GGML
ggml is a machine learning tensor library written in C that provides high performance and large model support on commodity hardware. The library supports 16-bit floats, integer quantization, automatic
ggml is a machine learning tensor library written in C that provides high performance and large model support on commodity hardware. The library supports 16-bit floats, integer quantization, automatic
Integer quantization
reduces model size and memory requirements whilst maintaining reasonable accuracy
16-bit float support
balances precision and performance for faster computation
Automatic differentiation
enables model training and fine-tuning directly within the library
Hardware optimisation
includes specific implementations for Apple Silicon, AVX/AVX2 x86 processors, and WebAssembly
Zero runtime memory allocations
pre-allocates memory upfront for predictable performance
Built-in optimisation algorithms
includes ADAM and L-BFGS for training workflows
Running voice recognition systems on Raspberry Pi devices
Deploying language models on personal machines whilst keeping data private
Building multi-instance AI services on Apple devices
Creating offline AI features in mobile and web applications
Fine-tuning models with limited computational resources