#cplusplus #ggml #llama
The `llama.cpp` project allows you to run large language models (LLMs) like LLaMA and others with high performance on various hardware, including local machines and cloud services. Here are the key benefits It works on Apple Silicon, x86 architectures, NVIDIA, AMD, and Moore Threads GPUs, as well as CPUs, ensuring you can use it on a wide range of devices.
- **Optimized Performance** You can build and run the project locally, install it via package managers, use Docker images, or download pre-built binaries.
- **Extensive Model Support** It includes tools like `llama-cli` for simple text completion, `llama-server` for setting up an HTTP server, and `llama-perplexity` for measuring model quality.
This makes `llama.cpp` a powerful and flexible tool for anyone looking to work with LLMs efficiently.
https://github.com/ggerganov/llama.cpp
The `llama.cpp` project allows you to run large language models (LLMs) like LLaMA and others with high performance on various hardware, including local machines and cloud services. Here are the key benefits It works on Apple Silicon, x86 architectures, NVIDIA, AMD, and Moore Threads GPUs, as well as CPUs, ensuring you can use it on a wide range of devices.
- **Optimized Performance** You can build and run the project locally, install it via package managers, use Docker images, or download pre-built binaries.
- **Extensive Model Support** It includes tools like `llama-cli` for simple text completion, `llama-server` for setting up an HTTP server, and `llama-perplexity` for measuring model quality.
This makes `llama.cpp` a powerful and flexible tool for anyone looking to work with LLMs efficiently.
https://github.com/ggerganov/llama.cpp
GitHub
GitHub - ggml-org/llama.cpp: LLM inference in C/C++
LLM inference in C/C++. Contribute to ggml-org/llama.cpp development by creating an account on GitHub.