned runtime has its own manifest.
 
 ## Usage
@@ -74,7 +76,7 @@ import sys
 from pathlib import Path
 from huggingface_hub import hf_hub_download
 
-REPO = "DataFog/datafog-pii"
+REPO = "DataFog/pii-en-65m"
 REVISION = "7cadd41e21f59b2a149e31378d073cf6ca057531"
 PREFIX = "runtimes/v0.2.0"
 TARGET = "macos-arm64"  # Select your tested platform below.
@@ -122,7 +124,7 @@ print([(f["label"], f["start"], f["end"]) for f in result["findings"]])
 # [('first_name', 8, 12), ('last_name', 13, 18), ('email', 22, 38)]
 ```
 
-The example output was checked against the released runtime. See the [versioned download guide](runtimes/v0.2.0/DOWNLOAD.md) for installation details.
+The example output was checked against the released runtime. See the [download guide](DOWNLOAD.md) for installation details.
 
 ### MCP integration
 

manifest.json

@@ -3,8 +3,8 @@
   "version": "0.1.0",
   "files": {
     "DOWNLOAD.md": {
-      "sha256": "d9bec8da2b7a4efcb32e7c748fcaad44074fa7b7031303d6f34d56df38deba81",
-      "bytes": 1536
+      "sha256": "f31de18000dfd29c2cc448c6383de6d7a05e9624a0f79c21b65bfde0adde19a4",
+      "bytes": 3209
     },
     "LICENSE": {
       "sha256": "cfc7749b96f63bd31c3c42b5c471bf756814053e847c10f3eb003417bc523d30",
@@ -23,8 +23,8 @@
       "bytes": 2526
     },
     "README.md": {
-      "sha256": "80205bcdc3939661cb9151fcdf71c5599635083b09ef62426adf78542e7da46c",
-      "bytes": 19311
+      "sha256": "ca69541ef1b5e5bc21186e14886e7bdf92d6dd55d7446a68f19fca0e3e62ba9a",
+      "bytes": 19624
     },
     "archives/datafog-pii-v0.1.0-macos-arm64.tar.gz": {
       "sha256": "2dd5251c1b984011852a46a3f4f30b176decf82f543a691c5a288e0a9f93b7a1",