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OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx
OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx is a token classification model from OpenMed. Use it when you need labels on individual words, such as names. It is set up for openmed. The card lists the license as apache-2.0.
This repository contains an MLX packaging of OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1 for Apple Silicon inference with OpenMed.
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.safetensors431 MB · 100%
From the Hugging Face model README
This repository contains an MLX packaging of OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1 for Apple Silicon inference with OpenMed.
OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1bert (BertForTokenClassification)pt)config.json, id2label.json, MLX weight files)safetensorsopenmed[mlx] on Apple Silicon MacsOpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1config.json, id2label.json, openmed-mlx.json, MLX weights, and tokenizer assetsDownload this OpenMed MLX artifact directly from the Hub:
hf download OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx --local-dir ./OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx
Use the downloaded directory when you want to pin this exact MLX artifact in an offline or local Apple Silicon workflow.
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-Portuguese-BioClinicalBERT-Base-110M-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.
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-Portuguese-BioClinicalBERT-Base-110M-v1-mlx --local-dir ./OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx
from openmed import extract_pii
from openmed.core import OpenMedConfig
text = "<your clinical note here>"
result = extract_pii(
text,
model_name="./OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1-mlx",
config=OpenMedConfig(backend="mlx"),
use_smart_merging=True,
)
print(result.entities)
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:
This repo uses the current legacy-compatible MLX layout:
config.jsonid2label.jsonweights.safetensors and/or weights.npz)Tokenizer assets are bundled in this repo.
OpenMed/OpenMed-PII-Portuguese-BioClinicalBERT-Base-110M-v1