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temsa/
OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8

Name: OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8
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OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8

Raw-only Irish core PII release derived from OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1.

This repo does not require the scanner / validator layer used by temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc7. Both the full checkpoint and the ONNX q8 artifact use the same learned score-only decoder over token-presence and typed boundary heads.

Coverage

PPSN
ACCOUNT_NUMBER
BANK_ROUTING_NUMBER
CREDIT_DEBIT_CARD
PASSPORT_NUMBER
POSTCODE
PHONE_NUMBER
EMAIL
FIRST_NAME
LAST_NAME
SWIFT_BIC

Included Variants

Full transformers checkpoint in the repo root
Unquantized ONNX export in onnx/model.onnx
Dynamic q8 ONNX artifact in onnx/model_quantized.onnx
inference_mask.py for the full checkpoint
inference_mask_onnx.py for the ONNX q8 artifact
common.py, model.py, and multitask_model.py implementing the raw-only decoder
benchmark files in eval/

Artifact sizes:

Full checkpoint: 515 MB (model.safetensors)
Dynamic q8 ONNX: 393 MB (onnx/model_quantized.onnx)

What Changed From rc7

rc7 achieves its public quality with a bundled scanner / validator inference stack.

rc8 removes that layer completely:

no regex-based candidate extraction
no checksum validator dependency at inference time
no separate scanner spec or generated scanner code
same compact mLiteClinical encoder family, but with a raw-only multi-head decoder

The tradeoff is explicit:

rc7 is still stronger on the broad manual Irish core suite
rc8 is easier to embed, simpler to maintain, and its ONNX q8 path stays very close to the full checkpoint

Architecture

rc8 keeps the DistilBERT-size encoder class of the 135M mLiteClinical base and adds:

a token-presence head for each released label
a typed start-boundary head
a typed end-boundary head
a score-only decoder that uses model scores, token offsets, continuity priors, and minimum-length priors from config

There is no scanner or external validator in the release path.

Design references that informed this direction:

Split-NER: https://aclanthology.org/2023.acl-short.36/
SpanNER: https://aclanthology.org/2021.acl-long.558/
Boundary Smoothing for Named Entity Recognition: https://aclanthology.org/2022.acl-long.490/
TinyBERT: https://aclanthology.org/2020.findings-emnlp.372/

How To Use It

Full checkpoint:

bash

uv run python inference_mask.py \
  --model temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8 \
  --min-score 0.5 \
  --text "My PPSN is 1234567TW, my Eircode is D02 X285, and my phone is 087 123 4567." \
  --json

Dynamic q8 ONNX:

bash

uv run python inference_mask_onnx.py \
  --model temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8 \
  --min-score 0.5 \
  --text "Please provide your passport NN5123456 and call me on 0851234567." \
  --json

Benchmarks

Main comparison:

Model	Irish core F1	Edge F1	Finance F1	Finance-boundary F1	User PPSN F1	GA weak PPSN F1	Multilingual PPSN F1	Core CPU ex/s	Multilingual CPU ex/s
Base OpenMed	0.3743	0.0556	-	-	-	-	0.0000	15.1811	37.4666
Previous public `rc7` full	1.0000	-	1.0000	1.0000	-	1.0000	-	3.5394	-
Previous public `rc7` ONNX q8	0.9934	-	1.0000	1.0000	-	1.0000	-	12.1653	-
`rc8` full	0.9737	1.0000	1.0000	1.0000	1.0000	1.0000	0.9176	2.2965	6.3095
`rc8` ONNX q8	0.9737	1.0000	1.0000	1.0000	1.0000	1.0000	0.9176	46.1420	99.7166

Irish core label breakdown:

Label	`rc8` full	`rc8` ONNX q8
PPSN	1.0000	1.0000
PHONE_NUMBER	0.9565	0.9565
POSTCODE	1.0000	1.0000
ACCOUNT_NUMBER	0.8000	0.8000
PASSPORT_NUMBER	1.0000	1.0000
EMAIL	1.0000	1.0000
FIRST_NAME	0.9744	0.9744
LAST_NAME	0.9744	0.9744

Dynamic q8 Artifact

Artifact paths:

unquantized: onnx/model.onnx
preprocessed: onnx/model.preprocessed.onnx
quantized: onnx/model_quantized.onnx

Quantization recipe used here:

ONNX pre-processing before quantization
ONNX Runtime dynamic int8
qint8
per_channel=true
op_types=MatMul,Gemm,Attention

For CPU deployment, the ONNX q8 artifact is the recommended default.

