spb/zyquo-mlx Public MIT
The local MLX foundry for your Mac — run, fine-tune, quantize, and ship models. Nothing leaves your machine.
Swift 93.4%
Python 3.8%
Makefile 2.2%
Shell 0.5%
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phase3: foundry core — PyBridge (PythonRunner, uv venv env, JSON-protocol scripts), DatasetService, TrainingService/RunStore/MetricsStream, ConversionService (Swift quant + Py fuse/convert), CLI drivers
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Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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phase2: architecture + inference POC — domain models, InferenceEngine actor, ModelStore, MemoryAdvisor, CLI POC (LLM 603 tok/s + embeddings verified)
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Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>