Instructions to use OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
Refresh OpenMed MLX model card
Browse files
README.md
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- Weight format: `safetensors`
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- Python MLX: supported through `openmed[mlx]` on Apple Silicon Macs
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## Python Quick Start
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Use the standard OpenMed API if you want OpenMed to choose the right runtime automatically:
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- Weight format: `safetensors`
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- Python MLX: supported through `openmed[mlx]` on Apple Silicon Macs
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## OpenMed MLX Status
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- Private MLX rollout: refreshed on 2026-06-23
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- Hub artifact: private OpenMed MLX repository
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- Source checkpoint: [`OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1`](https://huggingface.co/OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1)
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- Collection: [OpenMed Medical MLX Models](https://huggingface.co/collections/OpenMed/medical-mlx-models)
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- Runtime: OpenMed Python MLX backend on Apple Silicon
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- Artifact layout: `config.json`, `id2label.json`, `openmed-mlx.json`, MLX weights, and tokenizer assets
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## Python Quick Start
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Use the standard OpenMed API if you want OpenMed to choose the right runtime automatically:
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