Limits

rc8 is raw-only. It intentionally gives up the scanner/validator stack used by rc7, so its broad manual-suite ceiling is lower.
The current remaining local misses are a bare 8-digit account-number case and one Gaelic phone-number case in the manual core suite.
If you need the exact rc8 behavior, use the bundled inference scripts or import decode_token_presence_segments from common.py.

License And Attribution

Release license: Apache-2.0
Base model: OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1
See NOTICE and training_sources.json for attribution and training details.

Portfolio Comparison

Updated: 2026-03-16.

Use this section for the fastest public comparison across the temsa PII masking portfolio.

The first core table only includes public checkpoints that ship both comparable q8 accuracy and q8 CPU throughput.
The first PPSN table only includes public artifacts that ship comparable PPSN accuracy and CPU throughput.
Missing cells in the archive tables mean the older release did not ship that metric in its public bundle.
DiffMask rows use the reconciled clean_single_pass harness that matches the deployed runtime.
GlobalPointer rows use the public raw-only span-matrix release bundle and its packaged q8 ONNX artifact.
The same content is shipped as PORTFOLIO_COMPARISON.md inside each public model repo.

Irish Core PII: Comparable Public Checkpoints

Repo	Stack	Full Core F1	Q8 Core F1	Q8 Multilingual PPSN F1	Q8 Core ex/s
`temsa/IrishCore-GlobalPointer-ContextPII-4L-122M-v1-rc4`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	299.0
`temsa/IrishCore-GlobalPointer-ContextPII-4L-122M-v1-rc3`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	317.9
`temsa/IrishCore-GlobalPointer-ContextPII-4L-122M-v1-rc2`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	292.5
`temsa/IrishCore-GlobalPointer-ContextPII-4L-122M-v1-rc1`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	337.3
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc27`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	270.0
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc25`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	212.1
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc24`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	278.9
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc23`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	237.6
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc22`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	106.8
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc21`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	150.8
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc20`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	181.9
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc19`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	73.1
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc18`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	126.2
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc17`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	125.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc16`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	125.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc15`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	125.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc14`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	119.2
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc13`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	126.1
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc12`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	73.6
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc11`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	94.1
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc10`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	125.8
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc9`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	119.8
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc8`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	128.9
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc7`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	89.0
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc6`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	89.0
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc5`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	84.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc4`	GlobalPointer raw-only + context labels	0.9935	0.9935	0.9333	61.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc3`	GlobalPointer raw-only + context labels	0.9935	0.9935	0.9333	61.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc2`	GlobalPointer raw-only + context labels	0.9935	0.9935	0.9222	61.5
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc1`	GlobalPointer raw-only + context labels	0.9935	0.9935	0.9222	61.5
`temsa/IrishCore-GlobalPointer-135M-v1-rc4`	GlobalPointer raw-only span-matrix	1.0000	1.0000	0.9333	221.6
`temsa/IrishCore-GlobalPointer-135M-v1-rc3`	GlobalPointer raw-only span-matrix	1.0000	1.0000	0.9213	204.9
`temsa/IrishCore-GlobalPointer-135M-v1-rc2`	GlobalPointer raw-only span-matrix	0.9934	0.9934	0.9326	231.2
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8`	Raw-only token-span	0.9737	0.9737	0.9176	46.1
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc7`	Hybrid classifier + generated scanner spec	1.0000	0.9934	1.0000	30.0
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc6`	Hybrid classifier + repair decoders	1.0000	0.9934	1.0000	29.5
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc5`	Hybrid classifier + repair decoders	0.9737	0.9669	0.9333	34.4
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc4`	Hybrid classifier + repair decoders	0.9870	0.9740	0.9600	114.2
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc3`	Hybrid classifier + repair decoders	0.9806	0.9677	0.9333	44.9
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc2`	Hybrid classifier + repair decoders	0.9554	0.9615	0.7887	119.1
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v1`	Hybrid classifier baseline	0.9530	0.9333	0.9882	103.3
`temsa/IrishCore-DiffMask-135M-v1-rc6`	DiffMask token-span, scanner-free	0.9801	0.9733	0.9274	130.3
`temsa/IrishCore-DiffMask-135M-v1-rc5`	DiffMask token-span, scanner-free	0.9733	0.9733	0.9379	249.2
`temsa/IrishCore-DiffMask-135M-v1-rc4`	DiffMask token-span, scanner-free	0.9733	0.9733	0.9371	29.5
`temsa/IrishCore-DiffMask-135M-v1-rc3`	DiffMask token-span, scanner-free	0.9664	0.9664	0.9591	30.0
`temsa/IrishCore-DiffMask-135M-v1-rc2`	DiffMask token-span, scanner-free	0.9664	0.9664	0.9212	247.1
`temsa/IrishCore-DiffMask-135M-v1-rc1`	DiffMask token-span, scanner-free	0.9801	0.9934	0.9412	251.2

