OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1-mlx

OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1 for OpenMed MLX

This repository contains an MLX packaging of OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1 for Apple Silicon inference with OpenMed.

At a Glance

• Source checkpoint: OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1
• Model family: bert (BertForTokenClassification)
• Primary language hint: Turkish (tr)
• Artifact layout: legacy-compatible MLX (config.json, id2label.json, MLX weight files)
• Weight format: safetensors
• Python MLX: supported through openmed[mlx] on Apple Silicon Macs

Python Quick Start

Use the standard OpenMed API if you want OpenMed to choose the right runtime automatically:

pip install "openmed[mlx]"

from openmed import extract_pii

text = "<your clinical note here>"
result = extract_pii(
    text,
    model_name="OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1",
    use_smart_merging=True,
)

for entity in result.entities:
    print(entity.label, entity.text, round(entity.confidence, 4))

On Apple Silicon, OpenMed can use this preconverted MLX artifact when openmed[mlx] is installed. On other systems, OpenMed falls back to the Hugging Face / PyTorch backend.

Use This Preconverted MLX Repo Directly

If you want to use this MLX snapshot explicitly, download it locally and point OpenMed at the directory:

pip install "openmed[mlx]"
hf download OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1-mlx --local-dir ./OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1-mlx

If this repo is private in your environment, authenticate first with hf auth login or set HF_TOKEN.

from openmed import extract_pii
from openmed.core import OpenMedConfig

text = "<your clinical note here>"
result = extract_pii(
    text,
    model_name="./OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1-mlx",
    config=OpenMedConfig(backend="mlx"),
    use_smart_merging=True,
)

print(result.entities)

Swift Status

This repo is based on bert. Python MLX supports this artifact today, and this family is in the current OpenMedKit Swift MLX support matrix.

If you are building an Apple app today, the recommended paths for this model are:

• Python MLX for evaluation or local workflows on Apple Silicon
• CoreML in OpenMedKit if you already have a compatible bundled Apple export
• Track the current Swift support matrix in the OpenMedKit docs

Artifact Notes

This repo uses the current legacy-compatible MLX layout:

• config.json
• id2label.json
• MLX weight files (weights.safetensors and/or weights.npz)

Tokenizer assets are bundled in this repo.

Links

• Source checkpoint: OpenMed/OpenMed-PII-Turkish-ClinicalE5-Large-335M-v1
• OpenMed GitHub: https://github.com/maziyarpanahi/openmed
• MLX backend docs: https://openmed.life/docs/mlx-backend/
• OpenMedKit docs: https://openmed.life/docs/swift-openmedkit/