GGML is a C-based tensor library that offers efficient and compatible implementation for machine learning practitioners. It supports 16-bit floating-point operations and integer quantization, which helps optimize memory usage and computation speed.

Features:

• C-based implementation for efficiency and compatibility
• 16-bit floating-point support for reduced memory requirements and improved computation speed
• Integer quantization for memory and computation optimization

Benefits:

• Large-scale model training with minimal memory usage and faster computation
• High-performance computing tasks with optimized memory and computation

Use Cases:

• Large-scale model training for machine learning
• High-performance computing tasks in machine learning