Irish Core PII: Other Public Checkpoints

Repo	Stack	Full Core F1	Q8 Core F1	Q8 Multilingual PPSN F1	Notes
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc1`	Hybrid classifier prototype	0.9487	—	—	Predates the public q8 artifact.

Finance-boundary q8 F1 is 1.0000 for OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc6, OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc7, OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8, and all public IrishCore-DiffMask releases from rc1 to rc6. OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc5 ships 0.8750 on that public q8 suite.

PPSN-Only: Comparable Public Artifacts

Repo	Artifact	Irish Large F1	Multilingual PPSN F1	User Raw F1	QA v8 F1	CPU ex/s
`temsa/OpenMed-mLiteClinical-IrishPPSN-135M-v1`	fp32 canonical checkpoint	0.8979	0.9704	0.8000	0.7385	57.4
`temsa/OpenMed-mLiteClinical-IrishPPSN-135M-v1-fp16`	fp16 CPU/GPU artifact	—	0.9704	0.8000	0.7385	45.8
`temsa/OpenMed-mLiteClinical-IrishPPSN-135M-v1-q8`	dynamic int8 CPU artifact	—	0.9040	—	—	132.1

PPSN-Only: Historical Public Checkpoints

Repo	Main Published Metrics	Notes
`temsa/OpenMed-PPSN-mLiteClinical-v1`	same as canonical fp32 repo: multilingual 0.9704, user raw 0.8000	Legacy alias; prefer `temsa/OpenMed-mLiteClinical-IrishPPSN-135M-v1`.
`temsa/OpenMed-PPSN-v6-raw-rc2`	irish_reg_v5 0.8750; user_raw 0.8000; qa_v8 0.7385	Raw PPSN-only research checkpoint; no packaged multilingual CPU benchmark row.
`temsa/OpenMed-PPSN-v5_1`	irish_large_v2 raw 0.9285; qa_v6 hybrid strict 1.0000	Hybrid PPSN-only checkpoint; predates the canonical multilingual suite packaging.
`temsa/OpenMed-PPSN-v5`	irish_reg_v5 raw 0.8235; irish_reg_v5 hybrid strict 1.0000	Hybrid PPSN-only checkpoint; predates the canonical multilingual suite packaging.
`temsa/OpenMed-PPSN-v4`	synthetic non-PPSN drift check only	Predates the current PPSN eval suite; no packaged apples-to-apples multilingual CPU row.

If you need the strongest current raw-only Irish core model, start with IrishCore-GlobalPointer-135M-v1-rc4. If you need the fastest CPU-first raw-only line, compare it against IrishCore-DiffMask-135M-v1-rc6. If you need a PPSN-only artifact, compare the canonical fp32, fp16, and q8 variants of OpenMed-mLiteClinical-IrishPPSN-135M-v1 directly in the table above.