GGML

GGML (Generic Graph Machine Learning) is a powerful tensor library catering to the needs of machine learning practitioners. It is written in C, offering efficiency and compatibility across platforms. GGML supports 16-bit floating-point operations, which reduce memory requirements and improve computation speed. It also enables integer quantization, allowing optimization of memory and computation by quantizing model weights and activations to lower bit precision. GGML is ideal for training large-scale machine learning models that require extensive computational resources and for high-performance computing tasks in machine learning. It provides a robust set of features and optimizations that enhance the training of models and high-performance computing on commodity hardware.