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[ 原始碼： llama.cpp ]
套件：llama.cpp-tools-extra（5882+dfsg-3）
LLM inference in C/C++ - extra utilities
The main goal of llama.cpp is to enable LLM inference with minimal setup and state-of-the-art performance on a wide range of hardware - locally and in the cloud.
* Plain C/C++ implementation without any dependencies * Apple silicon is a first-class citizen - optimized via ARM NEON, Accelerate and Metal frameworks * AVX, AVX2, AVX512 and AMX support for x86 architectures * 1.5-bit, 2-bit, 3-bit, 4-bit, 5-bit, 6-bit, and 8-bit integer quantization for faster inference and reduced memory use * Custom CUDA kernels for running LLMs on NVIDIA GPUs (support for AMD GPUs via HIP and Moore Threads MTT GPUs via MUSA) * Vulkan and SYCL backend support * CPU+GPU hybrid inference to partially accelerate models larger than the total VRAM capacity
The compute functionality is provided by ggml. By default, ggml's CPU backend is installed, but there are many other backends for CPUs and GPUs.
This package contains all tools that are not already shipped in package llama.cpp-tools.
其他與 llama.cpp-tools-extra 有關的套件
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- dep: libc6 (>= 2.38)
- GNU C 函式庫：共用函式庫
同時作為一個虛擬套件由這些套件填實： libc6-udeb
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- dep: libcurl4t64 (>= 7.16.2)
- easy-to-use client-side URL transfer library (OpenSSL flavour)
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- dep: libgcc-s1 (>= 3.0) [除 riscv64]
- GCC 支援函式庫
- dep: libgcc-s1 (>= 3.4) [riscv64]
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- dep: libggml0 (>= 0.0~git20250712.d62df60)
- Tensor library for machine learning - libraries
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- dep: libllama0 (>= 5882+dfsg)
- LLM inference in C/C++ - libraries
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- dep: libstdc++6 (>= 14)
- GNU Standard C++ Library v3
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- dep: llama.cpp-tools (= 5882+dfsg-3)
- LLM inference in C/C++ - main utilities