On-device LLM deployment via CoreML
16 repos
Quantized and optimized versions of large language models (Qwen, Gemma, and other architectures) compiled to Apple's CoreML format for efficient inference on iOS devices and Apple Silicon hardware. These repositories focus on making modern language models run locally on mobile and edge devices through aggressive quantization (often 4-bit or lower), stateful execution for efficient token generation, and native Swift/iOS integration. Useful for anyone building privacy-preserving, latency-sensitive LLM applications on Apple platforms.
Python · 1
Swift · 1
coreml ·2,064
ios ·2,050
machine-learning ·2,049
swift ·2,049
apple-silicon ·1,877
mlpackage ·1,864
coremltools ·1,864
core-ai ·1,863
deep-learning ·1,863
gan ·1,863
