AI & Machine Learning
Running OpenMed Ondevice
Run OpenMed models fully on-device with the MLX (Apple Silicon), CoreML (iOS/macOS), or ONNX/WebGPU (cross-platform/browser) backends, including convert-quantize-run workflows. Use when the user wants to deploy OpenMed at the edge, run NER/de-id on Apple Silicon, target iPhone/iPad/Mac, export to ONNX or WebGPU, quantize a clinical model to int8/4-bit, run with no network, or pick between MLX/CoreML/ONNX. Covers the mlx/coreml/onnx extras, the convert() functions and python -m convert CLIs, quantization, loading a local MLX artifact through analyze_text, OpenMedMLXLanguageModel/generate_text, and the on-device-only PHI guarantee (nothing leaves the host).
- Publisher / source
- maziyarpanahi/openmed (found on GitHub top repositories)
- Upstream record
- maziyarpanahi/openmed
- Version
- Version 1
- Published
- Publication review
- Approved for publication
- Content fingerprint
1e0573b91ea72d30f08eadd4f31c160e288e2d85cb34d9c4d5f899d6bfd5843e