The llama.cpp project aims to enable LLM inference with minimal setup and high performance on various hardware, including Apple silicon and x86 architectures. It supports integer quantization for faster inference and reduced memory use, as well as custom CUDA kernels for running LLMs on NVIDIA GPUs. The project also offers backend support for Vulkan, SYCL, and OpenCL, and allows for CPU+GPU hybrid inference. To get started, users can clone the repository, build the server, download gguf models from Hugging Face, and run the server locally. Once the server is up, users can access it at localhost:8080 to set preferences and start chatting. The project provides a visual reference through a YouTube video.
Source link
Source link: https://medium.com/free-or-open-source-software/how-to-build-llama-cpp-on-macos-and-run-large-language-models-6aa53c7c056b?source=rss——large_language_models-5
in AI Medium
Compiling llama.cpp and executing language models on MacOS #programming
Preeti
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