MLX rollout: refreshed for public access on 2026-06-23
Hub artifact: OpenMed MLX repository
Source checkpoint: OpenMed/OpenMed-NER-SpeciesDetect-TinyMed-135M
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-SpeciesDetect-TinyMed-135M-mlx --local-dir ./OpenMed-NER-SpeciesDetect-TinyMed-135M-mlx

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

Quick Start

bash

pip install openmed
pip install "openmed[mlx]"

python

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-SpeciesDetect-TinyMed-135M",
    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.

Open Xcode and go to File > Add Package Dependencies.
Paste the OpenMed repository URL: https://github.com/maziyarpanahi/openmed
Choose the package product OpenMedKit from the repository.
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-SpeciesDetect-TinyMed-135M
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