Пакет: llama.cpp-tools (8064+dfsg-2)

[ Източник: llama.cpp  ]

LLM inference in C/C++ - main 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 the subset of the most commonly used utilities: llama-cli, llama-server, llama-bench, and llama-quantize.

Други пакети, свързани с llama.cpp-tools

• dep: adduser

  add and remove users and groups

• dep: libc6 (>= 2.38)

  GNU C Library: Shared libraries
  също и виртуален пакет, предлаган от libc6-udeb

• dep: libgcc-s1 (>= 3.0)

  GCC support library

• dep: libggml0 (>= 0.9.6)

  Tensor library for machine learning - libraries

• dep: libllama0 (= 8064+dfsg-2)

  LLM inference in C/C++ - libraries

• dep: libssl3t64 (>= 3.0.0)

  Secure Sockets Layer toolkit - shared libraries

• dep: libstdc++6 (>= 14)

  GNU Standard C++ Library v3

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amd64	3 526,8 кБ	14 995,0 кБ	[списък на файловете]