OpenMed-NER-ProteinDetect-SuperClinical-184M-mlx

OpenMed-NER-ProteinDetect-SuperClinical-184M for OpenMed MLX

This repository contains an OpenMed MLX conversion of OpenMed/OpenMed-NER-ProteinDetect-SuperClinical-184M for Apple Silicon inference with OpenMed.

Artifact metadata:

• OpenMed MLX task: token-classification
• OpenMed MLX family: deberta-v2
• Weight format: safetensors
• Runtime API: OpenMed MLX token-classification backend

OpenMed MLX Status

• MLX rollout: refreshed for public access on 2026-06-23
• Hub artifact: OpenMed MLX repository
• Source checkpoint: OpenMed/OpenMed-NER-ProteinDetect-SuperClinical-184M
• Collection: OpenMed Medical MLX Models
• Runtime: OpenMed Python MLX backend on Apple Silicon
• Artifact layout: config.json, id2label.json, openmed-mlx.json, MLX weights, and tokenizer assets

Use This MLX Snapshot

Download this OpenMed MLX artifact directly from the Hub:

hf download OpenMed/OpenMed-NER-ProteinDetect-SuperClinical-184M-mlx --local-dir ./OpenMed-NER-ProteinDetect-SuperClinical-184M-mlx

Use the downloaded directory when you want to pin this exact MLX artifact in an offline or local Apple Silicon workflow.

Quick Start

pip install openmed
pip install "openmed[mlx]"

from openmed import analyze_text
from openmed.core.config import OpenMedConfig

result = analyze_text(
    "Patient John Doe, DOB 1990-05-15, SSN 123-45-6789",
    model_name="OpenMed/OpenMed-NER-ProteinDetect-SuperClinical-184M",
    config=OpenMedConfig(backend="mlx"),
)

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

Swift and Apple Apps

Use Swift with OpenMedKit, not with MLX weight files directly.

1. Open Xcode and go to File > Add Package Dependencies.
2. Paste the OpenMed repository URL: https://github.com/maziyarpanahi/openmed
3. Choose the package product OpenMedKit from the repository.
4. Add a compatible CoreML model bundle plus id2label.json to your app target.

This MLX model is for Python services on Apple Silicon, local MLX inference on macOS, and Hub-hosted model distribution. If a given environment cannot write weights.safetensors, OpenMed falls back to weights.npz so the model remains usable.

Credits

• Base checkpoint: OpenMed/OpenMed-NER-ProteinDetect-SuperClinical-184M
• OpenMed GitHub: https://github.com/maziyarpanahi/openmed
• OpenMed website: https://openmed.life
• MLX conversion and runtime support: OpenMed
• Swift runtime for Apple apps: OpenMedKit from the OpenMed repository