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temsa/
IrishCore-GlobalPointer-135M-v1-rc4

Name: IrishCore-GlobalPointer-135M-v1-rc4
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IrishCore-GlobalPointer-135M-v1-rc4

IrishCore-GlobalPointer-135M-v1-rc4 is a raw-only Irish PII masking model derived from OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1.

It targets explicit masking with placeholders such as [PII:PPSN], [PII:EMAIL], and [PII:POSTCODE] for:

PPSN
ACCOUNT_NUMBER
BANK_ROUTING_NUMBER
CREDIT_DEBIT_CARD
PASSPORT_NUMBER
POSTCODE
PHONE_NUMBER
EMAIL
FIRST_NAME
LAST_NAME
SWIFT_BIC

The main target is English plus Irish Gaelic text in citizen-support, public-sector, and HSE-style flows. The repo ships both the full transformers checkpoint and a dynamic q8 ONNX artifact for CPU deployment.

What This Model Is

This release is a compact span-matrix extractor built on top of the OpenMed mLiteClinical encoder.

Short version:

Base OpenMed: plain BIO token classification
DiffMask: token-span extraction with per-token presence plus boundary heads
GlobalPointer: direct typed span scoring over the token grid

This release is fully raw-only:

no external regex scanner layer
no external checksum validator layer
only a bundled lightweight span-repair stage inside common.py

The published behavior is fully defined by the weights plus the bundled decode/repair logic in common.py.

Architecture

Encoder: DistilBERT-size encoder from OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1
Span head: GlobalPointer-style typed span matrix
Positional encoding inside the span head: RoPE
Training objective: positive-weighted BCE with hard-negative mining over valid upper-triangular spans
Runtime: one forward pass plus span decoding, with lightweight context-aware repairs for a few boundary-sensitive labels

Unlike the DiffMask line, this release does not use diffusion-style training. It directly predicts whether each (start_token, end_token) pair is an entity span for each released label.

Why This Line Exists

The main reason for this architecture change was to improve the cases where earlier raw-only lines were fragile:

mixed messages containing 2-3 PII types together
Eircode and IBAN/card boundaries in realistic support text
PPSN and phone/entity overlap cases
broader generalization on unseen nearby phrasing

The tradeoff is straightforward:

accuracy is materially better on the hard Irish/UAT suites
CPU q8 speed is slower than the DiffMask q8 line

Included Artifacts

full transformers checkpoint in the repo root
dynamic q8 ONNX artifact in onnx/model_quantized.onnx
inference_mask.py
inference_mask_onnx.py
benchmark JSON and summaries in eval/
release provenance in training_sources.json

Benchmark Summary

Gov Chatbot Red-Team v2

Suite	Full F1	Q8 F1	Q8 Exact F1	Q8 Failures
Gov chatbot red-team v2	1.0000	1.0000	1.0000	0.0000
Gov chatbot gap holdout v2	1.0000	1.0000	1.0000	0.0000

This Release

Suite	Full F1	Q8 F1	Q8 ex/s
Irish core	1.0000	1.0000	221.5743
UAT exact	1.0000	1.0000	188.6537
Fresh holdout	0.9841	0.9841	145.9336
Hardening exact	1.0000	1.0000	112.4948
Edge	1.0000	1.0000	235.2888
Multilingual PPSN overall	0.9333	0.9333	224.6955
Multilingual PPSN label-only	1.0000	1.0000	—

Closest Public Comparisons

Repo	Stack	Q8 Core F1	Q8 Hardening F1	Q8 Multilingual F1	Q8 Core ex/s
`temsa/IrishCore-GlobalPointer-135M-v1-rc4`	GlobalPointer raw-only span-matrix	1.0000	1.0000	0.9333	221.5743
`temsa/IrishCore-DiffMask-135M-v1-rc6`	DiffMask raw-only token-span	0.9733	0.9756	0.9274	130.3415
`temsa/OpenMed-mLiteClinical-IrishCorePII-135M-v2-rc8`	Raw-only token-span	0.9737	—	0.9176	46.1420

Practical reading:

This release is the strongest raw-only checkpoint in this repo family on the hard Irish/UAT/holdout suites.
The q8 CPU artifact keeps the same accuracy on the main suites used for release.
The multilingual benchmark's overall score is lower than the PPSN label-only score because that suite penalizes extra name detections as false positives. On the label that matters there, PPSN, this release is strong.

Usage

Full checkpoint

bash

python3 inference_mask.py \
  --model temsa/IrishCore-GlobalPointer-135M-v1-rc4 \
  --text "My PPSN is 1234567T, my Eircode is D02 XY45, and my phone is 087 123 4567." \
  --json

ONNX q8 CPU artifact

bash

python3 inference_mask_onnx.py \
  --model temsa/IrishCore-GlobalPointer-135M-v1-rc4 \
  --text "My PPSN is 1234567T, my Eircode is D02 XY45, and my phone is 087 123 4567." \
  --json

Both scripts emit:

extracted spans with offsets and labels
masked text using [PII:LABEL]

How It Differs From Other OpenMed-Derived Lines

Compared with the original OpenMed base model:

this release does not use a BIO token head
it scores typed spans directly
it is tuned only for the released Irish core PII labels

Compared with DiffMask:

no diffusion-style masked denoising during training
no token-presence or boundary heads
direct span-matrix scoring instead of reconstructing spans from token and boundary logits

Compared with the old hybrid releases:

no external scanner or validator layer is required for the published behavior
deployment stays simple: encoder + span head + deterministic replacement

Limitations

It is slower on CPU than the DiffMask q8 release.
The multilingual benchmark is not a clean multilingual NER benchmark; it is a PPSN-focused suite where extra name detections count against the overall score.
If you need the fastest CPU-first public line rather than the strongest raw-only accuracy, compare this release against temsa/IrishCore-DiffMask-135M-v1-rc6.

References

DistilBERT: https://arxiv.org/abs/1910.01108
Global Pointer: Novel Efficient Span-based Approach for Named Entity Recognition: https://arxiv.org/abs/2208.03054
RoFormer: Enhanced Transformer with Rotary Position Embedding: https://arxiv.org/abs/2104.09864

License And Attribution

Release license: Apache-2.0
Base model: OpenMed/OpenMed-PII-mLiteClinical-Base-135M-v1
Dataset attribution is listed in NOTICE

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-rc6`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	282.9
`temsa/IrishCore-GlobalPointer-ContextPII-4L-122M-v1-rc5`	4-layer GlobalPointer distilled fast student	1.0000	1.0000	0.9333	282.9
`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-rc29`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	232.7
`temsa/IrishCore-GlobalPointer-ContextPII-135M-v1-rc28`	GlobalPointer raw-only + context labels	1.0000	1.0000	0.9333	232.7
`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.