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
Add public MLX snapshot usage note
Browse files
README.md
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@@ -37,6 +37,16 @@ This repository contains an MLX packaging of [`OpenMed/OpenMed-PII-Portuguese-mS
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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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- 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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## Use This MLX Snapshot
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Download this OpenMed MLX artifact directly from the Hub:
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```bash
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hf download OpenMed/OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx --local-dir ./OpenMed-PII-Portuguese-mSuperClinical-Large-279M-v1-mlx
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```
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Use the downloaded directory when you want to pin this exact MLX artifact in an offline or local Apple Silicon workflow.
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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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