Efficient LLM Inference with llama.cpp in C/C++

llama.cpp is an open-source project designed for LLM inference using C/C++. It aims to provide high-performance inference capabilities with minimal setup, making it suitable for a variety of hardware configurations, both locally and in the cloud.

Key features:

• Plain C/C++ implementation - no dependencies required.
• Optimized for Apple Silicon - utilizes ARM NEON, Accelerate, and Metal frameworks.
• Support for multiple architectures - includes AVX, AVX2, AVX512 for x86 and RVV for RISC-V.
• Flexible quantization options - supports 1.5-bit to 8-bit integer quantization for improved performance.
• Custom CUDA kernels - enables efficient execution on NVIDIA GPUs.

The project serves as a platform for developing new features for the ggml library and supports a wide range of models from various sources, including Hugging Face.